Supplemental Data. Cellular and Network Mechanisms. of Operant Learning-Induced. Compulsive Behavior in Aplysia

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1 Current Biology, Volume 19 Supplemental Data Cellular and Network Mechanisms of Operant Learning-Induced Compulsive Behavior in Aplysia Romuald Nargeot, Morgane Le Bon-Jego, and John Simmers Supplemental Experimental Procedures Experimental Animals Adult A. fasciata, which are found locally from August to November in the Bassin d'arcachon (France), were supplied by the Lycée de la Mer (Gujan Mestras) and the Laboratoire de Biologie Marine (Arcachon). A. californica were purchased from the University of Miami (Fl, USA) and were used in the seasonal period when local A. fasciata are unavailable. Animals were maintained at 15 C in filtered artificial sea water (ASW) until used, and were fed daily with fresh seaweed (Ulva lactuca) obtained from the Lycée de la Mer and the Station de Biologie Marine at Roscoff (France). The animals remained unfed for 2 days before experiments to stimulate food-seeking during food-reward training. Behavioral Training Animals were first randomly assigned to a control (untrained) and two experimental groups to be given contingent or non-contingent food reward training, then placed individually in a small (8 dm 3 ) transparent aquarium placed over a mirror and filled with 5 L of fresh, aerated ASW. After an initial test period to verify that the different groups of animals expressed similar levels of spontaneous radula activity, training lasted 40 min and differed according to the particular group protocol. Throughout the behavioral status test and training periods, animals in all three groups were subjected to a continuous application of a food stimulus (1.5 cm 2 piece of seaweed) to the lips, without this inciting stimulus being bitten. The additional stimulus used for foodreward training consisted of an intra-buccal injection of 20 µl of a seaweed juice obtained from the maceration of 0.4 g of dried Ulva lactuca in 10 ml of ASW. Juice delivery was timed either to occurrences of radula bite cycles (in the contingent-reward training procedure) or at fixed intervals and independently of the timing of spontaneous bites (for non-contingent training). Since the neuronal correlates of these training protocols are reliably expressed for ~4 h by buccal feeding circuitry [S1], post-training effects were assessed by recording fictive radula biting in isolated B.g. preparations without intervening behavioral testing. All in vitro preparations were tested with identical experimental procedures and without knowledge of the behavioral history of animals. Only individual preparations that were subsequently found to match the statistically predominant phenotype of fictive biting expected from their respective training protocols (i.e. stereotyped rhythmic fictive biting in contingent preparations, slower non-rhythmic biting in control and non-contingent preparations; see Figure S1) were used for further detailed analysis.

