Neuronal control of leech behavior

Transcription

1 Progress in Neurobiology 76 (2005) Neuronal control of leech behavior William B. Kristan Jr. a, Ronald L. Calabrese b, W. Otto Friesen c, * a Section of Neurobiology, Division of Biological Sciences, 9500 Gilman Dr., University of California, San Diego, La Jolla, CA , USA b Department of Biology, Emory University, 1510 Clifton Road, Atlanta, GA 30322, USA c Department of Biology, Gilmer Hall, University of Virginia, P.O. Box , Charlottesville, VA , USA Received 7 April 2005; received in revised form 23 August 2005; accepted 26 September 2005 Abstract The medicinal leech has served as an important experimental preparation for neuroscience research since the late 19th century. Initial anatomical and developmental studies dating back more than 100 years ago were followed by behavioral and electrophysiological investigations in the first half of the 20th century. More recently, intense studies of the neuronal mechanisms underlying leech movements have resulted in detailed descriptions of six behaviors described in this review; namely, heartbeat, local bending, shortening, swimming, crawling, and feeding. Neuroethological studies in leeches are particularly tractable because the CNS is distributed and metameric, with only 400 identifiable, mostly paired neurons in segmental ganglia. An interesting, yet limited, set of discrete movements allows students of leech behavior not only to describe the underlying neuronal circuits, but also interactions among circuits and behaviors. This review provides descriptions of six behaviors including their origins within neuronal circuits, their modification by feedback loops and neuromodulators, and interactions between circuits underlying with these behaviors. # 2005 Elsevier Ltd. All rights reserved. Keywords: Elemental oscillators; Interneurons; Serotonin Contents 1. Introduction Anatomy and electrophysiology The hydroskeleton and behaviors Circulation and heartbeat The heartbeat neural control system of the leech The elemental oscillators Mechanisms of oscillation in an elemental half-center oscillator Coordination in the beat timing network Heartbeat motor pattern switching by switch interneurons Gaps in our current knowledge Overt behaviors Introduction Local bending Motor neurons Mechanosensory neurons that produce local bending Local bend interneurons The local bend response as a directed behavior Gaps in our current knowledge * Corresponding author. Tel.: ; fax: address: wof@virginia.edu (W.O. Friesen) /$ see front matter # 2005 Elsevier Ltd. All rights reserved. doi: /j.pneurobio

2 280 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Shortening Whole-body shortening Local shortening Gaps in our knowledge Swimming History: reflex chain versus central pattern generator Swimming behavior and motor control Central oscillator circuits Control of swimming activity Neuromodulatory control: serotonin and other biogenic amines Role of sensory feedback Functional aspects of the central oscillator Gaps in our current knowledge Vermiform crawling Behavior Kinematics Motor neuron activity Sensory input Models Initiation of crawling Gaps in our current knowledge Feeding Behavior Chemosensation Motor patterns Regulation and plasticity Gaps in our knowledge Interactions among behaviors Methodologies and approaches for further research Functional indicator dyes Modeling Plasticity Development Conclusion Acknowledgements References Introduction The major goal of neurobiology is to understand how the brain works: how it senses the external world and internal states, how it processes this sensory input, how it evaluates different inputs to select an appropriate motor act, and how it generates that behavior. One approach to studying these questions is to study the function of a particular neural structure (e.g. the superior colliculus or the habenular nucleus) in a complex brain and ask how it works. Another approach is to select a behavior and ask how the properties of neurons and their interconnections produce that behavior. The latter approach is the more direct, but is possible only in animals with relatively simple nervous systems, or in selected parts of complex nervous systems with neurons that are identifiable from animal to animal. For example, behavioral circuits have been described in a number of such animals: mollusks (Arshavsky et al., 1998; Satterlie et al., 2000; Brembs et al., 2002; Dembrow et al., 2003; Sakurai and Katz, 2003; Jing and Gillette, 2003; Staras et al., 1999; Bristol et al., 2004), crustaceans (Selverston et al., 2000; Teshiba et al., 2001; Prinz et al., 2003; Beenhakker et al., 2004), insects (Sasaki and Burrows, 2003; Wang et al., 2003; Riley et al., 2003; Wilson et al., 2004; Daly et al., 2004), amphibians (Roberts et al., 1999; Combes et al., 2004), fish (Higashijima et al., 2003; Grillner, 2003), and rodents (Sekirnjak et al., 2003; Kiehn and Butt, 2003; Yvert et al., 2004). Rhythmic movements such as chewing, respiratory movements, locomotory movements, and, in some animals, heartbeat are of particular interest because of their combination of complex dynamics and relative stereotypy (Marder and Calabrese, 1996; Stein et al., 1997; Orlovsky et al., 1999). Oscillatory networks of central neurons are important components of most such motor patterngenerating networks. The anatomical wiring and synaptic connectivity within a network is the backbone on which intrinsic and synaptic properties of component neurons operate to produce network dynamics. The states of these intrinsic and synaptic properties are themselves dynamic, being subject to modulation through a multiplicity of sensory inputs provided by neurons extrinsic and intrinsic

3 to the network (Katz, 1995; Harris-Warrick et al., 1997; Nusbaum et al., 1997). A very useful animal for establishing the neuronal bases of behaviors has been the leech, particularly the European medicinal leech, Hirudo medicinalis. In this animal, more behaviors have been studied in neuronal terms than in any other. This review provides an overview of all the behaviors that have been studied, and an update of less comprehensive but more detailed reviews that have appeared elsewhere (Brodfuehrer et al., 1995b; Calabrese et al., 1995; Kristan et al., 1995). There is always the possibility that the neuronal mechanisms found in a particular animal will be unique to that animal, due to its specific evolutionary history and individual peculiarities of anatomy and biomechanics. We, however, believe the opposite: that there are general strategies for producing behaviors that will be found in all animals with a central nervous system (CNS). There are many technical reasons why the medicinal leech is an auspicious animal for identifying behaviorally relevant neuronal systems. Some of the reasons are generally true of simple animals, and others are true of the leech in particular. It is worth enumerating the list to indicate why the medicinal leech has been so useful in studying the neuronal bases of behaviors: W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) The leech nervous system is relatively simple (Fig. 1A) and readily accessible even while the animal is behaving in a variety of semi-intact preparations (Fig. 1B), making it possible to relate motor patterns directly to behaviors. 2. Quite accurate representations of all the behaviors, or at least their rudiments, can be elicited in isolated nerve cords (Fig. 1B), where intracellular and optical recording is more favorable. 3. The neurons are easily seen and readily identified, based on the location of their somata (Fig. 1C), morphology (Fig. 1D), and physiological properties. 4. Intracellular neuronal activity can be recorded readily because the somata are relatively large (10 80 mm) and every soma is visible in segmental ganglia. These properties also make optical recording feasible. 5. Long, easily accessible peripheral nerves allow for stimulation of selected neurons and monitoring of neuronal activity with extracellular electrodes. 6. Most relevant electrical parameters can be measured. Intracellular recordings from somata reveal relatively large, individual synaptic potentials, which are not greatly attenuated from their origins in the neuropil, and attenuated action potentials. 7. The nervous system is iterated, with homologous neurons found in most, if not all, 21 segmental ganglia (Fig. 1). So despite having more than 10,000 neurons, the functional unit (i.e. the number of different kinds of neurons) of the leech CNS is relatively small. For instance, there are only 400 neurons per segmental ganglion (Macagno, 1980), and most of these are paired. Thus, in essence, the segmental nerve cord (roughly corresponding to the spinal cord in vertebrates) consists of 42 copies (one on each side of 21 segments) of a basic unit of 200 neurons. Fig. 1. Anatomy of the medicinal leech and its nervous system. (A) Schematic diagram of the leech, showing the major features of its nervous system. There are 21 segmentally homologous midbody ganglia, numbered M1 M21. The anterior brain (inset) consists of a supraesophageal ganglion (sup.) that is part of the prostomium, plus a subesophageal ganglion (sub.), which forms from the coalescence of the four most anterior embryonic ganglia that are visible in the adult brain as neuromeres 1 4. (B) Types of preparations used to study the neuronal bases of leech behaviors. The kinematics of all behaviors have been characterized in intact animals (top panel) by measuring the distances between markers placed on the external body wall in successive frames of a movie or video. A variety of semi-intact preparations (example in middle panel) have provided intracellular and extracellular recordings during each of the behaviors, thereby revealing the underlying motor neuronal firing patterns. The isolated nervous system (bottom panel), in its entirety or in pieces, produces motor patterns that are distinguishable as the neuronal substrates of each of the behaviors. Such preparations are the most useful for electrophysiological characterizations of neuronal properties and synaptic connections. (C) Schematic view of the ventral surface of a midbody ganglion, indicating the arbitrary numbering scheme used to identify ganglionic neurons. Most midbody ganglia have the same neurons and locations of the soma. The dotted lines indicate the packet margins formed by the six giant glial cells, each of which encapsulates characteristic clusters of neuronal somata. The scale bar (200 mm) indicates the size of a midbody ganglion in a mature leech weighing 2 5 g. The functions of about a third of the neurons are known. (D) Structure of a single neuron. Dye, injected into the soma, diffused into the processes in the center of the ganglion, where all synaptic contacts are made. This region is termed the neuropil. This neuron, cell 208, has extensive, bilaterally symmetric branches and sends a single axon posteriorly down one of the two lateral connectives (the small, medial connective is called Faivre s nerve ). Based upon the location of its soma and its branching pattern, each neuron has a distinctive morphology. The scale bar in D represents 100 mm.

4 282 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Most neurons in the CNS are unique rather than members of functionally identical clusters, hence activating or ablating single neurons (irreversibly by killing or reversibly by hyperpolarization) often has behaviorally detectable consequences. Because of these favorable features, it is possible, in principle, to identify every neuron that contributes substantially to any leech behavior. In practice, this task is far from trivial, so that no single behavior has yet been completely characterized. In no other system, however, have so many behaviors been investigated and described at the neuronal circuit level. This review is intended to provide a brief overview of the state of what is known, and what remains to be known about the most completely described behaviors. To understand these descriptions, background information concerning basic leech anatomy and electrophysiology is essential. After this introduction, the neuronal circuits underlying six different behaviors are discussed individually, followed by a discussion of how these circuits interact. A final section provides a vision of how the leech may prove useful for future research Anatomy and electrophysiology Leeches are annelids, all of which are segmented worms (Fig. 1A). Unlike most other annelids, leeches have a fixed number of segments 32 plus an anterior non-segmental region called the prostomium. The segments form as a repeated iteration of divisions of the same stem cells, whereas the prostomium is derived from a different set of stem cells (Stent et al., 1992). The prostomium and the most anterior four segments form the head and the most posterior seven segments form the tail. There are a variety of specializations in the head and tail, the most striking of which are the suckers. The mouth is in the middle of the front sucker, whereas the anus is located in the body wall anterior and dorsal to the posterior sucker. At rest, the posterior sucker is usually attached to the substrate. The anterior end is used to explore the environment, so that the anterior sucker is typically attached only when the leech is crawling or feeding. The body is a tube formed by epidermis and muscles, which encases the internal organs: the gut and intestines, the nephridia and urinary sacs, the reproductive organs, and the blood vessels (Fig. 2A). The circulatory system of a leech is closed, with four major longitudinal blood vessels that run the length of the leech and a mesh of circumferentially directed vessels connecting them. The dorsal and ventral longitudinal vessels are passive (they function as veins) and the lateral tubes are contractile (they function as hearts). The leech CNS consists of a ventral nerve cord with a brain at each end (Fig. 1A). Each segment contains a single ganglion, which communicates with the adjacent anterior and posterior ganglia via three connectives (a pair of large lateral connectives and a smaller medial connective, known as Faivre s Nerve). The four anterior ganglia fuse during embryogenesis to form a subesophageal ganglion, and a supraesophageal ganglion forms within the prostomium. The borders of these individual ganglia are visible in the adult. The neuronal compartments of the four ganglia are called neuromeres. Together, the supraesophageal and subesophageal ganglia form the anterior brain (sometimes called the head brain). Similarly, the last seven ganglia in the chain fuse embryonically to form the posterior brain (also called the tail brain). The neuromeres in the anterior brain are denoted as R1 4 (rostral neuromeres 1 4), those in the posterior brain are C1 7 (caudal neuromeres 1 7), and the individual, mid-body ganglia are labeled M1 M21. Neuronal somata within the CNS are roughly spherical, and are located on the surface of segmental ganglia and terminal brains. In midbody ganglia, somata are in 10 clusters four on the dorsal surface and six on the ventral surface delineated by giant glial cells that effectively engulf the somata of dozens of neurons. In fact, modern-day characterization of the function of leech neurons began with a series of elegant studies by Stephen Kuffler and his colleagues using these giant glial cells to study the electrical properties and potential functions of glia (Kuffler and Potter, 1964; Nicholls and Kuffler, 1964). They concluded that the membranes of these glial cells are nearly perfect K + electrodes, and that their contributions to the electrical function of the nervous system is to sequester K + ions released by active neurons in order to buffer the effects of local release of the K +. These giant glial cells, therefore, gather the neuronal somata into packets, with the lateral edges serving as packet margins that provide useful markers for identifying neurons. The ventral surface of a typical midbody ganglion is shown in Fig. 1C. Most or all of the leech central neurons are identifiable from animalto-animal and segment-to-segment on the bases of the size and location of their somata within a cluster, as well as their characteristic electrophysiological properties and morphological features (Muller et al., 1981). All neurons in the leech CNS are monopolar: a single process extends from each soma. Typically, this process gives rise to one or more axons that leave the ganglion, via nerves to the periphery in the case of sensory and motor neurons (MNs), and via the connectives in the case of interneurons (INs) and some sensory and secretory neurons. Secondary branches emerge from the main process; these side branches may subdivide to generate many orders of branching (Fig. 1D). Synaptic connections are made primarily on these fine branches. All the ganglionic MNs that send axons via segmental nerves to muscles in the body wall (Stuart, 1970; Ort et al., 1974; Norris and Calabrese, 1987) and to the lateral heart tubes (Thompson and Stent, 1976a) are located within the CNS. The muscles used by the leech to make overt movements are of four types: longitudinal, circular, oblique, and dorsoventral (Fig. 2B). Contractions of each of these muscles produce characteristic types of movements: longitudinal muscle contractions produce shortening, circular muscle contractions produce a reduction in cross-section and elongation, oblique muscle contractions cause stiffening at an intermediate body length, and dorsoventral muscle contractions cause a flattening of the body and contribute to elongation. Each MN connects to a single muscle type, and only to muscle fibers on either the left or right side of its own segment, and then only to a regional subset of muscle fibers. For instance, MNs both excitatory and

5 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 2. Schematic views of a leech midbody segment. (A) Cut-away view of the middle of a leech, showing the location of the central nervous system, major peripheral nerves, blood vessels, viscera, and musculature. Each midbody ganglion connects to adjacent ganglia via connectives and to the periphery through characteristic nerves. The four major longitudinal blood vessels (heart tubes) connect to one another via circumferential blood vessels. The lateral longitudinal blood vessels are contractile and serve as hearts. The ventral nerve cord is suspended in the ventral blood vessel, which, like the dorsal vessel, is passive. A rich capillary vascularization of the skin provides for gas exchange in these aquatic animals, so that the skin effectively functions as a gill. (B) A simplified schematic diagram, emphasizing the geometric relationships of the muscle groups used to produce the behaviors shown in Fig. 3. Contractions of circular muscles produce elongation, longitudinal muscles produce shortening, and dorsoventral (DV) muscles produce flattening. Oblique muscles stiffen the animal at a length intermediate between maximal contraction and maximal elongation. Not shown are annulus erector muscles, located in the skin, that cause the individual annuli (five per segment in the midbody) to form peaked ridges around the animal. inhibitory that project to longitudinal muscles, innervate either dorsal, dorsolateral, lateral, ventrolateral, ventral, or dorsolateroventral regions (Stuart, 1970). The excitatory neuromuscular transmitter is ACh (Sargent, 1977) and the inhibitory transmitter is GABA (Cline, 1986). Activity of various combinations of these MNs in different temporal patterns produce the behaviors described in subsequent sections. Leeches have a variety of sensory receptors. For instance, there are light-sensitive receptors in the sensilla located in each segment and in the eyes (a pair of expanded sensilla located on the lateral edge of each of the first five segments) (Kretz et al., 1976); chemoreceptors, in placodes on the upper lip (Elliott, 1987); stretch receptors, embedded in the dorsal, lateral, and ventral body wall of each segment (Blackshaw et al., 1982; Blackshaw and Thompson, 1988; Blackshaw, 1993; Cang et al., 2001); and mechanoreceptors of different sorts. There are ciliated mechano-receptive neurons whose somata are in the sensilla (DeRosa and Friesen, 1981; Phillips and Friesen, 1982) and respond to movements of the water (Brodfuehrer and Friesen, 1984). There are also mechanoreceptors with somata in the CNS (Nicholls and Baylor, 1968) that have free nerve endings in the skin (Blackshaw, 1981) and respond to different intensities of stimulation to the skin: light touch (T cells), pressure (P cells), and noxious stimuli (N cells). These neurons have primary

