Brain gate system

Transcription

1 Introduction :- How does the brain control motor function? The brain is "hardwired" with connections, which are made by billions of neurons that make electricity whenever they are stimulated. The electrical patterns are called brain waves. Neurons act like the wires and gates in a computer, gathering and transmitting electrochemical signals over distances as far as several feet. The brain encodes information not by relying on single neurons, but by spreading it across large populations of neurons, and by rapidly adapting to new circumstances. Motor neurons carry signals from the central nervous system to the muscles, skin and glands of the body, while sensory neurons carry signals from those outer parts of the body to the central nervous system. Receptors sense things like chemicals, light, and sound and encode this information into electrochemical signals transmitted by the sensory neurons. And interneurons tie everything together by connecting the various neurons within the brain and spinal cord. The part of the brain that controls motor skills is located at the ear of the frontal lobe. How does this communication happen? Muscles in the body's limbs contain embedded sensors called muscle spindles that measure the length and speed of the muscles as they stretch 1 and contract as you move. Other sensors in the skin respond to stretching and pressure. Even if paralysis or disease damages the part of the brain that processes movement, the brain still makes neural signals. They're just not being sent to the arms, hands and legs. A technique called neuro feedback uses connecting sensors on the scalp to translate brain waves into information a person can learn from. The sensors register different frequencies of the signals produced in the brain. These changes in brain wave patterns indicate whether someone is concentrating or suppressing his impulses, or whether he is relaxed or tense. Human Brain The human brain is the center of the human nervous system. It has the same general structure as the brains of other mammals, but is larger than expected on the basis of body size among other primates. Estimates for the number of neurons (nerve cells) in the human brain range from 80 to 120 billion. Most of the expansion comes from the cerebral cortex, especially the frontal lobes, which are associated with executive functions such as self-control, planning, reasoning, and abstract thought. The portion of the cerebral cortex devoted to vision is also greatly enlarged in human beings, and several cortical areas play

2 specific roles in language, a skill that is unique to humans. Despite being protected by the thick bones of the skull, suspended in cerebrospinal fluid, and isolated from the bloodstream by the blood brain barrier, the human brain is susceptible to many types of damage and disease. The most common forms of physical damage are closed head injuries such as a blow to the head, a stroke, or poisoning by a variety of chemicals that can act as neurotoxins. Infection of the brain, though serious, is rare due to the biological barriers which protect it. The human brain is also susceptible to degenerative disorders, such as Parkinson's disease, multiple sclerosis, and Alzheimer's disease. A number of psychiatric conditions, such as schizophrenia and depression, are thought to be associated with brain dysfunctions, although the nature of such brain anomalies is not well understood. The frontal lobe is an area in the brain of mammals, located at the front of each cerebral hemisphere and positioned anterior to (in front of) the parietal lobe and superior and anterior to the temporal lobes. It is separated from the parietal lobe by a space between tissues called the central sulcus, and from the temporal lobe by a deep fold called the lateral (Sylvian) sulcus. The precentral gyrus, forming the posterior border of the frontal lobe, contains the primary motor cortex, which controls voluntary movements of specific body parts. The frontal lobe contains most of the dopamine-sensitive neurons in the cerebral cortex. The dopamine system is associated with reward, attention, short-term memory tasks, planning, and motivation. Dopamine tends to limit and select sensory information arriving from the thalamus to the fore-brain. A report from the National Institute of Mental Health says a gene variant that reduces dopamine activity in the prefrontal cortex is related to poorer performance and inefficient functioning of that brain region during working memory tasks, and to slightly increased risk for schizophrenia. Frontal Lobe 2