2 In Vitro Electrophysiology Animals were anesthetized by the injection of ml of MgCl 2 into their hemolymph. After isolation, the bilaterally-paired buccal ganglia (B.g.) were pinned out in a Sylgard-lined Petri dish containing ASW (mm): NaCl, 450; KCl, 10; MgCl 2 (6H 2 O), 30; MgSO 4, 20; CaCl 2 (2H 2 O), 10; Hepes, 10 (ph adjusted to 7.4 with HCl). The preparations were maintained at 15 o C by means of a Peltier cooling device and were not superfused during the actual experiment. Extracellular recordings and stimulations were made using wire electrodes placed against selected peripheral nerves (see Figure 1A). Monopolar (recording) and bipolar (stimulation) electrodes were insulated from the bath with Vaseline petroleum jelly. Radula motor patterns, each consisting of motor nerve bursts that would normally drive protraction, retraction and closure phases of a radula bite cycle, were elicited by monotonic stimulation (8.5 V, 0.3 ms at 2 Hz) of the two bilateral 2,3 nerves (n.2,3; [S2]) generated by a single Grass S88 stimulator and delivered through a photo-isolation unit. Intracellular recordings and stimulations were made from de-sheathed ganglia with glass microelectrodes (tip resistance ~10-20 MΩ) filled with 2 M KCH 3 CO 2. All recorded signals were amplified by Axoclamp-2B electrometers (Molecular Devices, Palo Alto, CA), visualized on a Tektronix 5113 oscilloscope, digitized by an analog to digital converter (CED 1401, Cambridge Electronic Design, UK) and analyzed with Spike2 software (Cambridge Electronic Design, UK). Intrasomatically-recorded B30, B63 and B65 neurons were identified electrophysiologically according to the following criteria: Firstly, they produce spontaneous bursting activity that occurs during the protraction phase of each radula motor pattern [S3-S5]. Second, they have no axonal projections in peripheral buccal nerves, and third, they all produce mixed chemical excitatory and electrotonic synaptic potentials in the contralateral B31/32 motoneurons. Moreover, B30 has no axonal projection in the cerebro-buccal connectives (CBC), it produces IPSPs and a long-lasting activation of the bilateral B8 motoneurons and it does not make conventional synaptic connections with the B61/62 motoneurons [S5]. B63 was identified on the basis of its axonal projection in the contralateral CBC, a unique excitatory synapse with the contralateral B61/62 motoneurons and its lack of a conventional synapse with B8. B65 was identified by its absence of axonal projections in the CBCs and its production of facilitating EPSPs in the bilateral B61/62 motoneurons [S4,S6]. The input resistance (R i ) of neurons was measured by two-electrode current clamp whereby a recorded cell s membrane potential was held at -70 mv by continuous current injection through one electrode that also served to inject additional constant 2 s current pulses of -5 to -15 na in 5 na steps. The second electrode was then used to record the resultant voltage change and membrane input resistance was calculated as the ratio of the maximum voltage deflection over current pulse amplitudes of -10 na. The strength of electrical coupling between selected pairs of neurons was calculated as the ratio of the maximum postsynaptic voltage response to the corresponding maximum presynaptic voltage deflection elicited by a 2 s negative current pulse. In these experiments, two presynaptic electrodes were again used, one to maintain the cell s resting membrane potential at - 70 mv and for additional negative current pulse injection, while the other electrode was used for voltage recording. The resting membrane potential of the postsynaptic neuron, which was simultaneously impaled with a third electrode, was not altered experimentally during the recording of the electrical synaptic potential. No significant differences were found in the initial resting membrane potentials of recorded postsynaptic neurons in the different experimental groups of preparations (see Figure S2A), indicating that changes in the coupling coefficient