6 284 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) receptive fields within their own segment, and secondary ones (via axons through connectives) in the adjacent ganglia both anterior and posterior. There are three pairs of T cells and two pairs of P cells. The receptive fields of these cells divide up the body wall into roughly equal, overlapping receptive fields around the circumference of the animal. There are two pairs of N cells in each ganglion, each of which innervates half the ipsilateral body wall. All the N cells respond to noxious mechanical stimuli, but the two on each side differ in their responses to other stimuli, such as heat and low ph (Pastor et al., 1996). The great majority of the neuronal somata within the leech CNS, as in other animals, are neither sensory nor MNs; rather they are INs without direct connection to the periphery. These INs were identified largely by methodically searching for neurons associated with specific behaviors. For example, specific neurons were identified when intracellular current injection evoked (or terminated) a behavior in either semi-intact preparations, or fictive behavior in the isolated CNS. Using this technique, INs were found that participate in seven behaviors: heartbeat (Thompson and Stent, 1976b), local bend (Lockery and Kristan, 1990b), shortening (Shaw and Kristan, 1995), swimming (Friesen et al., 1978; Weeks, 1982a,b,c; Friesen, 1985, 1989b; Brodfuehrer and Friesen, 1986a,b,e), crawling (Eisenhart et al., 2000), reproduction (Zipser, 1979) and feeding (Zhang et al., 2000). It is largely true that homologs of each of the neurons found in one ganglion can be found in the remaining 20 segments. There are exceptions to this general rule, which are pointed out in the sections below. In addition, homologs of the Retzius neurons (Lent, 1977) and several mechanosensory neurons (Yau, 1976) have been found in the neuromeres of the subesophageal ganglion, although many of the INs in the subesophageal ganglion do not appear to have homologs in the segmental ganglia (Brodfuehrer and Friesen, 1986a,b,c,e). This ability to identify a particular neuron in segment after segment and in animal after animal has greatly aided the characterization of neuronal circuits. In addition, this stereotypy has led to the notion that all neurons within the leech CNS are unique (with the possible exception of the PE cells (Baptista and Macagno, 1988), neurons that develop postembryonically in the ganglia of segments 5 and 6, which are the reproductive segments of leeches). The leech was developed as a neurophysiological preparation in the 1930 s by Gray et al. (1938), who studied the neuronal bases of leech swimming and crawling. The first intracellular recordings were accomplished in the early 1960 s, when Hagiwara and Morita (1962) and Eckert (1963) recorded intracellularly from the somata of the paired Retzius neurons in segmental ganglia of Hirudo. They both showed convincingly that these neurons are strongly electrically coupled. They also demonstrated that at least two of the neurons in each ganglion were identifiable by the location and size of their somata, as well as their electrophysiological properties. The identification and characterization of leech neurons advanced greatly when John Nicholls chose to identify neurons that had been used in the laboratory of Stephen Kuffler to characterize the electrophysiological properties of glial cells and their effects on the electrical function of neurons (Kuffler and Potter, 1964). The Nicholls lab identified mechanosensory neurons (Nicholls and Baylor, 1968) and MNs (Stuart, 1970) in stereotyped locations within each segmental ganglion. They showed that these sensory neurons made both electrical and chemical synaptic connections onto the MNs, and also established a number of physiological techniques to suggest strongly that these connections were direct, monosynaptic contacts, without any intervening INs (Nicholls and Purves, 1970). Subsequently, several other MNs have been identified (Ort et al., 1974; Thompson and Stent, 1976a; Sawada et al., 1976; Norris and Calabrese, 1987). Many of these MNs are inhibitory (Stuart, 1970; Sawada et al., 1976; Ort et al., 1974), releasing GABA onto muscle fibers to hyperpolarize them and cause their relaxation (Cline, 1986). Surprisingly, at least some of the inhibitory MNs also make strong central connections, with both excitatory and inhibitory MNs (Ort et al., 1974; Granzow et al., 1985; Granzow and Kristan, 1986; Friesen, 1989a), and with INs (Friesen, 1989b) The hydroskeleton and behaviors Leeches perform a variety of distinguishable behaviors by combinations of lengthening, shortening, and bending. Fig. 3 shows five of these behaviors: local bending, swimming, whole-body shortening, crawling, and feeding. Each behavior is produced by a characteristic temporal and spatial pattern of muscle contractions. The nature of these motor patterns is discussed below, in individual sections devoted to each of the behaviors. Leeches have no hard, fixed skeleton. Instead, they use a muscular arrangement that has been termed a muscularhydrostat (Kier and Smith, 1985) or a hydroskeleton (Kristan et al., 2000). The leech body is a tube whose shape is controlled by muscles in each segment. To a first approximation, each segment is a cylinder with an ovoid cross-section (Fig. 2B); a segment maintains roughly the same volume during all behaviors. The muscles used to produce the behaviors shown in Fig. 3 are the longitudinal and circular layers in the body wall, plus the dorsoventral muscles that span the body cavity. Contraction of one muscle type changes the shape of the cylinder by increasing internal pressure, stretching the other muscle types. Hence, each of these three muscle types is potentially an antagonist for the other two sets of muscles. The body stiffness, which acts like a skeleton, is caused by cocontraction of antagonistic muscles or, for some behaviors, by contraction of a fourth set of muscles, the oblique muscles. These latter, thin muscles, which lie between the longitudinal and circular muscles, are oriented obliquely, so that their contraction stiffens the body at an intermediate body length the posture seen in a leech at rest. In effect, leeches have a degree of freedom not available to skeletized animals: they can control the stiffness of their skeleton dynamically during a behavior. A single segment can perform four types of basic movements: (1) bending, by contracting the longitudinal muscles on one side; the longitudinal muscles on the opposite side may also relax;

7 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) (2) shortening, by contracting all longitudinal muscles at the same time; (3) elongation, by contracting the circular muscles and (4) flattening, by contracting the dorsoventral muscles. (Note that flattening also produces elongation). Fig. 3. Examples of leech behaviors. (A) Local bending: pressing on the skin at any location around the leech s surface (e.g. dorsal, ventral, lateral) causes contraction of the longitudinal muscles at the site of the touch, and relaxation of the longitudinal muscles on the opposite side. (B) Swimming: successive frames of a film of a swimming leech, from the side, taken at 50 ms intervals. A quasisinusoidal wave of dorsoventral contractions moves from the front of the leech (at left) to the back. The trough of the wave is produced by local contractions of the dorsal longitudinal muscles, and the crest is produced by contractions of the ventral longitudinal muscles. The whole body is strongly flattened throughout the swim cycle. In a single segment, swimming consists of repeating alternations between dorsal and ventral longitudinal contractions. The rearward progression of the traveling waves results from an intersegmental delay in longitudinal muscle contractions. This delay varies in proportion to the cycle period to maintain approximately one waveform in the body at all cycle periods (the normal range being s). The white dots at four locations along the animal s body are white beads sewn onto the lateral edge of the leech at specific locations. The 12 frames shown constitute one swim cycle (note that the body shape in the last frame is very similar to that seen in the first frame). (C) Wholebody shortening: when the front end of the leech is touched (top frame), it pulls back rapidly (bottom frame) by contracting the longitudinal muscles in all body segments simultaneously. (There is a short intersegmental delay, caused by spike conduction between segments, but this delay is much shorter than the delays seen in swimming.) This response is greatest when the animal is fully elongated. (D) Crawling: schematic drawings of six characteristic stages of vermiform crawling. In the top trace, the animal has shortened fully and attached both suckers. The step begins with release of the front sucker (to the right) and the beginning of a wave of elongation at the front end produced by contraction of the circular muscles (second frame). The circular muscle-induced elongation moves back along the animal until the body is fully extended; at this point, the front sucker attaches (third frame). With both suckers attached, the elongation at the front end is replaced by contraction (fourth frame), caused by relaxation of the circular muscles and contraction of the longitudinal muscles. This contraction moves back along the animal, pulling on the posterior end and lengthening it. As the contraction wave moves through the back half of the animal, the back sucker releases (fifth frame). The cycle is completed when the contraction wave reaches the rear end and the back sucker is reattached (sixth frame). (E) Feeding: shown is a typical posture during the consummatory phase of feeding. The back sucker can be attached to the host or, as shown here, it can be floating free. The front sucker is tightly attached to the skin surface and the The first four behaviors illustrated in Fig. 3 are caused by different temporal and spatial patterns of these segmental movement units. Local bending (Fig. 3A) occurs in a small number of adjacent segments (1). Whole-body shortening (Fig. 3C) takes place in the whole animal almost simultaneously (2). In swimming (Fig. 3B), flattening of the whole body (4) is maintained throughout swimming episodes, and serves to stiffen the body and present a wide surface to the water. During swimming, each segment alternately bends dorsally and ventrally, with each segment producing the same movement as its more anterior neighbor at a phase delay of about 5%. This produces a repeated up-and-down undulation with about one peak and one trough in the body at any given time (Kristan et al., 1974a). Crawling (Fig. 3D) is also an oscillatory locomotory pattern, but in this case shortening (2) alternates with elongation (3) in each segment. Again, whatever occurs in a given segment is repeated in the next segment with a delay of about 5% of the cycle period. Compared to swimming, crawling cycles are slow: swim cycles are s in duration (Kristan et al., 1974a,b; Kristan and Calabrese, 1976), whereas crawling cycles are 2 20 s in duration (Stern-Tomlinson et al., 1986; Cacciatore et al., 2000). The action of the suckers is important in shortening and crawling, but very little is known about their muscular or neuronal control. The typical feeding posture (Fig. 3E) is with one or both suckers attached. The jaws evert through the front sucker, rasp a hole in the skin of the prey, and blood is sucked through the oral opening in this sucker. Specialized internal muscles in the pharynx produce the suction that brings the blood into the body, but longitudinal muscles produce a peristalsis that moves blood into the various chamber of the gut (Wilson and Kleinhaus, 2000). 2. Circulation and heartbeat Heartbeat is an autonomic function that is rhythmic and continuous in Hirudo medicinalis. The circulatory system is a closed network comprising four longitudinal vessels one dorsal, one ventral, and two lateral that run the length of the animal, communicating in every segment by a series of branched vessels (Fig. 2A). Rhythmic constrictions of the muscular lateral vessels (the heart tubes) drive the flow of blood through the closed circulatory system (Thompson and Stent, 1976a). The heart muscle can generate a myogenic rhythm of contractions, which are normally entrained by patterned rhythmic motor outflow from segmental ganglia. The hearts are coordinated so that one beats in a rear-to-front progression anterior end is held in a characteristic, rigid posture with pulsations at 2 4 Hz reflecting the sucking movements made by the pharyngeal muscles in the anterior end. The rest of the body produces slower movements, either undulations or peristaltic movements (see Fig. 25) that move the ingested blood into the gut pouches (see Fig. 2A). Scale bar, 2.5 cm.

8 286 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) (peristaltically), whereas the other one beats synchronously along most of its length. The peristaltic side produces high systolic pressure and forward flow of blood in the heart tubes, whereas the synchronous side produces low systolic pressure and blood flow into the peripheral circulation (Krahl and Zerbst-Boroffka, 1983; Hildebrandt, 1988; Wenning et al., 2004a,b) The heartbeat neural control system of the leech The hearts are innervated in each segment by heart excitatory (HE) MNs, a bilateral pair of neurons found in each of the third through 18th segmental ganglia (i.e. M3 M18) (Thompson and Stent, 1976a,b). Each HE MN contacts heart muscle directly and forms conventional cholinergic neuromuscular junctions (Maranto and Calabrese, 1984a,b; Calabrese and Maranto, 1986). The heart MNs are rhythmically active (Fig. 4C); they entrain the myogenic rhythm of the heart through rhythmic excitation. Thus the spatio-temporal activity pattern of the segmental heart MNs (the motor pattern) determines the constriction pattern of the hearts. This motor pattern is organized by a central pattern generator (CPG): the isolated ventral nerve cord continuously produces a heartbeat pattern that is similar in period and spatial pattern to the heart constrictions seen in the animal (Fig. 4C) (Calabrese and Peterson, 1983). The rhythmic activity pattern of the heart MNs derives from the cyclic inhibition that they receive from this CPG (Fig. 4). When these inhibitory inputs to the heart MNs are blocked by bicuculline, the MNs fire at a steady rate (Schmidt and Calabrese, 1992). There is an asymmetry in the heart constriction pattern that arises from an asymmetry in the motor pattern (Thompson and Stent, 1976b). That is, the same coordination modes peristaltic and synchronous observed in the two hearts are also seen in the HE MNs. The HE MNs on one side are active in a rear-to-front progression, while the HE MNs on the other are active nearly synchronously along most of the nerve cord (Calabrese and Peterson, 1983; Wenning et al., 2004b), and the coordination of the HE MNs along the two sides switches approximately every heartbeat cycles (Thompson and Stent, 1976b; Wenning et al., 2004a,b). Because switching between coordination states is produced by the isolated nerve cord, a CPG must produce this switching, too (Gramoll et al., 1994; Wenning et al., 2004b). The pattern generator comprises seven bilateral pairs of identified heart INs (HNs) that occur in the first seven segmental ganglia (Thompson and Stent, 1976c; Calabrese and Peterson, 1983). The connections made by heart INs are largely inhibitory; they inhibit each other, and those in M3, M4, M6, and M7 inhibit heart MNs (Fig. 4A and B) The elemental oscillators Because passing current into any one of the first four pairs of heart INs can reset and entrain the rhythm of the entire network of INs (Peterson and Calabrese, 1982), the heart INs in M1 M4 constitute the timing network of the heartbeat pattern generator Fig. 4. Activity and synaptic connectivity of heart excitatory (HE) MNs and heart interneurons (HN INs). (A) Circuit diagram showing the inhibitory synaptic connections from identified HN INs to HE MNs. (B) Circuit diagram showing the inhibitory synaptic connections among all the identified HN INs. Neurons with the same input and output connections are lumped together. In all circuit diagrams, large unfilled circles represent neurons (each identified by the number of its ganglion) and the lines represent major neurites or axons. Small filled circles represent inhibitory chemical synapses. (C) Simultaneous intracellular recordings showing the normal rhythmic activity of two reciprocally inhibitory oscillator heart INs of midbody ganglion 4, HN(R,4) and HN(L,4), and a heart MN HE(R,5) postsynaptic to HN(R,4) in an isolated nerve cord preparation. Dashed lines indicate a membrane potential of 50 mv. In all figures, the body side and ganglion number are indicated as in the following example: cell HN(L,1). (Fig. 4B). The other three pairs of heart INs are followers of these anterior pairs. Two foci of oscillation in this beat timing network have been identified in M3 and M4 (Peterson, 1983a). Reciprocally inhibitory synapses between the bilateral pairs of heart INs in these ganglia (Figs. 4B and 5A), combined with the intrinsic membrane properties of these neurons pace the oscillation (Peterson, 1983a,b; Cymbalyuk et al., 2002). Thus each of these two reciprocally inhibitory heart interneuronal pairs is an elemental half-center oscillator (Figs. 4B and 5A) and the M3 and M4 heart INs are called oscillator INs Mechanisms of oscillation in an elemental half-center oscillator Voltage-clamp studies have identified several intrinsic currents that contribute to the oscillatory activity of oscillator INs. These include:

9 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 5. Circuit diagram and electrical activity of the heartbeat-timing network. (A) The timing network consists of paired heart INs (HN) in the first four midbody ganglia (M1 M4). The first and second ganglia are represented as a single ganglion for simplicity. Large unfilled circles represent neurons (each identified by the number of its ganglion of origin) and the lines represent major neurites or axons, squares are distal sites of spike initiation, and small filled circles are inhibitory synapses. (B) Activity of a segmental oscillator. Simultaneous extracellular recordings of the paired oscillator INs in M3 made with a suction electrode placed snugly over the soma of each neuron. The two INs alternate in their activity. (C) Coordinated activity of the timing network. Simultaneous extracellular recordings of the coordinated activity of ipsilateral heart INs in M2 M4 made with suction electrodes. The oscillator INs in M3 and M4 are active nearly in-phase but with a perceptible phase lag of about 10% of the cycle period, while the coordinating IN is active in anti-phase (after Masino and Calabrese, 2002a). Please note that the literature on heartbeat uses an older designation for the midbody segmental ganglia: G1 G21, rather than M1 M21. a fast Na + current that mediates spikes; two low-threshold Ca 2+ currents [one rapidly inactivating (I CaF ) and one slowly inactivating (I CaS ); Angstadt and Calabrese, 1991]; three outward currents [a fast transient K + current (I A ) and two delayed rectifier-like K + currents, one inactivating (I K1 ), and one persistent (I K2 ); Simon et al., 1992]; a hyperpolarization-activated inward current (I h ), a mixed Na + /K + current with a reversal potential of 20 mv (Angstadt and Calabrese, 1989); a low-threshold persistent Na + current (I P ) (Opdyke and Calabrese, 1994). The inhibition between oscillator INs consists of a graded component that is associated with the low-threshold Ca 2+ currents (Angstadt and Calabrese, 1991) and a spike-mediated component associated with high-threshold Ca 2+ current (Simon et al., 1994; Lu et al., 1997; Ivanov and Calabrese, 2000). Spike-mediated transmission is sustained during normal bursting (Nicholls and Wallace, 1978; Ivanov and Calabrese, 2003), while graded transmission wanes during a burst because the low-threshold Ca 2+ currents inactivate (Angstadt and Calabrese, 1991). Modeling studies based on these biophysical measurements indicate that oscillation in an elemental half center oscillator is a subtle mix of escape and release (Fig. 6; Nadim et al., 1995; Olsen et al., 1995; Hill et al., 2001). Escape from inhibition is due to the slow activation of I h in the inhibited oscillator IN. Release from inhibition results from a waning of the depolarization in the active oscillator IN due to the slow inactivation of its I CaS, which slows its spike rate and thereby reduces its spike-mediated inhibition of the contralateral oscillator IN. A model of the half-center interactions was tested by voltage clamping oscillator INs using waveforms that mimic the slow wave of oscillation (Olsen and Calabrese, 1996). Quantitative estimates of I h, I P, and the low-threshold Ca 2+ currents, as well as their trajectories during oscillation, demonstrated that I h has a negative feedback relationship with period. Perturbations that produce a longer cycle period increase I h, thereby shortening the cycle period, whereas perturbations that produce a shorter period decrease I h, which increases the cycle period. Thus I h homeostatically regulates the heartbeat cycle period Coordination in the beat timing network The heart INs in M1 and M2 act as coordinating INs, serving to couple the two elemental oscillators (Fig. 5A). Together with the HN cells in M3 and M4, these INs form a beat timing network that paces the pattern generator and establishes the underpinnings of intersegmental coordination (Fig. 5A; Peterson, 1983a,b; Masino and Calabrese, 2002a). The INs in M1 and M2 do not initiate spikes in their own ganglion; instead they have two spike initiating sites, one in M3 and the other in M4. Normally, the great majority (>85%) of spikes in the coordinating neurons are initiated in M4, but under certain conditions spikes can also be initiated in M3 (Peterson, 1983a,b; Masino and Calabrese, 2002a). For example, when M3 and M4 are separated by cutting the connective, the processes of the coordinating neurons in M3 will initiate spikes. Thus, isolated M3 and M4 each contain a segmental oscillator that consists of a pair of reciprocally inhibitory oscillator INs (elemental half-center) and the active stumps of processes from the coordinating neurons, which provide additional inhibition (Hill et al., 2001). (Invertebrate axons may have neuritic branches (input and output) at several sites within the nervous system and thus have multiple, electrotonically distant sites of synaptic input, spike initiation, and synaptic output (Perrins and Weiss, 1998; Coleman et al., 1995).) The coupling between the M3 and M4 segmental oscillators causes the M3 and the M4 oscillator INs on the same side to be active roughly in phase (Fig. 5C). In an isolated beat timing network (M1 M4), the phase relationship between the oscillators is constant (i.e. their activity is phase-locked) but varies among preparations and whether the preparation is exposed to modulator substances. In the majority of unmodulated preparations, the M4 oscillator leads the M3 oscillator (Fig. 5C; Peterson, 1983a,b; Masino and Calabrese, 2002a). Because both the M3 and M4 oscillator INs provide inhibitory input to heart MNs, the phase relationships between the M3 and M4 segmental oscillators is important in determining the HE MN activity pattern. When the M3 and M4 segmental oscillators were reversibly uncoupled by blocking axonal conduction in the connectives between M3 and M4 with a sucrose solution, the intact phase difference proved to be

10 288 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 6. Synaptic conductances and some major intrinsic currents that are active during a single cycle of a two cell (half-center) heart IN oscillator model (Hill et al., 2001). (A) Biological neurons. (B) Model neurons. The graded synaptic conductance (g SynG ) is shown at the same scale as the total synaptic conductance (g SynTotal ), which is the sum of the graded and spike-mediated conductances. The slow calcium current (I CaS ), the hyperpolarization-activated current (I h ), and the persistent sodium current (I P ) are shown to the same scale. Note that I P is active throughout the entire cycle period. determined by the difference between the isolated periods in the segmental oscillators: the faster oscillator leads in phase, and the phase difference is nearly linearly related to the period difference (Masino and Calabrese, 2002c). Both the period difference between the segmental oscillators as well as their phase differences can be changed using neuromodulators and pharmacological agents (Masino and Calabrese, 2002b). Again, in these experiments, the period of the intact beat timing network was the same as the period of the faster segmental oscillator (Masino and Calabrese, 2002a,b; Hill et al., 2002). This rate dominance by the faster oscillator is likely to result from the faster oscillator beginning to fire earlier in each cycle, thereby silencing the ipsilateral coordinating INs and removing their inhibition onto the slower oscillator, thus speeding up the slower oscillator s rhythm. The feasibility of this conceptualization has been shown in modeling studies (Hill et al., 2002, 2003; Jezzini et al., 2004) Heartbeat motor pattern switching by switch interneurons Switching between the peristaltic and synchronous modes (Fig. 7A) is accomplished by a pair of switch INs whose somata are in M5. The M3 and M4 oscillator INs on one side inhibit the switch heart IN on the same side (Figs. 4B and 7B)(Thompson and Stent, 1976c; Calabrese, 1977). These switch INs inhibit both heart INs in M6 and M7. Only one of the switch INs produces impulse bursts during any given heartbeat cycle; the other switch IN is silent, although it receives rhythmic inhibition from the beat timing oscillator (Fig. 7B; Calabrese

11 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 7. Switches in coordination state in the central motor program for heartbeat. (A) Continuous extracellular records from the vascular nerves (VN) of three segmental ganglia of an isolated nerve cord. The records are indexed for segment and body side as indicated in Fig. 4. The bursts of impulses recorded on the vascular nerves result from activity in the axons of the heart HE MNs. Small arrowheads at the beginning and end of the record indicate the starts of bursts. The record begins with the right side coordinated peristaltically (note rear-to-front progression in the start of the heart MN bursts) and the left side coordinated synchronously. At the large arrowheads a switch in coordination state occurs so that at the end of the record the right side is coordinated synchronously and the left is coordinated peristaltically (after Calabrese and Peterson, 1983). (B) Simultaneous intracellular recordings from two switch heart INs of ganglion M5 show that only one is rhythmically active at a time; the other is inactive. The large arrowheads indicate a spontaneous reciprocal switch of their activity states (after Lu et al., 1999). (C) Circuit diagrams of the heartbeat pattern generator and the phase relations among the heart INs (HN cells) before and after the switch illustrated in B. Circuit diagrams are like that of Fig. 4B. Neurons that are stippled fire approximately in phase with one another and in antiphase with those that are not stippled. The system has two different coordination states, depending on which of the two switch heart INs is active and which is inactive (dashed line) (Calabrese, 1977; Gramoll et al., 1994; Lu et al., 1999). The coordination of MNs anterior to ganglion M7 is also controlled by the switch IN, which unilaterally drives an unidentified premotor IN in a nearly one-to-one fashion (Calabrese, 1977). The small phase differences (5 10%) between the HN(3) and HN(4) neurons and the between the HN(6) and HN(7) INs are not illustrated. and Peterson, 1983; Gramoll et al., 1994; Lu et al., 1999). With a period approximately times longer than the period (8 s) of the heartbeat cycle, the silent switch IN is activated and the previously active one is silenced. The activity of the switch INs determines which side is in the peristaltic versus the synchronous activity mode (Fig. 7B). The switch INs link the timing oscillator in M1 M4 to the M6 and M7 heart INs. Because only one switch IN is active at any given time, there is an inherent asymmetry in the coordination of the heart INs on the two sides: the ipsilateral M3, M4, M6, and M7 heart INs are

12 290 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) active roughly in phase on the side of the active switch IN, whereas the ipsilateral M3 and M4 INs are active out of phase with the M6 and M7 INs on the side of the silent switch IN (Fig. 7C). Hence, the heart MNs are coordinated synchronously on the side of the rhythmically active switch IN, whereas the MNs are coordinated peristaltically on the side of the silent switch IN. The observed switches in the coordination state of the heart MNs, therefore, reflect switches in the activity state of the switch INs (Fig. 7B; Thompson and Stent, 1976c; Calabrese, 1977). Is the switch in the activity states of the switch INs controlled by an independent switch timing network or is the switching mechanism inherent to these neurons themselves? There appears to be no synaptic connections between the switch INs, because injecting current to change the activity in one switch IN does not influence the activity state of the other, even though spontaneous switches in the activity state are always reciprocal (Lu et al., 1999). Voltage-clamp studies showed that in the silent state, switch neurons have a persistent outward current that is not voltage-sensitive and reverses around 60 mv (Gramoll et al., 1994). This current turns off in a switch to the active state. Thus, in its silent state, the switch IN is inhibited by a persistent leak current. The dynamic-clamp (Sharp et al., 1993) was used to simulate the turn-on and turnoff of such a leak, which was found to be sufficient to change the activity state of the manipulated switch IN (Gramoll et al., 1994; Lu et al., 1999). These results argue that switching is controlled by an independent timing network, extrinsic to the switch neurons, that alternately imposes a tonic inhibitory leak alternately on one of the two switch INs. This network remains unidentified Gaps in our current knowledge The heartbeat CPG can be conceptualized as two timing networks: a beat timing network comprising the first four pairs of heart INs (two oscillator pairs and two coordinating pairs) and a switch timing network that governs the activity of the switch INs. The two timing networks converge on the switch INs, and together with the heart INs in M6 and M7, make up the heartbeat CPG (CPG). The output of the CPG is configured into two coordination states of heart MNs by the alternating activity states of the two switch INs. Although much remains to be done to understand the dynamics of the activity pattern of the INs in the heartbeat CPG and how these dynamics translate into the HE MN output pattern, the problems presented by such a synthesis seem tractable. 3. Overt behaviors 3.1. Introduction Four of the leech behaviors local bending, whole-body shortening, crawling, and swimming can be elicited by tactile stimulation of the leech. The fifth feeding is elicited by chemical, tactile, and thermal stimuli. Which behavior is elicited by tactile stimulation depends upon the location and intensity of the touch. Such studies have used a calibrated touching device (Lewis and Kristan, 1998c), electrical stimulation of the skin (Kristan et al., 1982), and intracellular depolarization (Nicholls and Baylor, 1968) to activate mechanoreceptive T (touch), P (pressure), and N (nociceptive) cells. One generality from these studies is that activating T cells elicits the same behaviors as activating P cells, but P cells are more effective than T cells. That is, fewer P cells need to be activated at lower frequencies to produce the same behavioral responses as T cells. N cell activation also evokes swimming behavior, but can also cause qualitatively different responses, such as writhing and flailing, which have yet to be studied. At a threshold level of mechanosensory stimulation, the predominant response elicited depends upon the location of the stimulus: stimulating the anterior end produces shortening, stimulating the posterior end produces crawling or swimming, and stimulating midbody sites produces local bending (Kristan et al., 1982). Over some range, increasing the stimulus intensity merely increases the intensity of the response. At high stimulation frequencies (in the range of Hz), however, the responses change qualitatively. Strong stimuli to the front and back often produce sequential responses, with a violent version of the primary response followed by a vigorous secondary response. For instance, stimulating strongly the front end often produces a vigorous shortening followed by a rapid elongation that might lead to crawling or swimming (Kristan et al., 1982). Increasing the intensity of stimulation to a middle segment produces progressively stronger and more extensive local bending, in which more remote segments anterior and posterior to the one stimulated stiffen, so that the bend of the segment being stimulated becomes more exaggerated and widespread (Wittenberg and Kristan, 1992a). At even higher stimulation intensities, the behavior switches to a whole-body response, such as curling or twisting (Kristan et al., 1982). The following sections summarize what is known about each of the neuronal circuits underlying the five individual behaviors. Local bending and shortening are purely reflexive, episodic responses to a well-defined stimulus. Swimming, crawling, and feeding are rhythmic behaviors that, like the heartbeat system described above, are produced by CPGs that can also produce the underlying motor pattern in the isolated nervous system (Fig. 1B). This part includes a section on interactions among the behaviors, emphasizing how individual neurons are used in more than one behavior Local bending Motor neurons In response to a light touch to the skin of a segment in the middle of a leech (Fig. 8A), that segment produces shortening on the side touched and lengthening of the side away from the touch (Fig. 3A). A segment produces this behavior by contracting longitudinal muscles on the side of the touch and elongating those on the opposite side, after initially contracting both sides (Fig. 8B; Kristan, 1982). (The contribution of circular muscles is discussed below.) Mono-

13 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 8. Behavior and neuronal bases of local bending. (A) The semi-intact preparation used to characterize local bending. One lateral half of a leech s body wall, from dorsal midline to ventral midline, is removed and pinned out on one end. Two tension transducers are attached to the other end to measure tension generated by the dorsal and ventral longitudinal muscles. The dark dots along three of the annuli indicate the sites of the sensilla, located along the middle annulus in each segment. One ganglion is left attached to the piece of body wall by its nerves; it is pinned out to allow recording from individual MNs. A stimulating electrode is placed on the skin to excite the terminals of the mechanosensory neurons innervating the mid-dorsal region of the body wall in the middle segment. (B) Tension produced by dorsal and ventral longitudinal muscles in response to stimulating the dorsal skin. The stimulus activated sensory neurons for a short time, indicated by the bar (stim.) under the tension traces. Initially, both dorsal and ventral longitudinal muscles contracted, but the ventral muscle started to relax in less than 1 s, while the dorsal longitudinal muscle continued to contract for several more seconds. If the ventral skin had been stimulated the pattern would be reversed. (C) Recordings from excitatory and inhibitory MNs to longitudinal muscles during a local bend response. The same kind of electrical stimulus was given to the dorsal skin while recording from four different MNs. (The recordings were made successively; they are lined up relative to the stimulus to indicate their activity during a single response.) DE is an excitor MN to the dorsal longitudinal muscles; VE is an excitor of the ventral longitudinal muscles; DI is an inhibitor of the dorsal longitudinal muscles, and VI is an inhibitor of the ventral longitudinal muscles. Note that stimulating the dorsal skin activates DE and inhibits VE, as expected from the tension recordings. The inhibitors, DI and VI, show the opposite response. The motor neuronal responses are entirely consistent with the tension recordings except that VE shows only inhibition; it does not show the initial excitation apparent in the Ventral tension trace in part B. This initial excitation Fig. 9. Local bend circuitry. (A) Simplified schematic summary of connections. Pressure-sensitive mechanoreceptors innervating dorsal and ventral body wall (P D and P V cells, respectively), with overlapping receptive fields, sense pressure to the skin. They transmit this activity, via excitatory synapses, to a layer of INs that excites longitudinal MNs. The inhibitory MNs, in addition to inhibiting muscles, also inhibit the excitors of the same muscles. This central inhibition provides the only known inhibitory input to the MNs during local bending. (B) Schematic summary of the central connections. All four P cells connect to all 17 known INs, although the strengths of these connections produce cosine-shaped receptive fields for the INs. The connections from the cell immediately above (in the same vertical column) are strong, and the strength diminishes with lateral distance. For instance, cell 115 receives strong synaptic input from the ipsilateral P d cells but very weak connections from the contralateral P v cell. Note that inhibitory MNs receive inputs that are the same as for the excitatory MNs of the opposite sign. For instance, DI (in this figure, called imnd ) receives the same input as the DE MNs ( emnd ). This connectivity produces responses seen in Fig. 8C. In both diagrams, inhibitory connections are indicated by filled circles and excitatory connections by lines. All excitatory connections are feed-forward, from P cells to INs and from INs to MNs. synaptic connections from the T and P mechanosensory cells onto the L MNs (each of which activates all the longitudinal muscles in one side of the body wall) cause the initial cocontraction. Polysynaptic connections onto MNs with more restricted motor fields (e.g. dorsal excitor neuron cell 3 (DE-3) excites a band of dorsal longitudinal muscles and ventral of the dorsal and ventral longitudinal muscles, in fact, is produced largely by the activation of the L cells, MNs that cause strong contraction in all the longitudinal muscles on one side of a segment. The L cells are activated only during the stimulus, so that the initial response to the stimulus is, as previously surmised from neuronal connections (Nicholls and Baylor, 1968), a shortening response. Activity in the more localized MNs (i.e. DE and VE) persists far after the stimulus; this persistent activity is the cause of the local bend.