3 parietal cortex (PPC) receives somatosensory and/or visual input, which then, through motor signals, controls movement of the arm, hand, as well as eye movements. Parietal Lobe The parietal lobe is a part of the brain positioned above (superior to) the occipital lobe and behind (posterior to) the frontal lobe. The parietal lobe integrates sensory information from different modalities, particularly determining spatial sense and navigation. For example, it comprises somatosensory cortex and the dorsal stream of the visual system. This enables regions of the parietal cortex to map objects perceived visually into body coordinate positions. The parietal lobe plays important roles in integrating sensory information from various parts of the body, knowledge of numbers and their relations and in the manipulation of objects. Portions of the parietal lobe are involved with visuospatial processing. Although multisensory in nature, the posterior parietal cortex is often referred to by vision scientists as the dorsal stream of vision. This dorsal stream has been called both the 'where' stream and the 'how' stream. The posterior 3 Occipital Lobe The occipital lobe is the visual processing center of the mammalian brain containing most of the anatomical region of the visual cortex. The primary visual cortex is Brodmann area 17, commonly called V1 (visual one). Human V1 is located on the medial side of the occipital lobe within the calcarine sulcus; the full extent of V1 often continues onto the posterior pole of the occipital lobe. V1 is often also called striate cortex because it can be identified by a large stripe of myelin, the Stria of Gennari. Visually driven regions outside V1 are called extrastriate cortex. There are many extrastriate regions, and these are specialized for different visual tasks, such as visuospatial processing, color discrimination and motion perception.

4 A significant functional aspect of the occipital lobe is that it contains the primary visual cortex. Retinal sensors convey stimuli through the optic tracts to the lateral geniculate bodies, where optic radiations continue to the visual cortex. Each visual cortex receives raw sensory information from the outside half of the retina on the same side of the head and from the inside half of the retina on the other side of the head. The cuneus (Brodmann's area 17) receives visual information from the contralateral superior retina representing the inferior visual field. The lingula receives information from the contralateral inferior retina representing the superior visual field. The retinal inputs pass through a "way station" in the lateral geniculate nucleus of the thalamus before projecting to the cortex. Cells on the posterior aspect of the occipital lobes' gray matter are arranged as a spatial map of the retinal field. Functional neuroimaging reveals similar patterns of response in cortical tissue of the lobes when the retinal fields are exposed to a strong pattern. If one occipital lobe is damaged, the result can be homonomous vision loss from similarly positioned "field cuts" in each eye. Occipital lesions can cause visual hallucinations. Lesions in the parietal-temporal-occipital association area are associated with color agnosia, 4 movement agnosia, and agraphia. Damage to the primary visual cortex which is located on the surface of the posterior occipital lobe, can cause blindness due to the holes in the visual map on the surface of the visual cortex that resulted from the lesions. Temporal Lobe The temporal lobe is a region of the cerebral cortex that is located beneath the Sylvian fissure on both cerebral hemispheres of the mammalian brain. The temporal lobe is involved in auditory perception and is home to the primary auditory cortex. It is also important for the processing of semantics in both speech and vision. The temporal lobe contains the hippocampus and plays a key role in the formation of long-term memory. The superior temporal gyrus includes an area (within the Sylvian fissure) where auditory signals from the cochlea (relayed via several subcortical nuclei) first reach the cerebral cortex. This part of the cortex (primary