3 between cell pairs in the different experimental groups were not due to initial differences in postsynaptic membrane potential. The bi-directionality of coupling between cells was also verified qualitatively by injecting current via the single post-junctional recording electrode and recording the voltage response in the previously pre-junctional neuron. Data Analysis To assess the temporal organization of fictive radula bite cycles or of spike bursts in individual neurons, autocorrelations were computed by Spike2 software over a fixed number of successive events: either 100 radula motor patterns recorded extracellularly from motor nerves, 800 action potentials in intracellular recordings of B30 and B65 neurons, or 2000 action potentials in intracellular recordings from B63 neurons. The differences in numbers of analyzed events in the different cell types reflected their typical spontaneous firing frequencies. Autocorrelations were then expressed as histograms of 2.5 s bin widths over ranges of 150 s or 300 s for the analysis of extracellularly-recorded motor patterns and intracellularly-recorded action potentials, respectively. The choice of these time scales reflected the slower burst frequencies of individual neurons in response to depolarizing current injection as compared to the shorter cycle periods of motor patterns generated by the buccal network under tonic stimulation of the peripheral 2,3 nerve. The expression of radula motor patterns or impulse bursts in individual neurons was considered to be rhythmically recurring (i.e. with regular inter-pattern intervals) when the corresponding autocorrelation histograms could be fitted (with a correlation coefficient r 0 at a significant level of p < 0.05) by a damped sinusoidal Gabor function with a minimum of three peaks, an amplitude of at least 10% above offset, and a period, phase lag, time constant 0 at a significant level of p < 0.05 ([S1,S7,S8]; Figure S1A). The cycle-by-cycle variability (or dispersion) of burst onsets in B30 or B65 neurons relative to the onset of B63 bursts was determined by angular analysis [S9]. For this, periods between repetitive B63 impulse bursts were considered as successive cycles of 360 degrees. Burst onsets were detected by spike2 software in which a burst of action potentials was defined as impulse discharge at a frequency >2 Hz for at least 1 s when this activity was elicited by buccal network activation in response to nerve 2,3 stimulation, or by impulses at a frequency >0.5 Hz for at least 4 s when activity was elicited in an individual cell by intracellular current injection. The onset of bursting in a specific neuron relative to B63 (0 ) was computed as an angular fraction of 360 degrees. The dispersion value for a cell's burst onsets in a given preparation was computed as the average distance (in degrees) between each angular fraction and the corresponding mean calculated over successive B63 burst cycles by using Oriana software (Kovach Computing Services, Anglesey, Wales) [S9]. Group comparisons were made using SigmaStat software (Systat, Richmond, CA, USA) with non-parametric statistical tests because of the departure from a normal distribution and/or non-homogeneity of variances within or between groups of data. The Wilcoxon paired-sample test (T) and the Friedman s analysis of variance by ranks (χ 2 ) were used for comparisons of 2 and 3 dependent groups of data, respectively, while the Kruskal-Wallis test (H) was used for comparisons of 3 independent data groups. Post-hoc pairwise multiple comparisons of samples of equal and unequal sizes were made using the Newman-Keuls multiple range test (q) and the Dunn test (Q), respectively. Comparisons of the proportion of in vitro preparations in which neurons expressed rhythmic bursting in unpaired-sample procedures were made using the Fisher exact test (P). All tests were considered significant for a probability level of p 0.05.

4 Supplemental References S1. Nargeot R., Petrissans C., and Simmers J. (2007). Behavioral and in vitro correlates of compulsive-like food-seeking induced by operant conditioning in Aplysia. J. Neurosci. 27, S2. Nargeot R., Baxter D.A., and Byrne J.H. (1997). Contingent-dependent enhancement of rhythmic motor patterns: An in vitro analog of operant conditioning. J. Neurosci. 17, S3. Hurwitz I., Kupfermann I., and Susswein A.J. (1997). Different roles of neurons B63 and B34 that are active during the protraction phase of the buccal motor programs in Aplysia californica. J. Neurophysiol. 78, S4. Kabotyanski E.A., Baxter D.A., and Byrne J.H. (1998). Identification and characterization of catecholaminergic neuron B65, which initiates and modifies patterned activity in the buccal ganglia of Aplysia. J. Neurophysiol. 79, S5. Jing J., Cropper E.C., Hurwitz I., and Weiss K.R. (2004). The construction of movement with behavior-specific and behavior-independent modules. J. Neurosci. 24, S6. Due M.R., Jing J., and Weiss K.R. (2004). Dopaminergic contributions to modulatory functions of a dual-transmitter interneuron in Aplysia. Neurosci. Lett. 358, S7. Engel A.K., König P., Gray C.H., and Singer W. (1990). Stimulus-dependent neuronal oscillations in cat visual cortex: Intercolumnar interaction as determined by cross-correlation analysis. Eur. J. Neurosci. 2, S8. Young M.P., Tanaka K., and Yamane S. (1992). On oscillating neuronal responses in the visual cortex of the monkey. J. Neurophysiol. 67, S9. Zar J.H. (1984). Biostatistical Analysis. Englewood Cliffs NJ: Prentice-Hall.