14 292 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 10. Summary of receptive fields of mechanosensitive P cells, INs, and MNs. The left column (panels A, C, and E) shows data used to determine the receptive fields obtained from recordings of the different neurons. The maximal response location was calculated for all the neurons by fitting a cosine function to their stimulus response magnitudes at several locations within their receptive fields. The data were plotted relative to the peak location (08). Receptive fields for the P cells were determined from preparations illustrated in Fig. 8A. Stimulating each of the four P cells and plotting the amplitude of the response, as a function of the locations of the middle of the P cell receptive fields, determined receptive fields for INs and MNs. In all cases, the data were normalized to the maximal response for each neuron. The panels in the right column (B, D, and F) are idealized summaries of all the receptive fields for all the neurons of each kind, which were used to simulate the function of the system. (A) Touch (T) and pressure (P) cell receptive fields. The curve is the best-fit cosine function to all data. (B) The best-fit cosine functions for each of the four P cells, each centered on the location of the maximal response. (C) Local bend IN receptive fields, with the best-fit cosine curve. Normalized data are shown for four

15 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) excitor neuron cell 4 (VE-4) excites a ventral longitudinal band) produce the more prolonged excitatory response on the side of stimulation (Fig. 8C). The same stimulation also activates the inhibitory MNs on the side away from the touch, thereby inhibiting both longitudinal muscles and the excitatory MNs to the longitudinal muscles during the contraction on the side of the touch (Lockery and Kristan, 1990a). This inhibition could be produced either by direct inhibitory connections from the local bending INs (LBIs), or by excitatory connections onto appropriate inhibitory MNs. Tests showed that when the inhibitory MNs synapsing onto DE-3 were hyperpolarized during ventral stimulation, the input onto DE-3 was excitatory (Lockery and Kristan, 1990b). This experiment suggests that LBIs make only excitatory connections onto MNs, and that the only inhibition in the pathway is the one made by the inhibitory MNs onto the excitatory MNs (and muscles; Fig. 9A). Because there are neither feedback connections (e.g. from INs to sensory cells, or MNs back onto INs) nor any functionally important lateral connections at the sensory or interneuronal level, the first two layers of the local bending system form an excitatory, feed-forward circuit (Fig. 9B). The third layer provides the only lateral connections, namely the inhibitory connections made by the inhibitory MNs onto the antagonistic excitors. These inhibitory connections provide the reciprocity of the response; inhibitory MNs to a given longitudinal muscle (e.g. the left dorsal) receive the sensory input that is identical to that for the excitatory MNs on the opposite side (i.e. the right ventral) and relax the muscles on the side contralateral to the touch Mechanosensory neurons that produce local bending Two lines of evidence indicate that the P cells are the most important mechanosensory neurons for producing the local bend response. First, monitoring responses of T and P cells to tactile stimuli of different intensities showed that the amplitude of the local bend tracked the responses of P cells but not T or N cells (Lewis and Kristan, 1998c). Second, stimulating a single P cell produces a response that is essentially the same as stimulating the skin in the middle of that P cell s receptive field (Kristan, 1982; Lewis and Kristan, 1998a). Hence, to determine the neuronal bases of local bending, the activity of the P cells is the most important. The receptive field of each P cell is the top of a cosine function, cut off at 908 (Fig. 10A), taking the body circumference as The scatter of the points around this curve shows that there is considerable variability in the responses at different locations even when the site and magnitude of the stimulus is kept the same (Lewis and Kristan, 1998c; Lewis, 1999). Adjacent P cells form overlapping receptive fields that span about half the body circumference, with peak responsiveness in the middle of the dorsal and ventral quadrants on each side (Fig. 10B) Local bend interneurons INs involved in local bending, the LBIs, were located by recording intracellularly from many of the 400 neurons in individual segmental ganglia, searching for neurons that (1) received strong input from a P cell with a dorsal receptive field (P D ), and (2) activated the dorsal MN, DE-3 (Lockery and Kristan, 1990b). Seventeen such INs were found, six of which were bilaterally paired and one of which was unpaired. By stimulating each of the P cells individually and in pairs (Lockery and Kristan, 1990b), the receptive fields of each IN were inferred (Lewis, 1999). The receptive fields of each LBI could be nicely fit by a cosine function, and, because each LBI receives input from all the P cells, their receptive fields span the whole circumference of the body (Fig. 10C), that is, twice the width of the P-cell receptive fields. The center of the receptive field for each identified LBI is characteristic for that IN, and the locations of the centers are distributed fairly evenly around the dorsal and lateral body wall (Fig. 10D). In the search for LBIs, none were found to have ventral receptive fields (Lockery and Kristan, 1990b). This is likely the result of the search strategy, which was directed specifically to find INs with dorsal inputs and outputs. Because LBIs with ventral fields would be only weakly activated by P D inputs and would not activate DE MNs, they could easily have been missed in the original search. If the search was thorough, another three or four pairs of ventral LBIs might yet be identified. The connections from LBIs to MNs were inferred from the responses of MNs to stimulating P cells, individually and in adjacent pairs. Because each MN receives input from every P cell, their receptive fields like those of the LBIs span the entire circumference of the body wall (Fig. 10E). Also like the LBIs, the receptive fields of the MNs are well characterized by a cosine function. Unlike the LBIs, however, the receptive fields have an inhibitory component from the P cells whose receptive fields are on the side opposite to fields activated by each MN. This inhibition ensures that the side opposite to the location of a touch relaxes, allowing the bend to be more effective in moving the body away from an object touching it. As discussed above, the direct LBI input onto the MNs appears to be exclusively excitatory, but this excitation is overridden by indirect inhibition via the inhibitory MNs (Fig. 9B). The receptive fields of the MNs, like those of the P cells and INs, are distributed uniformly over the body wall. In fact, the tactile receptive fields of the MNs are very similar to their motor units. For instance, excitatory dorsal longitudinal MNs have receptive fields centered on the dorsal surface and excitatory ventral MNs have receptive fields centered on the ventral surface. It is this coherence of sensory and motor fields, in fact, that provides the localization of the local bend. The relaxation of the side opposite to the touch results from the disjunction in the sensory and motor fields of the inhibitory MNs. For example, the LBIs (cells 115, 125, 212, and 218) in response to stimulating each of the four P cells. (D) The idealized receptive fields for all the known and hypothesized INs. (E) Motor neuron receptive fields. Normalized synaptic responses from the four P cells for both excitors (cell 3 is a DE, cell 4 is a VE) and inhibitors (cell 1 is a DI, cell 2 is a VI) are shown, with the cosine function that best fits the data for all the motor neurons. (F) Idealized receptive fields for the longitudinal muscle MNs, with the peaks lined up by the locations of their maximal responses. (G) The approximated motor fields of the longitudinal MNs used in modeling the function of the local bending circuit. All connections are excitatory to the three or four sections of longitudinal muscles (from Lewis and Kristan, 1998b). These are approximations of the innervation fields of the MNs (Stuart, 1970).

16 294 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 11. Vector model matches local bending behavior. (A1) The direction of 16 local bending responses to identical stimuli delivered to the mid-dorsal skin, 458 from the dorsal midline (arrow). The dashed line indicates the average response to the 16 stimuli. The angular difference between the arrow and the dashed line is the error of the response. (A2) The locations of 12 responses to repeated bursts of intracellular stimulation delivered to the right ventral P cell that were similar to the train of impulses seen when the middle of the receptive field of this neuron was touched. These stimulus trains produced an average response (dashed line) very close to the middle of the receptive field of this neuron, which is the expected response to activation of a single P cell. (From Fig. 10B, the only location at which a touch would

17 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) sensory receptive fields of the dorsal inhibitors are centered on the ventral surface of the opposite side, and the ventral inhibitors are most strongly activated by touching the dorsal skin on the opposite side The local bend response as a directed behavior The characteristics of the local bend circuit (broadly tuned neurons with overlapping receptive fields) provide an ideal way for a neuronal population to perform a vector estimation of the location of a stimulus (Salinas and Abbott, 1995) or for calculating the direction of a movement controlled by those INs (Georgopoulos et al., 1988). The schematic summary diagrams in Fig. 10B, D, F, and G emphasize the fact that touching a particular location produces shortening centered at that location. Behavioral tests showed that the response was centered to within 8% of the circumference of the stimulated segment (Lewis and Kristan, 1998b), despite the fact that the responses of only four sensory neurons are used to make this localization. This precision is possible by using the relative firing rates of overlapping sensors that are evenly distributed over the circumference. This population code is maintained through the LBI layer to the MNs. A simple model of this network, using the amount of variability seen in the responses at the sensory level, showed that this network was sufficient to explain the precision shown by the animal s localized bending response to local stimulation (Lewis and Kristan, 1998a). In addition, the model matched the accuracy of the response to stimulation at two locations (Fig. 11). This experiment confirmed that individual P cells contribute strongly to the direction of the response as well as showing that a vector population code is important in determining response direction. Further analyses made three additional points: (1) Very few P cell spikes less than five typically were required to determine the location of the response (Lewis and Kristan, 1998c). (2) The response direction was determined tens of milliseconds before the response began. This shows that sensory feedback was not required for determining response location (Lewis and Kristan, 1998c). (3) The number of INs required to determine the response direction depends critically upon the noise in the system. The number of INs used about 24 nicely compensates for the level of noise found in the system (Lewis and Kristan, 1998a). More recent studies have used an optic flow algorithm developed for video surveillance to plot local bending movements very precisely (Zoccolan et al., 2001). A vector field analysis of optic flow data, showed that circular muscles contribulte significantly to the local bend (Zoccolan and Torre, 2002). Interestingly, a linear combination of the contributions of circular and longitudinal MNs matched the observed responses to mechanosensory stimulation very well. In addition, applying this much finer-grained analysis to stimulating individual T, P, and N cells confirmed that the major contribution to local bending is from the P cells. On a more global scale, this analysis showed that, despite a large variability in the individual MN responses, the contraction phase of local bending was quite reproducible, because the variability between MNs was independent (Zoccolan et al., 2002). The relaxation phase of the response, however, was much more variable, probably due to variabilty in the duration of the responses of the INs and in the biomechanics of the muscles (Garcia-Perez et al., 2004). By using principle component analysis on optic flow data, the local bend response was shown to discriminate the location of two tactile stimuli as well as humans can do with their finger tips (Baca et al., 2005). As suggested previously (Lewis and Kristan, 1998c), this analysis also showed that the location of the stimulus is coded within the first 200 ms of the stimulus (before the movement actually starts), so that more prolonged stimuli did not produce better localization (Baca et al., 2005). Longer stimuli did, however, produce larger responses, suggesting that response location and response magnitude are coded somewhat differently. Because its neuronal circuitry is so well defined, local bending is an ideal behavior for testing ideas about sensory coding. Neural net models of local bending behavior have been used to investigate both the feasibility of using a distributed network to perform local bending (Lockery et al., 1989; Kristan, 2000) and the influence of synaptic plasticity on local bending (Lockery and Sejnowski, 1992). A very interesting, although somewhat troubling, conclusion from these neural net models is that synaptic changes large enough to produce significant behavioral changes could be undetectable electrophysiologically, if they were distributed over many neurons (Lockery and Sejnowski, 1993). A more optimistic outcome of these models is that population coding schemes make it possible for a small number of neurons to produce several different behaviors, provided that they are activated by different sensory neurons or INs (Lockery and Sejnowski, 1992; Kristan, 2000). A more physiologically realistic model (Baca and Kristan, 2001) showed that the inhibition provided by the inhibitory MNs could both produce lateral inhibition and smooth out the responses in the coarse representation of location by the P cells Gaps in our current knowledge The local bend response arises from a relatively simple, mostly feed-forward system that pulls the body away from the activate only one P cell is in the middle of its receptive field, i.e. at 458.) The responses had less variability than did stimulation of the body wall (e.g. the left panel) because the variability of the P-cell response was eliminated by the electrical stimulation. (B1) Data obtained when the stimuli shown in A1 and A2 were delivered simultaneously, showing the locations of the responses to 16 repetitions of this stimulus pairing. The average response (dashed line) is nearly half-way between the average of the two individual responses. (B2) Directions of the responses predicted from the individual responses of the P cells. The tighter clustering of the responses indicates that much of the variability in the responses to touch was due to the variability of the P cell responses. (C1 and C2) Responses of the model from Fig. 10 to the same P cell activations shown in B1. These responses show the same general features as the real data, suggesting that the neuronal network, as characterized, is essentially complete (from Lewis and Kristan, 1998a).

18 296 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) site of touch. The orderly overlap in the receptive fields of the neurons at each level provides a simple network to calculate a population vector. Such a system has been proposed for a variety of other behaviors: eye movements in mammals (Sparks et al., 1997), arm movement in primates (Georgopoulos et al., 1988), escape responses in crickets (Theunissen et al., 1996) and cockroaches (Camhi and Levy, 1989), and flight orientation in insects (Douglass and Strausfeld, 2000). In all these systems, a common theme is the mapping of location from a sensory space onto motor space to produce an accurate response with a minimal number of neurons. The most obvious gaps in our knowledge of the local bending system are the missing LBIs (i.e. the ones with ventral receptive fields, and determining how the LBIs connect to circular muscle motor neurons). But even without this knowledge, the neuronal circuitry for local bending is so well characterized, that it provides a very useful system for testing ideas about coding. Previous studies have suggested that the location of local bending is encoded in the relative number of impulses in adjacent P cells. This can be tested by recording intracellularly from two P cells with adjacent receptive fields and imposing variations in their normal firing patterns by stimulating them in variations of their normal patterns. In other words, the convincing way to determine the validity of a code is to see whether the system can in fact decode the hypothesized code. In addition, it would be useful to know the function(s) of the inhibitory connections among the MNs. Are they simply for lateral inhibition, or do they contribute significantly to the calculation of the population vector? How these calculations are performed, as well as the basis for the independence of variations in MN responses (Zoccolan et al., 2002), can be traced out in the activity of the LBIs Shortening Shortening in the leech is caused by a co-contraction of all longitudinal muscles in body segments. Contractions can occur in all segments (whole-body shortening) or only a few segments (local shortening) Whole-body shortening Moderate activation of mechanosensory neurons particularly P cells in the anterior end of the leech reliably produces whole-body shortening (Fig. 3C). Such stimulation activates two parallel interneuronal pathways: a fast, weak one and a slower, more prolonged one (Fig. 12A). The S cells are the central elements in the fast pathway. There is a single S cell in each ganglion (Frank et al., 1975) that sends an axon both rostrally and caudally into the medial connective (Faivre s nerve). The axons of the S cells are among the largest in the leech CNS, and have the fastest conduction velocity. The axons from S cells in adjacent ganglia meet midway between the ganglia and make highly effective electrical junctions that allow action potentials to pass without fail in either direction. These interconnected S cells form a reliable fast-conducting system (FCS, Bagnoli et al., 1975) that carries action potentials from the site of spike initiation (which can be in the S cell in any ganglion) to every ganglion in the nerve cord (Frank et al., 1975). The S cells respond to mechanosensory and photic inputs (Frank et al., 1975; Bagnoli et al., 1975). In each segment, S cells make electrical connections with L cells, the MNs that, as stated earlier, cause all longitudinal muscles in one hemisegment to contract. The FCS is strongly activated during whole-body shortening (Magni and Pellegrino, 1978; Mistick, 1978). In the Amazonian leech, Haementeria ghilianii, all the connections are sufficiently effective so that activating the S cell at moderate rates produces a significant shortening response (Kramer, 1981). In Hirudo, however, the S-to-L connection is so weak that stimulating the S cell even at rates higher than those observed during shortening behavior, produces only a very weak motor response (Shaw and Kristan, 1999). The strongest, most behaviorally relevant pathway is from mostly unidentified INs, which have much slower conduction velocities than the FCS, but which produce a strong and prolonged activation of the MNs with more limited motor fields than the L cell. It appears that the FCS provides a fast but subthreshold activation of the longitudinal muscles, upon which the slower system produces full-blown shortening (Fig. 12B and C). These interneuronal pathways activate all the excitatory MNs to the longitudinal muscles in all segments of the body with short latencies. The S cell excitation spreads at 5 6 ms per segment, and the other pathways are significantly slower, at ms per segment (Shaw and Kristan, 1999). In addition, the inhibitory MNs are strongly inhibited during whole-body shortening (Shaw and Kristan, 1995). There is significant variability in the response of individual MNs during wholebody shortening, but the ensemble average of the MN response is much less variable, because the responses of each MN is statistically independent from all the others (Pinato et al., 2000; Arisi et al., 2001) Local shortening Mechanical stimulation of the skin in mid-body segments elicits a local shortening response (Fig. 13A; Wittenberg and Kristan, 1992a). As is true for whole-body shortening, P cells are most effective in producing local shortening; in both behaviors all the longitudinal muscle excitors are excited and all the inhibitors are inhibited. What distinguishes the two types of shortening is that local shortening is restricted to the segments adjacent to the stimulated segment rather than involving the whole body. The number of segments involved in local shortening increases with increasing stimulus intensity, until, at the extreme, the whole body can be involved. Even at this extreme, however, local shortening differs from wholebody shortening in that the segment being stimulated produces a bend rather than a shortening (i.e. the longitudinal muscles on the side of the segment being stimulated contract and those on the other side relax). The consequence of this radiating shortening on either side of the site is that the degree of bending about the site of stimulation increases with increasing stimulus intensity. Interestingly, a subset of the very same INs responsible for local bending send processes out of their own ganglion into several adjacent ones, where they make