5 auditory cortex) is involved in hearing. Adjacent areas in the superior, posterior and lateral parts of the temporal lobes are involved in high-level auditory processing. In humans this includes speech, for which the left temporal lobe in particular seems to be specialized. Wernicke's area, which spans the region between temporal and parietal lobes, plays a key role (in tandem with Broca's area, which is in the frontal lobe). The functions of the left temporal lobe are not limited to lowlevel perception but extend to comprehension, naming, verbal memory and other language functions. The underside (ventral) part of the temporal cortices appear to be involved in high-level visual processing of complex stimuli such as faces (fusiform gyrus) and scenes (parahippocampal gyrus). Anterior parts of this ventral stream for visual processing are involved in object perception and recognition. The medial temporal lobes (near the Sagittal plane that divides left and right cerebral hemispheres) are thought to be involved in episodic/declarative memory. Deep inside the medial temporal lobes lie the hippocampi, which are essential for memory function particularly the transference from short to long term memory and control of spatial memory and behavior. Damage to this area typically results in anterograde amnesia. 5 Cerebellum The cerebellum (Latin for little brain) is a region of the brain that plays an important role in motor control. It may also be involved in some cognitive functions such as attention and language, and in regulating fear and pleasure responses,[1] but its movement-related functions are the most solidly established. The cerebellum does not initiate movement, but it contributes to coordination, precision, and accurate timing. It receives input from sensory systems of the spinal cord and from other parts of the brain, and integrates these inputs to fine tune motor activity.[2] Because of this finetuning function, damage to the cerebellum does not cause paralysis, but instead produces disorders in fine movement, equilibrium, posture, and motor learning.[2] In terms of anatomy, the cerebellum has the appearance of a separate structure attached to the bottom of the brain, tucked underneath the cerebral hemispheres. The surface of the cerebellum is covered with finely spaced parallel grooves, in striking contrast to the

6 broad irregular convolutions of the cerebral cortex. These parallel grooves conceal the fact that the cerebellum is actually a continuous thin layer of tissue (the cerebellar cortex), tightly folded in the style of an accordion. Within this thin layer are several types of neurons with a highly regular arrangement, the most important being Purkinje cells and granule cells. This complex neural network gives rise to a massive signal-processing capability, but almost all of its output is directed to a set of small deep cerebellar nuclei lying in the interior of the cerebellum. In addition to its direct role in motor control, the cerebellum also is necessary for several types of motor learning, the most notable one being learning to adjust to changes in sensorimotor relationships. Several theoretical models have been developed to explain sensorimotor calibration in terms of synaptic plasticity within the cerebellum. Most of them derive from early models formulated by David Marr and James Albus, which were motivated by the observation that each cerebellar Purkinje cell receives two dramatically different types of input: On one hand, thousands of inputs from parallel fibers, each individually very weak; on the other hand, input from one single climbing fiber, which is, however, so strong that a single climbing fiber action potential will reliably cause a target Purkinje cell to fire a burst of 6 action potentials. The basic concept of the Marr-Albus theory is that the climbing fiber serves as a "teaching signal", which induces a long-lasting change in the strength of synchronously activated parallel fiber inputs. Observations of long-term depression in parallel fiber inputs have provided support for theories of this type, but their validity remains controversial. Neuron A neuron is an electrically excitable cell that processes and transmits information by electrical and chemical signaling. Chemical signaling occurs via synapses, specialized connections with other cells. Neurons connect to each other to form neural networks. Neurons are the core components of the nervous system, which includes the brain, spinal cord, and peripheral ganglia. A number of specialized types of neurons exist: sensory neurons respond to touch, sound, light and numerous other stimuli affecting cells of the sensory organs that then send signals to the spinal cord and brain. Motor neurons receive signals from the brain and spinal cord, cause muscle

7 contractions, and affect glands. Interneurons connect neurons to other neurons within the same region of the brain or spinal cord. All neurons are electrically excitable, maintaining voltage gradients across their membranes by means of metabolically driven ion pumps, which combine with ion channels embedded in the membrane to generate intracellular-versus-extracellular concentration differences of ions such as sodium, potassium, chloride, and calcium. Changes in the crossmembrane voltage can alter the function of voltage-dependent ion channels. If the voltage changes by a large enough amount, an all-ornone electrochemical pulse called an action potential is generated, which travels rapidly along the cell's axon, and activates synaptic connections with other cells when it arrives. NEUROPROSTHETIC DEVICE: A neuroprosthetic device known as Braingate converts brain activity into computer commands. A sensor is implanted on the brain, and electrodes are hooked up to wires that travel to a pedestal on the scalp. From there, a fiber optic cable carries the brain activity data to a nearby computer. PRINCIPLE: "The principle of operation of the BrainGate Neural Interface System is that with intact brain function, neural signals are generated even though they are not sent to the arms, hands and legs. These signals are interpreted by 7