5 Figure S1. Contingent-Induced Regularization and Increase in Rate of Fictive Biting (A) Analysis of the temporal organization of successive radula motor patterns recorded during in vitro testing in control (A1), contingent (A2) and non-contingent preparations (A3). Fictive bite cycles (each defined by the start of protractor motoneuron activity) in control and non-contingent preparations were randomly distributed in time as indicated by their flat autocorrelation histograms that were not fitted significantly (n.s.) by a Gabor function. In contrast, radula motor patterns in the contingent preparations were rhythmically recurring (i.e. with regular cycle periods ~25 s) as indicated by the significant fit of the histograms by a sinusoidal Gabor function (bold line). Similar autocorrelation procedures were used to analyze the regularity of patterninitiating cell bursting as shown in the recordings of Figure S3. (B) Group comparisons. The proportions of in vitro preparations expressing rhythmic fictive biting (defined by autocorrelation analysis as seen in A) in control (Ctrl), contingent (Cont.) and non-contingent (Non-cont.) preparations were significantly different: Fisher exact unpaired comparisons indicated a significantly higher proportion of rhythmic preparations in the contingent group as compared to either the control (P = 0.021) or non-contingent groups (P = 0.021). The latter two groups were not significantly different (n.s.; P = 1). * p (C) The cycle frequency of radula motor patterns in the contingent group was significantly higher than in the control and non-contingent groups. The control and non-contingent groups were not significantly different. Kruskal-Wallis test: H 2 = Post-hoc Dunn pair-wise multiple comparisons for samples of unequal sizes: contingent versus control, Q = 2.61; contingent vs non-contingent, Q = 2.54; control vs non-contingent, Q = * p Error bars represent ± SEM.

6 Figure S2. Operant Conditioning Does Not Alter the Resting Membrane Potential of Pattern-Initiating Neurons but Leads to an Increase in Their Input Resistance (A) Mean resting potentials of B63, B30 and B65 neurons in control (unfilled bars), contingent (filled bars) and non-contingent preparations (shaded bars). For each cell type, no significant differences (n.s.) were observed between the three experimental groups. K-W test: B63, H 2 = 0.15; B30, H 2 = 0.75; B65, H 2 = (B) Input resistances (R i ) of neurons in the same experimental groups measured with two electrodes and calculated from the maximal membrane voltage deflection evoked by -10 na injected current from -70 mv resting potential. R i was significantly higher in contingent preparations than in control or non-contingent preparations. R i of neurons in control and noncontingent groups were not significantly different (n.s.). K-W test: B63, H 2 = 7.30; B30, H 2 = 7.03; B65, H 2 = Post-hoc N-K tests for B63 as representative of the three cell types: contingent vs control, q = 4.75; contingent vs non-contingent, q = 3.40; control vs noncontingent, q = * p 0.05 ; ** p 0.025; *** p

7 Figure S3. Contingent-Dependent Plasticity of Bursting in Functionally Isolated B30 and B65 Neurons Under similar experimental conditions as described in Figure 4, individually-activated B30 (A) and B65 cells (B) generated irregular spike bursts when continuously depolarized (with +2 na) in control (A1, B1) and non-contingent preparations (A3, B3). However, in contingent preparations (A2, B2), depolarization-induced bursting occurred at a higher rate and with stereotyped burst durations and inter-burst intervals. Vertical scales: 30 mv.

8 Figure S4. Voltage Dependence of Burst Frequency in Individual B30 and B65 Neurons Under single-cell activation as described in Figure 4, B30 (A) and B65 (B) neurons were continuously depolarized with two different current magnitudes (indicated below traces). The increase in burst frequency with membrane depolarization indicated that burst-generation was intrinsic to the neurons. In B30 and B65 of control (A1, B1) and non-contingent preparations (A3, B3), current-evoked matching of burst frequencies to those expressed by the same cell type in contingent preparations (A2, B2) did not produce regularized bursting. Moreover, currentinduced changes in the burst frequencies of cells in contingent preparations did not lead to irregular bursting.

9 Figure S5. Learning-Induced Increase in Electrical Coupling between Contralateral Pattern-Initiating Neurons Group comparisons showing contingent-induced increases in electrical coupling strength between the bilateral B63 (A), bilateral B65 (B), B63 and contralateral B30 (C), and between B63 and contralateral B65 (D) neurons. * p 0.05 ; ** p 0.025; *** p (N-K posttests). n.s. not significant.