19 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 12. Neuronal bases of whole-body shortening. (A) Schematic summary diagram of what is known about the neuronal circuit underlying whole-body shortening. Touch (T) and pressure (P) neurons in the anterior end (from the brain down to about segmental ganglion 7) activate both the fast, but weak S cell network,andaslower, stronger network (other pathways); both drive the excitatory MNs (DE, VE, and L) to longitudinal muscles and inhibit the inhibitors (DI, VI) to these same muscles in all segmental ganglia. (B) Synaptic input onto excitatory MNs during whole-body shortening in a semi-intact preparation (diagram on the left). Activating mechanosensory neurons in segments 3 and 4 (stimulus) excited both the L cell in segment 11 for the duration of the stimulus train and the dorsal excitor cell DE-3 for a much longer time. Extracellular recordings in the sameganglion showed the spikes from the L cell (marked by dots over the DP:B1 recording branch 1 of the dorsal posterior nerve) and cell 3 (the large spikes in the DP:B2 recording). The tension recordings show that the response is somewhat larger and faster in the anterior end than in the posterior end. (C) The whole-body nature of the shortening response. Stimulating the skin in segment 4 activates the P cell in that segment, as shown in the P d intracellular recording from that segment (top trace). The extracellular recordings from nerves DP:B1 and DP:B2 in segments 7 and 12 (bottom four recordings) show that the L cell and cell 3 in these segments were also activated during the shortening response. The stimulus marker provides a time calibration, which is 500 ms long. connections to MNs that produce shortening rather than bending (Fig. 13B; Wittenberg and Kristan, 1992b). It will be interesting to find out whether the two kinds of shortening share neuronal circuitry in the individual segmental ganglia Gaps in our knowledge For both whole-body and local shortening, there are more gaps than knowledge. Whole-body shortening is a very overpowering behavior; it appears to override all behaviors but feeding (Shaw and Kristan, 1997), and it activates the L cells, which cause the fastest and most powerful contraction of any longitudinal MNs (Stuart, 1970; Mason and Kristan, 1982). Some of the INs that trigger swimming are also active during shortening (Shaw and Kristan, 1997), so it will be interesting to determine how these very different behaviors share crucial interneurons. In addition, the function of the two parallel

20 298 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) underlying rhythmic neuronal activity patterns. Nearly concurrently, Brown (1911) proposed that central neuronal oscillators generate these neuronal substrates via reciprocal inhibition between neurons within the spinal cord. Ironically, both researchers studied the same behavior stepping in mammals. Despite the demonstration by Adrian that there is an inherent rhythmicity in the CNS of the beetle Dytiscus (Adrian, 1931), Gray and coworker s seminal work on swimming in leeches (Gray et al., 1938), and even the demonstration that crustacean swimmeret movements are generated by neuronal oscillators (Ikeda and Wiersma, 1964), the chainof-reflexes view prevailed for more than 50 years, leading to Wilson s critical research on flight in deafferented locusts (Wilson, 1961). Finally, research on the cardiac ganglion and stomatogastric systems in lobster (Hartline, 1967; Mulloney and Selverston, 1974), leech swimming (Kristan and Calabrese, 1976), and lamprey swimming (Cohen and Wallén, 1980), as well as numerous additional preparations (Selverston, 1985; Marder and Calabrese, 1996), clinched the argument unequivocally in favor of the central oscillator theory (Delcomyn, 1980); or so it seemed (Pearson, 2000). Fig. 13. Neuronal bases of local shortening. (A) A single P cell located in the middle of the animal (P D, segment 10) was stimulated intracellularly (bottom trace). The response was measured in DP nerve recordings from segments throughout the nerve cord. This stimulus elicited the largest response in the same segment stimulated, with a smaller response in adjacent segments, both anterior (9,L) and posterior (11,L). The excitation did not spread to either the most anterior segment recorded (4,L) or the most posterior one (18,L). (B) The response that spreads to other ganglia activates both dorsal and ventral excitatory MNs. Stimulating a P D neuron in ganglion 8 (bottom trace) activated cell 3, a dorsal excitor; cell 4, a ventral excitor; as well as the L cell (which contracts both dorsal and ventral longitudinal muscles) in ganglion 10. pathways (Fig. 12A) is provocative. It may be that the fast pathway is to ready the animal to behave and the slower pathway actually produces the response. As discussed in Section below, the S cell is very important for plasticity of the shortening response. Perhaps the INs that are active in shortening and other behaviors have a special role in plasticity Swimming History: reflex chain versus central pattern generator Early studies on the neuronal bases of animal locomotion spawned two opposing theories. The first, effectively promulgated by Philippson (Philippson, 1905, cited in Gray, 1950) and Sherrington (1906) at the beginning of the 20th century, was that coordinated chains of sensory reflexes generate the Swimming behavior and motor control This review of leech swimming begins with a brief overview of the circuits and mechanisms by which muscles, MNs, sensory neurons and INs control leech swimming movements. The older results have been reviewed many times (Stent et al., 1978; Kristan, 1974, 1980, 1983; Kristan and Weeks, 1983; Friesen, 1989d; Brodfuehrer et al., 1995b). Thus weight is given to recent experiments on the role of sensory feedback in setting intersegmental phase lags and cycle period, and an examination of functional aspects of the central oscillator and intersegmental coordination. The quasi-sinusoidal undulations that characterize swimming leeches (Fig. 14A) are a consequence of tension and relaxation cycles in two types of segmental muscles. First, the leech body, is flattened to form an elongated ribbon by tonic contractions of dorsoventral muscles. Second, the alternating contraction and relaxation of dorsal and ventral longitudinal muscles (DLM and VLM, respectively) act against internal pressures, with a period of about s, to generate rhythmic bending in body segments (Fig. 14B; Uexküll, 1905; Gray et al., 1938; Kristan et al., 1974a; Wilson et al., 1996b). Two major technical advances were critical for research into the neurobiological substrates of leech swimming movements: one was the advent of extracellular recordings, the other the development of a semi-intact preparation in which neuronal activity and body wall movements are available simultaneously for detailed analyses (Gray et al., 1938). These techniques, together with intracellular recording, revealed that the antiphasic contraction and relaxation of the DLM and VLM are commanded, respectively, by excitatory (six pairs/segment) and inhibitory (five pairs/segment) motoneurons (MNs; Stuart, 1970; Ort et al., 1974; Norris and Calabrese, 1987). Intersegmental phase lags of approximately 208/segment in MN activity ensure the generation of the rearward-traveling body wave (Kristan et al., 1974a,b). These MNs are

21 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 14. Expression of leech swimming movements. (A) Swimming leeches generate a quasi-sinusoidal wave of approximately one full wavelength. These swim profiles are essentially identical in three different leeches of very different length and weight. (B) Swimming movements result from antiphasic contractions in dorsal and ventral longitudinal muscles. The inset depicts the nerve cord body wall preparation used to obtain the extracellular records [DP(R,7) and DP(R,14)] and the tension measurements (dorsal and ventral tension, obtained from the proximal ventral and the distal dorsal body wall strips). A single swim episode was elicited by nerve stimulation (artifacts in the DP nerve traces). The inset at the bottom shows the four traces at higher temporal resolution to illustrate the intersegmental phase lags of MN activity and the antiphasic tension rhythms in the muscles. interconnected by inhibitory chemical synapses from the dorsal inhibitor (DI) to dorsal excitatory (DE) MNs, and from ventral inhibitor (VI) to ventral excitor (VE) MNs (Ort et al., 1974; Granzow and Kristan, 1986). The DIs also inhibit the VIs, an interaction that, unlike most other MNs, crosses the ganglion midline (Friesen, 1989a). Once thought to be an exception to the rule that rhythmic movements in animals are generated by neuronal oscillators located within the CNS (Kristan and Stent, 1975), further research revealed that isolated nerve cord preparations (comprising eight or more of the 21 midbody ganglia) are capable of generating rhythmic bursting in MNs that is an excellent facsimile of the overtly expressed rhythm (Kristan and Calabrese, 1976). This fictive swimming has a longer cycle period (0.5 2 s) and reduced intersegmental phase lags (about 108/segment) from that seen in intact animals (Pearce and Friesen, 1984). Experiments on semi-intact preparations also revealed that, although sensory feedback is not necessary for generating the basic swim rhythm, feedback loops, perhaps acting via the DI, are indeed present (Kristan and Calabrese,

22 300 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) ). These seminal results laid a solid foundation for studies of the central oscillator that generates the swimming rhythm, including studies on the central and sensory mechanisms that control initiation and termination of swim episodes, the mechanisms for chemical modulation of swim expression, and most recently, the role of sensory feedback in intersegmental coordination Central oscillator circuits The swimming rhythm is not generated by a MN circuit. Although MNs are phasically active and interact with each other, this network is not sufficiently complex, nor do MNs have intrinsic oscillatory properties, to generate the swim oscillations. Subsequent searches among the considerably smaller INs identified thirteen candidate swim oscillator INs in most midbody ganglia (at least from M2 to M16) by the criteria that: (a) their membrane potential is phase-locked to the swimming rhythms, (b) current injection into the IN somata either depolarization or hyperpolarization shifts the phase of swimming activity, and (c) there are synaptic interactions with other candidate oscillator INs (Friesen et al., 1976, 1978; Weeks, 1982b; Friesen, 1985, 1989b). A set of INs that satisfies all three criteria is found on both the dorsal and ventral aspects of the midbody ganglia (Fig. 15). With somata ranging from about mm in diameter, these INs are inhibitory and bilaterally paired (cells 27, 28, 33, 60, 115, and 123), except for an unpaired medium-sized excitatory IN (cell 208). Without exception, their axons project either anteriorly or posteriorly in lateral nerve cord connectives (Poon et al., 1978; Weeks, 1982b; Friesen and Hocker, 2001). However, definitive information about maximal projections for individual oscillator INs remains elusive. The current understanding is that INs project about six segments, but not more than seven segments (Pearce and Friesen, 1985b; Friesen and Hocker, 2001), except for cell 208, which may project as far as 10 segments (Weeks, 1982b). An important characteristic of swim-related neurons is the phase of their activity (Fig. 15B). The phase reference mark, 08, for each segment is the median impulse in DE-3 MN bursts recorded with extracellular electrodes (Kristan et al., 1974a). The activity phases of other MNs are either 08 (DE and VI) or 1808 (VE and DI), except for DI-1, which has a phase of 1208 (Ort et al., 1974; Friesen, 1989d). Phases of the INs are more dispersed, spanning 08 to nearly For simplicity and as an aid to modeling, IN phases may be placed into three phase groups: about 08 (40 508), 1208 ( ), and 2408 ( ) (Friesen, 1989d). Intersegmental phase lags in the isolated nerve cord preparations are for extended preparations (Kristan and Calabrese, 1976), but increase to about 408 if preparations are reduced to two segments (Pearce and Friesen, 1985b). Nearly all pairs of bilaterally homologous neurons in the leech swim circuit are electrically coupled. More importantly, the swim-related oscillator INs are interconnected via inhibitory synapses (Fig. 15A). Only one set of these IN interactions (between cells 27 and 28) is strictly reciprocal; other interactions appear reciprocal if laterality of INs is ignored (Fig. 15B). Reciprocal interactions, both direct and via electrical coupling, also link the DI and VI MNs to the INs. Because of these interactions and because their depolarization can shift the phase of swimming activity, these inhibitory MNs are candidate members of the swim oscillator circuit (Kristan and Calabrese, 1976; Friesen, 1989b; Mangan et al., 1994b). The unpaired cell 208 makes only excitatory connections (Weeks, 1982b; Nusbaum et al., 1987). Tests to determine whether intrasegmental interactions in the swim circuits are monosynaptic have proven difficult, in large part because many of these interactions are not spike-mediated. Consequently, individual synaptic potentials arising from synaptic connections within ganglia are rarely observed and action potentials are not required for synaptic interactions (Granzow et al., 1985; Friesen, 1985). Intersegmental interactions, however, occur via spike-mediated synapses. Those connections made by rostrally projecting INs are repeats their intrasegmental connections, whereas synaptic outputs by caudally projecting neurons are more diverse (Fig. 15C). Not shown in Fig. 15 are the very extensive intra- and intersegmental connections by which the INs and inhibitory MNs control the excitatory MNs (Poon et al., 1978; Weeks, 1982b). For completeness, it is essential to point out that inhibitory inputs to cells 60 and 33 are unknown and to mention that two additional neurons, cell 18 (Nusbaum, 1986) and 42 (Poon, 1976), are candidate, but poorly characterized, oscillator neurons. (Discussion of the mechanisms that generate swim oscillations is found below, in Section 3.4.7) Control of swimming activity Leech swimming activity is largely an episodic, rather than continuous, behavior, whether evoked in the intact animal, in semi-intact preparations, or in preparations of the isolated leech cord. In intact animals, swimming may be initiated by a variety of sensory inputs including tactile stimulation of the body wall and water movements. In the isolated nerve cord, bouts of fictive swimming are readily obtained in response to stimulation of a peripheral nerve, intracellular stimulation of single neurons, or even without stimulation, e.g. as spontaneous episodic events following application of serotonin (5- HT) or other neuromodulators. The neuronal network consists of at least three layers in addition to the two (oscillator INs and MNs) that have already been considered (Fig. 16). This section discusses the roles of the neurons in each of these hierarchical layers. Water vibrations, such as those caused by surface waves or due to water currents, also reliably elicit swimming in hungry, quiescent leeches (Young et al., 1981). In addition, these surface waves provide directional cues causing aroused leeches to swim towards the source of such waves. The anatomical structures responsible for these responses are sensillar movement receptors (SMRs), sensory hairs that cluster at the seven pairs of sensilla located on each midbody segment (DeRosa and Friesen, 1981; Phillips and Friesen, 1982). In scanning electron microscopy (SEM), SMRs appear as 1 mm wide, 10 mm long, single hairs; in transmission EM, SMRs have the distinct microtubule structure of sensory hair cells. Physiologically, responses recorded from individual sensillar nerves are

23 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 15. Intra- and intersegmental interactions between swim-related oscillator INs and MNs. DI and VI are inhibitory MNs; 123, 115, 60, 33, 28, and 27 are inhibitory INs; and 208 is an excitatory IN. (A) Subset of the neurons showing bilateral and ipsilateral interactions. Numerous reciprocal inhibitory interactions occur between INs and MNs across the midline of individual ganglia. (B) The segmental swim oscillator circuit with laterality of neuronal interactions collapsed. (C) Intersegmental interactions between the INs (gray lines denote intrasegmental connections). In B and C neurons are arranged in columns reflecting three phase groupings (top of B). Filled circles, inhibition; T-endings, excitation; resistor, nonrectifying electrical interaction; diode, rectifying electrical interaction. Both the synaptic targets and the sources of synaptic inputs for some neurons remain unidentified. (Modified from Friesen and Hocker, 2001, Fig. 1). selective to near field stimulation and appear in extracellular recordings from sensory nerves as graded compound action potentials that cover a wide frequency range [about Hz (Friesen, 1981; Brodfuehrer and Friesen, 1984)]. Target cells for water vibration stimulation include the CBW cells found in the anterior medial packet on the ventral side of many midbody ganglia (Gascoigne and McVean, 1991). Sensory stimulation initiates swimming activity through a cascade of interactions that eventually drive the swim oscillator (Fig. 16). One pathway in this cascade comprises the P and N sensory neurons, which drive trigger neurons (Tr1 and Tr2) via monosynaptic connections (Brodfuehrer and Friesen, 1986c,e). The somata of trigger neurons are located in the subesophageal ganglion; their axons project from that origin into the caudal nerve cord, with broadly distributed input and output sites in the intervening ganglia (Brodfuehrer and Friesen, 1986a,c). Brief stimulation of individual trigger neurons elicits bouts of swimming activity, with no correlation between the duration of trigger neuron activity and the ensuing swim episode (Brodfuehrer and Friesen, 1986a). Trigger neuron Tr2 is particularly interesting in that it acts as a toggle switch: brief stimulation can elicit swimming activity and a second stimulus, once swimming has commenced, brings that activity to an abrupt halt (O Gara and Friesen, 1995). Multiple, as yet unknown factors, determine whether swimming will occur in response to any stimulus (Cellucci et al., 2000). Trigger

24 302 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 16. Cascade of information flow from mechanosensory neurons to the swim-related muscles. Cell names: T, touch cell; P, pressure cell; N, nociceptive cells; SMR, sensillar movement receptor; Tr1 and Tr2, trigger neurons 1 and 2; SE1, swim excitor neuron 1; SIN1, swim inhibitor neuron 1; VE and VI, ventral excitors and inhibitors; DE and DI, dorsal excitors and inhibitors. FL, flattener neuron. The small inset numbers designate the reference phase of each oscillatory neuron. Darkly filled circles designate inhibitory neurons or those that inhibit swimming. The synaptic targets of some cells are unidentified. Synaptic symbols as in Fig. 15. neurons, which receive no feedback from the swim oscillator neurons, may be regarded as the highest centers for the control of swimming activity (Friesen, 1989c,d). Segmental targets of Tr2 have been found (Taylor et al., 2003); these neurons slow or stop ongoing swim motor patterns. Also located in the subesophageal ganglion, a pair of swim inhibitory INs (SIN) may be part of the swim-inactivating system (Brodfuehrer and Burns, 1995), whereas another set of neurons, the excitatory SE1 cells, may act as gain control elements that determine whether swimming will occur in response to some specific stimulus (Fig. 16; Brodfuehrer et al., 1995a). The subesophageal ganglion may also contribute directly to swim oscillations via cell SRN1, a brain IN that exhibits oscillations phase-locked to the swimming rhythm and which can shift the swimming phase (Brodfuehrer and Friesen, 1986d). Gating neurons, such as cell 204 and its homolog, cell 205 (Weeks, 1982a,c) occupy the third level of the swim-initiation cascade. The somata of these unpaired excitatory INs are restricted to the posterior half of the nerve cord (M9 M16). Their axons project to most, if not all ganglia of the nerve cord. Strong depolarization of even an individual swim gating neuron drives the expression of swimming activity even in nearly isolated ganglia (Weeks, 1981); when repeatedly activated, swim duration does not outlast the depolarization. When swimming activity is elicited by any means, including brief trigger neuron activity, these cells depolarize and remain depolarized throughout the swim episode (Weeks and Kristan, 1978). Part of this excitation results from monosynaptic excitatory input from trigger neurons (Brodfuehrer and Friesen, 1986b), but the source of the persistent depolarization remains unidentified. Body wall stimulation, followed by Tr1 activation, elicits concurrent depolarization of all cell 204 gating neurons. These, in turn, provide nearly simultaneous excitatory drive to a subset of the oscillator INs throughout the nerve cord. (Tr2 interactions with gating cells are polysynaptic and inhibitory.) Cells 204/205, in turn, drive both INs and MNs (Weeks, 1982a,c; Nusbaum et al., 1987). Interestingly, only three identified members of the central swim oscillator receive direct input from cells 204/205: cells 115, 28, and 208. At present, the only identified target for Tr2 is cell 256, a neuron that terminates swimming activity (Taylor et al., 2003). The neurotransmitter acting at the top of the excitatory cascade is glutamate, acting through non-nmda receptors at synapses between P cells and Tr1, between Tr1 and cell 204, and between cell 204 and cells 28, 115, and 208 (Brodfuehrer and Cohen, 1990, 1992; Thorogood and Brodfuehrer, 1995; Brodfuehrer and Thorogood, 2001). The great importance of gating neurons 204/5 in controlling swim period may be deduced from the fact that impulse frequency in these neurons, whether set by the experimenter or observed during swim episodes, predicts swim period with high precision (Pearce and Friesen, 1985a; Debski and Friesen, 1986). Flattening of the leech prior to swimming is mediated via activation of flattener MNs by cells 204, 205, and 208 (Weeks, 1982a,b,c). A set of serotonin-containing neurons, cells 21/61, also gate swimming (Nusbaum, 1986; Nusbaum and Kristan, 1986). These neurons receive input from T, P and N cells indirectly (Gilchrist and Mesce, 1997) and make excitatory interactions with the same oscillator INs as cells 204/5. Despite these similarities to cells 204/5, these more locally acting neurons are less robust in their swim initiation abilities, at least in Hirudo (Nusbaum et al., 1987). Control of leech swimming is obviously more complex than suggested by the linear cascade outlined in Fig. 16. For example, swimming activity evoked in ventral nerve cords that include the head ganglia is weaker and less regular than in brainless preparations, particularly in bursting recorded in the anterior half of the nerve cord (Brodfuehrer and Friesen, 1986d). Thus, the head ganglia have a marked inhibitory effect on swimming. In contrast, the tail ganglion facilitates swim initiation and duration, by reversing the inhibitory action of the head ganglia and prolonging swim episodes (Brodfuehrer et al., 1993). These differing effects of the head and tail brains initiate and reverse within seconds when impulse traffic to the brains is interrupted and reinstated, hence synaptic rather than hormonal mechanisms appear to be at work here, although those that mediate the excitatory actions of the tail ganglion are unknown Neuromodulatory control: serotonin and other biogenic amines Although neurons in the leech subesophageal ganglion exert the highest level of control over swim initiation and

25 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) termination, the overall propensity for swimming is regulated by neuroactive substances, most notably by 5-HT. Leeches with a high blood concentration of 5-HT swim more, and isolated nerve cord preparations engage in swimming activity spontaneously, when 5-HT levels are elevated (Willard, 1981). Swimming activity reaches a half-maximal level about 15 min after exposure to 50 mm 5-HT and returns to control levels about 30 min after washout. The primary effect in the isolated nerve cord (without the brain) is the appearance of spontaneous swim episodes, with few if any changes in cycle period, impulse frequencies, and the duration of episodes (Hashemzadeh-Gargari and Friesen, 1989). Bath application of 5-HT can even induce isolated ganglia individual to express the rudiments of the swimming rhythm. These hormonal effects, also observed when the 5-HT-containing Retzius cells are stimulated, standincontrasttotherapid activation of swimming by depolarization of the other 5-HTcontaining neurons, cells 21/61 (Kristan and Nusbaum, 1983). In the latter case, swim initiation appears as a synaptic rather than as a hormonal event; however, the importance of 5-HT, acting as a local hormone and neuromodulator, cannot be overstated. There is a negative correlation between the state of satiety in leeches and swimming behavior hungry leeches have higher levels of 5-HT and swim more readily in response to stimulation (Young et al., 1981; Lent, 1985). Therefore it appears likely that 5-HT levels are broadly important in regulating the appetitive phase of feeding behavior in the leech (Lent and Dickinson, 1984). Because focal application of 5-HT to the subesophageal ganglion terminates swimming (Crisp and Mesce, 2003), spatial differences in 5-HT modulation may contribute to transitions from the appetitive phase of feeding (swimming) to the consummatory one (ingesting the blood meal), when swimming is counterproductive. During the initiation of ingestion, the serotonergic Retzius neurons stop firing (Wilson et al., 1996; Zhang et al., 2000), in sharp contrast to an earlier view in which the Retzius neurons were thought to command both phases of feeding (Lent, 1985). Although the behavioral roles of dopamine are the least understood of the amines, dopamine also may play an important role in feeding (biting) behavior because dopamine-containing fibers have been found within the three accessory ganglia controlling the jaws (Crisp et al., 2002). In addition, bath application of dopamine to isolated nerve cords inhibits all ongoing and nerve-evoked swimming; this is correlated with the discovery that dopaminergic neurons are directly coupled to Tr2 (Crisp and Mesce, 2004). Thus dopamine has the potential to coordinate biting with the termination of swimming. [As mentioned earlier, Tr2 has been found to be a more potent swim terminator than swim activator (O Gara and Friesen, 1995).] Octopamine, the last of the monoamines discussed here, can induce swimming when bath applied to isolated nerve cords with the brain removed (Hashemzadeh-Gargari and Friesen, 1989) or with it attached (Crisp and Mesce, 2003). The dorsolateral octopamine (DLO) cells have been identified as the set of segmental neurons containing and synthesizing octopamine (Gilchrist et al., 1995; Crisp et al., 2002). The segmental Leydig cells, which closely neighbor the DLOS, were at first thought to contain octopamine (Belanger and Orchard, 1988). Although the Leydig cells are not octopaminergic or synaptically linked to the DLOs (Gilchrist et al., 1995; Crisp et al., 2002), these earlier studies helped to establish that octopamine is a naturally occurring neuromodulator in the leech. Because swimactivating mechanosensory inputs (T and P cells) have been found to co-activate the DLOs, these octopamine and 5-HTcontaining cells (Gilchrist and Mesce, 1997) may act in parallel with the Retzius neurons and other serotonergic cells (61 and 21). Subsequent studies have documented that bath application of a mixture of the two amines (isolated nerve cords with brains) results in a novel non-additive suppression of swimming, followed by a robust activation of swimming after the mixture is removed during a 30 min saline wash (Mesce et al., 2001). Related to the modulation of feeding behavior, 5- HT or octopamine also might be involved in the circadian regulation of behavior observed in a predatory leech (Angstadt and Moore, 1997). Further evidence that 5-HT is a critical hormone for the expression of swimming activity comes from depletion studies. Thus in isolated nerve cords acute treatment with reserpine which blocks the monoamine vesicle transporter eliminates all swimming activity, which is restored when 5-HT is subsequently bath-applied (Hashemzadeh-Gargari and Friesen, 1989). In intact animals, injection of reserpine into the crop depletes all amines for many weeks. Such animals cease normal biting behavior, their bodies become rigid, and sensitivity to stimulation is greatly reduced. Surprisingly, prolonged tactile stimulation can evoke swimming, which then persists far longer than in control animals (O Gara et al., 1991). This apparent anomaly may be a consequence of the loss of other amines, such as dopamine or octopamine, which are also depleted by reserpine (O Gara et al., 1991). Because dopamine has now been linked to the suppression of swimming (Crisp and Mesce, 2004), the reserpine-induced loss of this inhibitory factor could contribute to prolonged swimming in treated animals. Finally, it was found that when 5-HT is chronically removed from the nervous system of juveniles through treatment with 5,7-dihydroxytryptamine (5,7-DHT), swimming is not expressed in the adults (Glover and Kramer, 1982). The swim gating neurons, cells 204/5, with their direct involvement in swim initiation, are obvious candidates for modulation by 5-HT. A comparative study of cell 204 properties in normal saline and following exposure to bathapplied 5-HT revealed that 5-HT reduces the threshold for swim initiation via intracellular depolarization of these swim-gating neurons. Moreover, elevated 5-HT converted cell 204 into a trigger cell, so that even brief stimulation of cell 204 elicited swim episodes (Fig. 17A and B; Angstadt and Friesen, 1993a). Concomitant with these functional alterations, cell 204 in the presence of bath-applied 5-HT displayed enhanced postinhibitory rebound and afterhyperpolarization, mediated by Na + - dependent and Na + -independent conductances (Angstadt and Friesen, 1993b). The DI and VI MNs were depolarized slightly by elevated 5-HT levels but, as for cell 204, steady state I V

26 304 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) importantly from a functional viewpoint, brief pulses of injected current caused larger phase shifts when the inhibitory MNs were exposed to bath-applied 5-HT. The dynamics of the synaptic interactions of these MNs were altered by 5-HT, with increased and more rapid onset of, and recovery from, synaptic fatigue (Fig. 17C; Mangan et al., 1994b). Application of drugs that increase the intracellular concentration of camp mimic the effects of bath-applied 5-HT (Hashemzadeh-Gargari and Friesen, 1989), hence elevated camp is a likely mediator of the swim enhancing effects of 5-HT, whether through the alterations demonstrated in cell 204 and the inhibitory MNs, in oscillator INs, or in as yet unidentified swim excitor cells. Fig. 17. Modification of neuronal physiology and function by 5-HT. (A and B) Bath application of 5-HT transforms the swim-gating neuron, cell 204, into a trigger cell in an isolated nerve cord preparation. In both panels, the upper traces show the amplitude and duration of intracellular currents applied to cell 204 (middle traces). Identical current pulses have little effect in normal saline (A), but elicit a swim episode when 5-HT is elevated (DP records in lower traces of B). (C) Serotonin induces time-dependent membrane potential trajectories in MNs. Depolarization (by current injection, not shown) of an inhibitor MN (cell DI, upper traces) hyperpolarizes its postsynaptic target (the contralateral cell VI, lower traces). Bath-applied 5-HT induces presynaptic relaxation and postsynaptic fatigue with subsequent postinhibitory rebound (parts A and B are reprinted with permission from Angstadt and Friesen, 1993a; part C is modified from Mangan et al., 1994a,b). relationships were essentially unaltered (Mangan et al., 1994a). As observed in cell 204, 5-HT induced an enhancement of postinhibitory rebound and of afterhyperpolarization following the cessation of depolarizing current pulses. Most Role of sensory feedback In addition to the mechanosensory activity that elicits swimming, the neuronal circuit for swimming is also affected by sensory feedback during the production of swimming. Recently, the source of this sensory feedback has been described definitively as stretch receptors in the leech body wall, and the detailed function of one type of stretch receptor those located in the ventral body wall has been described in detail. Whole-body undulations, as seen during swimming in leeches, lamprey, or snakes is most effective when the waveform comprises about one wavelength (or slightly greater to minimize yaw; Fig. 14A; Taylor, 1952; Gray, 1958, 1968; Kristan et al., 1974a). The triumphant central oscillator theory informs us that neuronal circuits within the CNS generate the fundamental rhythms, however caveats reminding us of the importance of sensory feedback for shaping fully expressed movement rhythms have appeared repeatedly in the literature on motor systems (Kristan and Stent, 1975; Kristan and Calabrese, 1976; Pearson et al., 1983; Pearson and Ramirez, 1990). In the leech, sensory feedback plays a significant role in setting the swim cycle period, which is longer in the absence of sensory feedback (Kristan and Calabrese, 1976). More critically, intersegmental phase lags, which are about 208/ segment in swimming leeches are reduced to 8 108/segment in the isolated nerve cord (Pearce and Friesen, 1984). Feedback appears to be less critical in the expression of swimming behavior in lampreys and in coordination within the crayfish swimmeret system, where the isolated CNS can generate appropriate periods and intersegmental phase lags (Wallén and Williams, 1984; Grillner et al., 1991; Mulloney et al., 1993; Friesen and Cang, 2001). Sensory feedback is, of course, a feature of all animal locomotory systems. In leeches, feedback was deduced from experiments with the following results: (1) the cycle period of swimming leeches increases when the viscosity of the medium is increased (Gray et al., 1938); (2) stretching the body wall in nerve cord - body wall preparations alters the intensity of MN bursts, increases cycle period, and can even terminate swimming activity (Kristan and Calabrese, 1976); (3) mechanical expression of body movements is essential for the continuation of swimming movements in a partially restrained leech (Kristan and Stent, 1975) and (4) interseg-

27 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) mental coordination between two ends of a leech with a severed nerve cord is largely unimpaired, albeit there are greater intersegmental phase lags across the lesion site (Fig. 18A C; Yu et al., 1999). This last set of experiments overturned the long-held view that an intact nerve cord is essential for intersegmental coordination in leech swimming (Schülter, 1933; Kristan et al., 1974a). Moreover, because intersegmental phase lags generated within the nerve cord are too small, and those engendered by sensory feedback alone are too large, these experiments suggest that the shape of a swimming leech, a single cycle of a quasi-sinusoidal wave, arises from a compromise between central and peripheral coordination (Yu et al., 1999). Eight pairs of putative stretch receptors embedded in the segmental longitudinal muscles of leech body walls appear to have properties required for providing appropriate sensory feedback during swimming. These sensory neurons have peripheral somata, with dendrites that insert into longitudinal muscle fibers (Blackshaw and Thompson, 1988; Blackshaw, 1993; Huang et al., 1998). These neurons respond to stretch with graded hyperpolarization, which is conveyed electronically to nerve cord ganglia via huge (>20 mm in diameter; Cang et al., 2001; Gerta Fleissner, personal communication) non-spiking axons. Recordings from the axon of the ventral stretch receptor (VSR) which innervates VLM in nerve cord body wall preparations reveals membrane potential oscillations during swim activity with amplitudes up to 10 mv Fig. 18. Comparison of intersegmental phase lags in normal and severed nerve cord (SNC) leeches. Inset: preparations and electrode placements for intact (A) and SNC leeches (B). Traces showing swim bursts were obtained with extracellular nerve recordings from DP(7) and DP(14). Bursting activity remains coordinated in the two halves of the leech even with the nerve cord cut. C. Intersegmental phase lags in three types of preparations depicted as polar plots. Numbers are means + S.D. Phase lags in intact animals lie between those observed in isolated nerve cords and SNC leeches. (Modified from Yu et al., 1999). and a phase of about The VSR hyperpolarizes not only when tonic tension is increased by manually stretching the body wall, but also when body wall tension is increased naturally via MN (cell VE-4) stimulation (Fig. 19A C; Cang et al., 2001). Finally, hyperpolarization of the VSR mimics the effects of stretching the ventral body wall on impulse rates in MNs (Blackshaw and Kristan, 1990). These experiments demonstrate that the ventral stretch receptors are tension transducers for longitudinal muscles. [Tactile receptors in the nerve cord sheath might also contribute to sensory feedback (Smith and Page, 1974)]. Recent experiments reveal that the state of the VSR can influence intersegmental phase relationships (Cang and Friesen, 2000). In these experiments, sinusoidal currents were injected into the VSR axon near a midbody ganglion of an isolated nerve cord preparation. Records of swimming activity, and hence phase, were obtained from dorsal posterior (DP) nerves of this midbody ganglion and of the two adjacent ones. The phase of the sinusoidal current was varied over the full 3608 of the swim cycle. Under these conditions, intersegmental phase lags between the ganglion of the stimulated VSR axon (ganglion n) and its nearest neighbors depended on the phase of the injected current, such that at one phase (1208) the n (n 1) phase lags increased by about 58 and the n (n + 1) phase lag deceased by a similar amount. Conversely, when the phase of injected current was set to 2708, the n (n 1) phase lags decreased by 58, and that of n (n + 1) increased by a similar amount (Cang and Friesen, 2000). Thus, VSR activity can alter intersegmental phases in a phase-dependent manner, and hence may be critical for setting intersegmental phase lags to generate a single body wave. How is stretch receptor output conveyed to the neurons of the swim circuit? Extensive surveys with pairwise intracellular recordings revealed only weak, presumed polysynaptic interactions between the VSR and either inhibitory or excitatory MNs in the swim system. There is, however, a very strong electrical connection between the VSR and cell 33. In addition, there are inhibitory and excitatory interactions with other oscillatory INs, cells 28, 115, and 208, that are likely to be polysynaptic (Fig. 19D; Cang et al., 2001). VSR interactions with INS were functionally significant, for depolarization of the VSR greatly reduced the amplitude of swim oscillations in cells 28, 115, and 208. Also, in experiments to mimic body wall stretch, induced VSR hyperpolarization decreased the excitatory excursions in cell DE-3 and increased those of VE-4 during swimming activity expressed in isolated nerve cord preparations. The functional significance of VSR input for swim oscillations is clear: (1) the VSRs undergo rhythmic oscillations in membrane potential in preparations with the nerve cord attached to a flap of body wall; (2) rhythmic current injection into the VSR entrains the ongoing swimming rhythm in isolated nerve cord preparations, with a phase angle that is positively related to the frequency of current injection; (3) strong depolarization of the VSR shifts the swim phase (Yu and Friesen, 2004). These effects of the VSR on swim expression must be mediated by interactions between the VSR and oscillatory INs, which then provide the pathway for effects on

28 306 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) the MNs, including the observed modification of intersegmental phase lags. Of the eight putative stretch receptors in midbody segments, an additional six have been identified through filling their axons with Alexa Fluor 1 hydrazide dye (Fan and Friesen, 2005). Two of these have striking axon arborizations within segmental ganglia because their processes send terminals, unlike those of the VSR, also into the contralateral neuropil. Like the axon of the VSR, the giant axons of these cells do not conduct action potentials. Nevertheless, they also exhibit small, spike-like events that are generated within their central terminals. One of these axons is associated with dorsal longitudinal muscles and hence is called the dorsal stretch receptor (DSR). During fictive swimming, the DSR undergoes rhythmic oscillations that differ in phase from oscillations recorded during swimming activity in a nerve cord body wall preparation. The interactions of the DSR and the other identified putative stretch receptors with the circuits that control swimming or other behaviors remain to be found Functional aspects of the central oscillator Questions about the origins of the oscillations that underlie leech swimming have given rise to a series of answers. One answer is that individual ganglia are capable of generating the rudiments of the swimming rhythm when either swim-gating neurons are stimulated (Weeks, 1981) or 5-HT is bath applied (Hashemzadeh-Gargari and Friesen, 1989). Neuronal circuits within these ganglia comprise a unitary oscillator rather than the paired half-centers of the vertebrate spinal cord (Brown, 1911; Friesen and Hocker, 2001), probably because of the extensive connections, electrical and synaptic, that link bilateral cells in leech ganglia (Fig. 15A). Although initial modeling of the segmental swim circuit yielded cycle periods that were unrealistically short, more recent studies with analog neuromimes support the view that the identified interactions could account for these rudimentary oscillations (Wolpert and Friesen, 2000; Wolpert et al., 2000). In fact, although highly sensitive to parameter alterations, a computer model based on the identified intrasegmental connections generated membrane potential waveforms mimicking those observed in extended nerve cords (Taylor et al., 2000). The ability of individual ganglia to generate swim-like oscillations is not uniformly distributed along the nerve cord. The strongest swimming activity, either in isolated ganglia, or pairs of ganglia, occurs in the middle third of the nerve cord, from about M7 M12 (Pearce and Friesen, 1985a; Hocker et al., 2000), although this activity is never as robust as that of nerve cords extending from M2 to the tail brain. Only weak, erratic swim-like bursting occurs in individual isolated anterior ganglia, M2 M5; isolated ganglia posterior to M12 appear unable to generate even such swim rudiments. For producing swim oscillations, the functionality of nerve cord ganglia Fig. 19. Responses of the ventral stretch receptor (VSR) in a nerve cord body wall preparation (inset). (A) Depolarization of cell VE-4 by current injection (upper trace, intracellular record) causes increased tension in VLM (lower trace) that in turn induces hyperpolarization in the VSR (middle trace, intracellular record). (B) Relationships between MN activity and tension in ventral longitudinal muscle [tension (R,11)]. Rhythmic MN activity in cell 8 (intracellular record, upper trace; extracellular record from a DP nerve, bottom trace), causes rhythmic tension alterations in the body wall (middle trace). (C) VSR membrane potential oscillations (upper trace) are phase-locked to the swimming rhythm (lower trace). (D) Summary of interactions between the VSR and swim-related neurons. Of the several interactions between the VSR and cell 33, only the electronic interaction between the VSR and cell 33 is likely to be monosynaptic. Symbols as in previous figures (redrawn from Cang and Friesen, 2000 and Cang et al., 2001).

29 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) appears like an inverted U, low at the two ends and highest in the center. In addition, the period of swimming expressed in completely isolated ganglia, or short chains, is U-shaped; the cycle period is shortest in the center of the cord and longer at either end (Hocker et al., 2000). Based on the weakness of oscillations generated in isolated ganglia, the oscillator that generates swim oscillations should not be viewed as a chain of weakly coupled oscillators. Instead, the system relies on strong, extensive intersegmental interconnections to create robust oscillations from weak subunits. As stated earlier, the INs project at least six segments in each direction (Poon et al., 1978; Weeks, 1982b; Pearce and Friesen, 1985b; Friesen and Hocker, 2001). Thus in the mid nerve cord, 13 oscillator subunits are connected by direct synaptic interactions these might be considered to be the unit oscillator. As described above, sensory feedback contributes to intersegmental phase and to cycle period. This is shown most dramatically in reduced caudal preparations of the leech, which undergo vigorous, coordinated swimming movements even though the isolated posterior cord does not support swim oscillations (Hocker et al., 2000). However, even single segments, if isolated chronically from the nerve cord, can acquire swimming activity (Kristan and Guthrie, 1977). Intersegmental phase relationships are determined by period gradients in unit oscillators, coupling strength, and asymmetry in intersegmental interactions (Skinner and Mulloney, 1998a). Asymmetry in the functional strength of intersegmental coupling was assessed in the leech through experiments on Z-cut preparations, in which a given midbody ganglion was driven by input of differing cycle periods through ascending connections on one side and descending on the other by selective hemi-lesions of the ventral nerve cord. Correlation and spectral density analyses of the rhythmicity in this preparation demonstrated that effectiveness of ascending and descending interactions in the middle of the nerve cord are about equal (Friesen and Hocker, 2001). The anterior-to-posterior phase lags observed during swimming in the leech nerve cord must arise from asymmetry in the synaptic interactions between INs because: (1) coupling strength among midbody ganglia is approximately symmetrical and (2) the U-shaped period gradient tends to generate nonuniform intersegmental phase lags. Early modeling studies, relying on graphical analysis or modeling with electronic neuromimes suggested that the asymmetry in the identified, intersegmental interactions could account, at least qualitatively, for the observed phase lags (Friesen and Stent, 1977; Friesen et al., 1978; Friesen and Pearce, 1993). A subsequent computer study incorporated the swim circuits as a chain of phase oscillators coupled by multiple signal channels to mimic the intersegmental connections among ganglia. This model successfully accounted quantitatively for normal intersegmental phase delays, for increases in phase lag when the number of connected ganglia is reduced, and for alterations in phase lags induced by lesions and temperature manipulations (Pearce and Friesen, 1988). Mostly recently, a more biophysical, systems approach to modeling intersegmental coordination demonstrated again that the observed phase relationships are predicted by the identified intersegmental interactions (Zheng et al., 2004). A recent refinement and extension of the coupled phase oscillator model was used to study further the role of interactions within the nerve cord and between the central circuit and sensory feedback in intersegmental coordination (Cang and Friesen, 2002). This model is more realistic than its immediate predecessor because channels mimicking intersegmental interactions were limited to those identified experimentally (Fig. 20A). Moreover, the approach was to constrain the model at each step in its construction by experimental results followed by tests in which model output was compared to novel experimental data. As in the earlier phase model, phase shifts of segmental unit oscillators by intersegmental inputs were specified by phase response curves (PRCs; Fig. 20B). These curves were shaped through the use of subsidiary modeling. Relative PRC amplitudes were set to ensure symmetric intersegmental coupling strengths. The extended model also incorporated stretch receptors, constrained by the phase-shift effect of the VSR described above (Cang and Friesen, 2000). Simulations with this extended model reproduced a remarkable replica of swimming activity in leeches, including: (1) intersegmental phase lags of 8 108/ segment that exhibited a small positive period dependence (Kristan and Calabrese, 1976; Pearce and Friesen, 1984); (2) increases in phase lag when the length of the nerve cord is reduced (Pearce and Friesen, 1985b) and (3) intersegmental coordination with increased phase lags when the nerve cord is severed in mid body (Yu et al., 1999). Thus the known topology of the swim circuit can account for intersegmental coordination even though not all neurons or interactions in this circuit are identified. Students of rhythmic motor systems are deeply interested in the mechanisms that generate the cycle period (Friesen and Stent, 1978). The initial mechanism proposed for the leech swim circuits, based on the four pairs of oscillatory INs then identified (Friesen et al., 1976, 1978), focused on intra- and intersegmental interactions that form closed loops of inhibition (recurrent cyclic inhibition, RCI; Székely, 1964). Such inhibitory loops can generate stable oscillations with multiple intrasegmental phases and, concomitantly, intersegmental phase lags. The validity of this model was supported by graphical analysis and neuromime simulations, which yielded cycle periods and both intra- and intersegmental phase relationships similar to those observed in isolated nerve cord preparations (Friesen and Stent, 1977). Subsequent experiments, which demonstrated that an isolated ganglion could generate swim-like oscillations (Weeks, 1981; Hashemzadeh- Gargari and Friesen, 1989; Hocker et al., 2000), cast the RCI model into doubt and supported reciprocal inhibition (RI), which generates antiphasic oscillations (Brown, 1911; Friesen, 1989d; Brodfuehrer et al., 1995b). The RI model is currently invoked to account for locomotory oscillations in many species (Friesen, 1994), including lamprey. Perhaps the question of whether RCI or RI generates the swimming rhythm in leeches poses a false dichotomy. Weak, long-period oscillations with inappropriate phase relationships (Weeks, 1981; Hashemza-

30 308 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 20. Modeling and overview of the leech swim system. (A) Reduced circuit diagram employed to model intersegmental coordination. Cell numbers and phase lags as in Fig. 15. (B) Functional model: individual ganglia are modeled as phase oscillators that interact via signals transmitted during the active sector of any given neuron (shaded arcs). The signals advance or delay the phase of the local oscillator in accordance with physiologically realistic phase response curves. This simple model can account well for coordination in isolated nerve cords. (C) Schematic model of the complete swim system. Tension in the body wall, caused both by MN output and the environment, provides sensory feedback to the central swim oscillator circuits, thereby modulating both cycle period and phase in the intact leech. Symbols: SR, stretch receptor;, central oscillator (with intra- and intersegmental components). With the addition of sensory feedback and mechanical coupling between segments, the phase model generates a realistic simulation of swimming in the intact leech. Parts A and B are modified from Cang and Friesen, 2002; partcismodifiedfromyu, deh-gargari and Friesen, 1989) might be generated by RI, whereas the robust multiphasic oscillations recorded from preparations comprising multiple segments of the nerve cord, might be the result of known and other, as yet unidentified, intersegmental inhibitory loops. Given the weakness of segmental oscillators and the strength and broad extent of intersegmental interactions, the conclusion that intersegmental interactions are essential components of the swim oscillator seems inescapable Gaps in our current knowledge One obvious gap in the description of the leech swim circuit is that additional oscillatory INs and their interactions await identification. Two of the identified neurons cells 60 and 33 lack identified inputs. Additionally, intersegmental targets for cells 115 and 60 remain unknown (Fig. 15). A scanning technique, in which groups of neurons are depolarized by focal increases in extracellular K + concentrations (Friesen and Brodfuehrer, 1984), cutting-edge optical imaging (Cacciatore et al., 1999; Taylor et al., 2003; Briggman et al., 2005), and intracellular injections of dual tracer dyes (Alexa and Neurobiotin; Fan et al., 2005; Fan and Friesen, 2005) are proving helpful in locating the missing neurons. Detailed information on the strength of synaptic interactions and the biophysics of INs is needed, particularly for the construction of detailed biophysical models. Also, the physiology and links with the swim oscillator of only one segmental stretch receptor has been studied thoroughly; many more mapping studies are need to determine how the DSR and other stretch receptors provide sensory feedback to control cycle period and intersegmental phase lags. Moreover, there is limited knowledge of the biomechanics of DLM activation contraction strengths, rates of contraction, and length-tension relationships (Miller, 1975; Mason and Kristan, 1982; Wilson et al., 1996a). At the functional level, little is known about the control of swimming in leeches. For example, how does the brief output of trigger neurons lead to prolonged excitation in swim-gating neurons (Brodfuehrer and Thorogood, 2001)? Finally, the relative importance of central oscillators versus sensory-central loops in setting cycle period and intersegmental phase relationships in intact leeches or, for that matter, in other animals (Pearson and Ramirez, 1997) remains largely unknown. Even prior to more complete information, it is not premature to develop computer models of leech swimming like those already available for lamprey (Ekeberg and Grillner, 1999), which encompass the central neuronal oscillator, muscle mechanics, and sensory feedback. Such a complete model would provide a quantitative description of the leech swimming system presented schematically in Fig. 20C Vermiform crawling Behavior Vermiform crawling is a rhythmic behavior with two major phases extension and contraction that are typically coordinated with attachment and release of the front and back suckers (Fig. 21). A single cycle starts with a leech fully contracted and with both suckers attached. The front sucker releases and the animal starts to extend by contracting circular muscles. The extension starts at the front end and moves progressively more posterior. When the body is fully extended, the front sucker reattaches and the front end begins to contract. The contraction wave progresses posteriorly, putting tension on the posterior end of the body. When the contraction wave reaches about two-thirds of the way to the tail end, the back sucker actively releases. When the contraction wave reaches the posterior end, the rear sucker reattaches, thus completing one step cycle. In intact leeches, a step takes 3 10 s (Stern-Tomlinson et al., 1986), although it can take up to 20 s in dissected leeches

31 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) (Baader and Kristan, 1995; Cacciatore et al., 2000). This type of crawl step is one of two distinct modes of crawling displayed by leeches (Stern-Tomlinson et al., 1986). The other form, called inch-worm crawl or looping is faster (1 3 s) and the suckers are brought adjacent to one another at the end of contraction. Inch-worm crawling is seen only when a leech is under water (it tends to fall on its side when it attempts to inch-worm in air), and when it is strongly stimulated (e.g. when pinched or very hungry). Inch-worming is more efficient because the leech progresses by nearly a fully-extended body length with each inch-worm step, and much less (the body length at full extension minus the length at full contraction) during a vermiform step. Most studies have focused on vermiform steps, because it is difficult to provide a leech with the appropriate conditions for inchworming while recording from its nervous system. (Please note that all further references to crawling in this review refer to vermiform crawling.) Elongation of a segment is produced by a contraction of the circular muscles in a segment, and contraction is produced by the co-contraction of all the longitudinal muscles in that segment. For both elongation and contraction, the behavior begins at the front end and moves smoothly posteriorly as a wave. Hence, in a single segment, crawling appears as an alternation of bursting in the circular and longitudinal MNs. This pattern repeats itself, with a delay, in successively more posterior segments, thereby producing the intersegmental progression of the elongation and contraction waves. This pattern has been recorded in semi-intact (Baader and Kristan, 1992), and isolated nervous systems (Eisenhart et al., 2000) Kinematics To characterize the movement patterns during crawling, pieces of white sutures were knotted onto the skin of many segments and the animals were video-taped as they crawled (Fig. 22A; Stern-Tomlinson et al., 1986; Cacciatore et al., 2000). These analyses showed that the elongation phase was significantly more prolonged in slower crawl cycles, and that the contraction phase was short and varied significantly less with step cycle duration (Fig. 22B). In addition to variations in the elongation phase, step cycles also got longer because the delay from rear sucker placement and front sucker release increased with step cycle period. The average contraction and elongation duration diminishes as the wave gets to the posterior end of the animal (Fig. 22C(i)), reflecting the fact that the front of the animal stays contracted (or elongated) as the wave passes to the posterior end Motor neuron activity The motor neuronal activity recorded in both semi-intact and isolated nerve cord preparations is fully consonant with the kinematic data; circular muscle MNs produce impulse bursts in each segment that alternate with bursts in MNs that innervate longitudinal muscle, and the bursts appear progressively later in more posterior segments in both semi-intact preparations (Fig. 22C(ii)) and isolated nerve cords (Fig. 22C(iii)). Although the cycle periods in these two preparations are much longer than in intact animals, the coordination is the same in all three preparations; data for intersegmental travel time (ISTT) plotted against step duration for both dissected preparations fall on the regression lines calculated from the data for the intact animals (Fig. 22B; Cacciatore et al., 2000). Fig. 21. Schematic diagram of crawling behavior. This is a more detailed drawing of vermiform crawling than was provided in Fig. 3D. This figure emphasizes two features: (1) both the elongation and the contraction move slowly from front-to-back along the body and (2) there is a phase in the middle of the step when the back end of the animal is elongating while the front end is beginning to contract (from Cacciatore et al., 2000) Sensory input Although the basic crawling motor pattern produced in the isolated nervous system has the essential features seen in more intact preparations, there are several differences: A. The period is much longer than in intact animals (as long as 30 s);

32 310 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 22. Kinematics of crawling. (A) Segmental progression of the crawling step. Threads were sewn onto the skin of a leech (image on the left), which was videotaped as it crawled. Distances were measured from the head end to segment 2 (H-2), from segment 18 to the tail end (18-T), and between all other adjacent segments. Three plots of length vs. time are shown for the front end (H-2), back end (18-T), and one segment in the middle (10). Both the elongations and the contractions move from front-to-back, with contractions appearing to move through the animal faster than elongations. (B) Plot of the rate at which elongations and contractions move through the animal, the intersegmental travel time (ISTT) as a function of the duration of step cycles. The lines are the linear regressions for the elongation (open circles) and contractions (closed circles). The slopes of the two lines are significantly different, showing that elongations move through the leech s body more slowly

33 B. There is much more variability in the period than in either fully intact or semi-intact preparations and C. The duration of the bursts is greater than in semi-intact preparations. The bursts are so long that the circular motor bursts (elongation) overlap with the longitudinal motor bursts (contraction), particularly in the rear end of the nerve cord because the contractions occur relatively closer to the elongations in the rear of the animal (Fig. 22C). W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) These differences are likely due to the lack of sensory input in the isolated nerve cord, which in the intact animal supplies tonic excitation as well as cycle-by-cycle feedback, and regularizes and shortens the motor bursts. The source of the sensory feedback is not known. In addition to the effects of sensory input on the basic motor pattern, other, mostly anecdotal observations suggest that crawling is a highly variable behavior. For instance, mechanosensory stimuli delivered to the rear of the animal during extension will often cause it to release its rear sucker and swim away. In fact, leeches sometimes make this transition from elongation to swimming spontaneously, with no obvious stimulation of any sort. Identical stimuli delivered to a contracting leech will speed up the contraction, but never evoke swimming. (In fact, it seems impossible to elicit swimming in a leech with its front sucker attached.) Models Two kinds of models have been proposed to explain leech crawling. The first is a neuronal model that simulates the MN patterns along the nerve cord, and the second is a biomechanical model that explains how the motor patterns produce movements. In the neuronal model (Fig. 23), there is a single oscillator at the anterior end of the nerve cord that drives a motor controller for elongation, and a second one for contraction in the first body segment. Each segment has its own set of elongation and contraction motor controllers that are driven by the homologous controller in the previous segment. To produce a realistic motor output, the motor controllers must have positive feedback within a segment; to produce the full range of cycle periods observed, there must be parallel input to every segment that provides the same level of tonic input to all segments. The magnitude of this tonic input controls the cycle period (the greater the tonic input, the shorter the cycle period), although positive feedback is required for the tonic input to exert its effect. Without positive feedback, increasing the tonic input has very little effect on the period. This model is constrained by a large set of kinematic data and recordings from MNs in semiintact (Baader and Kristan, 1995) and isolated nerve cords (Eisenhart et al., 2000), including the effects of a variety of Fig. 23. Neuronal model of crawling. (A) The simplest model that produced a crawling step. The connections within each segment produce an elongation followed by a contraction (represented as an E/C unit) when the front segment is provided with tonic excitatory input (i s ). Positive feedback is needed in each E/ C unit to match the observation that the MNs fire at a frequency independent of the step duration. Shown to the right are the firings of just the circular MNs (elongation units) in 10 of the segments from front-to-back. Note that increasing the strength of i s (the serial input) increases the MN firing rate slightly, but did not change the rate of progression along the cord; i.e. the ISTT is relatively constant. (B) The same circuit, with the addition of a parallel input, I p, to each segmental E/C unit. With varying strength of I p, the ISTT varies over a range comparable to that seen in the intact animal (figures from Cacciatore et al., 2000). lesions of nerves and connectives (Stern-Tomlinson et al., 1986; Baader and Kristan, 1995; Cacciatore et al., 2000), but it awaits identification of any of the elements of the pattern generators. A biomechanical model of leech movements has been constructed (Skierczynski et al., 1996) based upon the anatomy of the leech, passive mechanical properties of the body wall (Wilson et al., 1996a), contractile properties of the muscles (Mason and Kristan, 1982; Wilson et al., 1996a), and pressures measured in the body lumen as leeches crawl, swim, and shorten (Wilson et al., 1996b). The model incorporates three muscle layers: longitudinal, circular, and dorsoventral (flattener). These features are shown in Fig. 24A. The model assumes that each segment maintains a constant volume at all times, and that MNs cause muscle shortening in only their own segment. Because of this geometry, longitudinal muscles (which shorten a segment) are antagonists to both the circular and the flattener muscles (both of which elongate a segment by decreasing its cross-sectional area, although they produce very different shapes). To produce movements, bursts of MN spikes cause muscle tension and shortening. Both are important: a low than contractions. (C) Summary of the MN activity patterns measured from intact animals (i), semi-intact preparations (ii), and isolated nerve cord preparations (iii). Open boxes show the average time spent in contraction and shaded boxes show the average time spent in contraction. Data for the intact animals (i) were estimated from the durations of the contractions and relaxations of the individual segments, from data like those in A. For semi-intact (ii) and isolated nerve cord (iii) preparations, durations of bursts in longitudinal (contraction) and circular (elongation) MNs were collected. Two features stand out: (1) the more intact the preparation, the shorter the step cycle duration, and (2) contractions and elongations were distinct in intact and semi-intact animals, whereas they overlapped significantly in isolated nerve cord preparations (from Cacciatore et al., 2000).

34 312 W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) Fig. 24. Biomechanical model of crawling. (A) Features used in the model of a single segment. The cross-section of the leech is ovoidal, with each of the four semi-axes of the ellipse (a 1, a 2, b 1, b 2 ) independently variable, determined by the circular muscle activity in each of the four quadrants. The length (L)ofeach segment is controlled directly by the activity of four longitudinal muscle bands attached to the top, bottom, and sides of the ellipses. (B) Extension phases of the crawling movements predicted by a 16-segment model of the leech. The data used to drive the segments are those measured from kinematics (i) and from motor neuronal bursts in semi-intact (ii) and isolated nerve cord preparations (iii), as shown in Fig. 22C. Three frames are shown for each condition, representing the beginning of the extension (top image), the midst of the elongation (middle image), and the end of the elongation (bottom image). The times to achieve these states varied in the three cases (from Kristan et al., 2000). level of sustained tension in antagonistic muscles is required to produce a rigidity that serves as a hydroskeleton for muscles to produce movements. (Contraction of one muscle in an otherwise flaccid segment produces very little movement of anything but itself; if the segment is rigid, a single muscle can move the whole segment). The biomechanical model was applied first to crawling. Motor neuronal bursts from isolated nerve cords (Eisenhart et al., 2000) and from semi-intact preparations (Baader and Kristan, 1992) were used to make estimates of the motor bursts from the kinematic studies. In each time bin (corresponding to 0.6 s), the firing of each MN excited its appropriate muscle, which generated tension until that segment achieved its steadystate shape (Mason and Kristan, 1982). The only mechanical interaction among segments was imposed by the constraint that adjacent segments share a cross-sectional face. To find a steadystate shape for the whole animal, the minimum total potential energy was calculated (Skierczynski et al., 1996). Sixteen segments were modeled (14 midbody segments were identical; the most anterior three segments were lumped with the head into one larger segment, and the most posterior two segments were lumped with the tail); the shape of the model approximates a leech fairly well (Skierczynski et al., 1996; Kristan et al., 2000). When the motor bursts estimated from the kinematics were used, the movements looked very much like a crawling leech (Fig. 24B). This is not surprising because the model was tuned to produce these movements. What was surprising was that although the pressures generated by the model were in no way constrained, they produced amplitudes that were very close to those measured in a crawling leech. In addition, the motor bursts recorded in semi-intact animals produced a slower and less efficient crawl, but the modeled animal appeared to be crawling. When motor bursts from the isolated nerve cord were used to drive the model, however, the behavior was very wrong in at least two ways: (1) the internal pressures in the model were much larger than any ever recorded from a real leech; (2) parts of the animal were contracting while other parts were elongating, so that the crawl steps were extremely inefficient very little progress was made with each step. These results suggest why MN burst patterns during crawling closely match the biomechanics in which they operate. For instance, the large pressures seen in (1) occur because circular MNs overlap somewhat with longitudinal bursts, a condition never seen in an intact or semi-intact animal. This suggests that sensory feedback can be used to tune a CPG to work in a biomechanically efficient range of its capability. Other biomechanical models have been used to simulate leech crawling (Wadepuhl and Beyn, 1989; Alscher and Beyn, 1998) and swimming (Jordan, 1998). These models use very simplified geometries, but more sophisticated mathematics for the crawling model (Alscher and Beyn, 1998), and a realistic model of animal/substrate coupling in the swimming model (Jordan, 1998). All of these models will be aided by more information about the neuronal circuits underlying the behaviors Initiation of crawling Intracellular activation of several identified neurons in the anterior brain of a leech can elicit overt behavior in semi-intact and fictive behavior in isolated nerve cord preparations. Examples include swim initiation by trigger neurons and SE cells. Another such neuron, cell R3b1, which is located in the third neuromere of the subesophageal ganglion, can initiate the crawling motor pattern in both semi-intact and isolated nerve cord preparations (Esch et al., 2002). It is effectively a crawl gating neuron because crawling stops when the depolarization is released. During a crawl episode initiated in another way (e.g. by stimulation of the posterior end), R3b1 oscillates above its resting potential. Surprisingly, depolarizing R3b1 can also produce swimming, or a combination of swimming and crawling. During the latter, hybrid behavior, swimming bursts occur during the extension phase of crawling; this odd behavior is sometimes seen even in intact animals when they are in very shallow water.

35 Gaps in our current knowledge Crawling behavior is well characterized kinematically, but little is known about the neuronal basis of its CPG. Because the crawling pattern can be elicited in isolated nerve cords (Eisenhart et al., 2000; Briggman et al., 2005), identifying the CPG should be a relatively straight-forward task. The neuronal model (Cacciatore et al., 2000) suggests a simple explanation for intersegmental coordination, but is agnostic about the location and nature of the underlying neuronal circuits. An appealing feature of the isolated nerve cord preparation for studying crawling is the possibility of studying the contextdependence of behavioral choice. For example, in both intact animals and isolated nerve cords, appropriate stimulation reliably triggers swimming, whereas the same stimuli delivered during the contraction phase of crawling speeds up the contraction but never leads to swimming (Eisenhart et al., 2000) Feeding W.B. Kristan Jr. et al. / Progress in Neurobiology 76 (2005) All leech species feed by ingesting prey or blood through their anterior sucker (Sawyer, 1986). The anterior sucker is attached to the host or prey, and a muscular pharynx just posterior to the esophagus produces suction by contraction of extrinsic muscles that pull open the lumen of the pharynx. A major distinction among leech families is whether they ingest their prey whole or suck its blood or other internal fluids. The medicinal leech attaches its front only to hosts much larger than itself, rasps through the host s skin with eversible jaws, and sucks the blood that oozes from the tripartite wound. Anticoagulants and anti-platelet substances are exuded into the wound to keep blood oozing from the cut during the min that it takes a leech to complete feeding. In fact, blood continues to ooze from the leech bite for several hours after the leech completes its meal. This ability to remove quantities of blood was the initial appeal of leeches medicinally (Payton, 1981). They are used in modern medicine to keep blood flowing through surgically replaced appendages until their venous supply can be re-established, usually after 3 4 days (Whitaker et al., 2004) Behavior While medicinal leeches feed, they produce slow peristaltic movements (Fig. 25), both front-to-back and back-to-front (Wilson and Kleinhaus, 2000). These movements serve to propel the blood rearward into the gut and lateral gut pouches present in segments Blood can be stored in these pouches for several months without decaying. Ultimately, the blood is moved into the intestine, where commensal bacteria help to digest the red blood cells (Braschler et al., 2003). While they are feeding, leeches are unresponsive even to very strong mechanosensory stimulation that would normally elicit a vigorous response (Misell et al., 1998). In fact, leeches can be cut open while they are feeding and will continue to eat (Lent, 1985). Such half leeches, or semi-intact leeches with only the head and a few anterior segments intact (Wilson et al., 1996; Zhang et al., 2000), will feed for longer times than normal, Fig. 25. Feeding behavior. (A) Measuring muscle activity in seven locations along the leech as it feeds. The drawing shows a leech attached to a membrane stretched over a tube containing blood. Bipolar EMG electrodes have been inserted into the longitudinal muscles at seven locations along the leech s body, in segments (B) EMG recordings during peristaltic movements from front to back. The large gray arrows indicate the direction of the peristalsis. (C) Recordings in the same animal when the peristalsis initially progressed back-tofront, then reversed about midway through the recording to go front-to-back for two cycles, only to reverse again near the end of the recording (from Wilson and Kleinhaus, 2000). presumably because gut filling is part of the feedback mechanism to terminate swimming (Lent and Dickinson, 1987). For many weeks after feeding, leeches are sluggish and passive. They tend to hide and, when disturbed, withdraw rather than advance or locomote (Lent and Dickinson, 1984; Groome et al., 1993). Hungry leeches, on the other hand, are found near the surface of a pond, are very active, and tend to move toward a disturbance rather than to withdraw from it (Sawyer, 1981, 1986; Lent et al., 1988). In the lab, hungry leeches orient toward the source of surface water waves and then swim towards that source (Young et al., 1981). This behavior can be elicited by the water waves in the dark and or visually by shadow waves