8 the System and a cursor is shown to the user on a computer screen that provides an alternate "BrainGate pathway". The user can use that cursor to control the computer, just as a mouse is used." into computer commands. NUERO CHIP: BrainGate is a brain implant system developed by the bio-tech company Cyberkinetics in 2003 in conjunction with the Department of Neuroscience at Brown University. The device was designed to help those who have lost control of their limbs, or other bodily functions, such as patients with amyotrophic lateral sclerosis (ALS) or spinal cord injury. The computer chip, which is implanted into the patient and converts the intention of the user 8 Currently the chip uses 100 hair-thin electrodes that 'hear' neurons firing in specific areas of the brain, for example, the area that controls arm movement. The activity is translated into electrically charged signals and are then sent and decoded using a program, which can move either a robotic arm or a computer cursor. According to the Cyberkinetics' website, three patients have been implanted with the BrainGate system. The company has confirmed that one patient (Matt Nagle) has a spinal cord injury, whilst another has advanced ALS.

9 In addition to real-time analysis of neuron patterns to relay movement, the Braingate array is also capable of recording electrical data for later analysis. A potential use of this feature would be for a neurologist to study seizure patterns in a patient with epilepsy. Braingate is currently recruiting patients with a range of neuromuscular and neurodegenerative conditions for pilot clinical trials in the United States. WORKING: Operation of the BCI system is not simply listening the EEG of user in a way that let s tap this EEG in and listen what happens. The user usually generates some sort of mental activity pattern that is later detected and classified. 9

10 PREPROCESSING: considered as key part of any BCI system. This The raw EEG signal requires some detection means to try to find out these mental preprocessing before the feature extraction. tasks from the EEG signal. It can be done in This preprocessing includes removing time-domain, e.g. by. unnecessary frequency bands, averaging the comparing amplitudes of the EEG and in current brain activity level, transforming the frequency-domain. This involves usually measured scalp potentials to cortex potentials and denoising. Frequency bands of the EEG :. digital signal processing for sampling and band pass filtering the signal, then calculating these time -or frequency domain features and then Band Frequency [Hz] Amplitude [_V] classifying Location them. These classification Alpha (_) algorithms Occipital/Parietal include regions simple comparison of µ-rhythm 9-11 varies amplitudes Precentral/Postcentral linear and non-linear regions equations and Beta (_) typically frontal regions Theta (_) 4-7 varies artificial varies neural networks. By constant Delta (_) <3 varies feedback varies from user to the system and vice versa, both partners gradually learn more from DETECTION: each other and improve the overall The detection of the input from the user and performance. them translating it into an action could be CONTROL: The final part consists of applying the will of the user to the used application. The user chooses an action by controlling his brain activity, which is then detected and classified 10 to corresponding action. Feedback is provided to user by audio-visual means e.g. when typing with virtual keyboard, letter appears to the message box etc.

11 TRAINING: The training is the part where the user adapts to the BCI system. This training begins with very simple exercises where the user is familiarized with mental activity which is used to relay the information to the computer. Motivation, frustration, fatigue, etc. apply also here and their effect should be taken into consideration when planning the training procedures BIO FEEDBACK: The definition of the biofeedback is biological information which is returned to the source that created it, so that source can understand it and have control over it. This biofeedback in BCI systems is usually provided by visually, e.g. the user sees cursor moving up or down or letter being selected from the alphabet. A boon to the paralyzed -Brain Gate Neural Interface System The first patient, Matthew Nagle, a 25-year-old Massachusetts man with a severe spinal cord injury, has been paralyzed from the neck down since Nagle is unable to move his arms and legs after he was stabbed in the neck. During 57 sessions, at New England Sinai Hospital and Rehabilitation Center, Nagle learned to open simulated , draw circular shapes using a paint program on the computer and play a simple videogame, "neural Pong," using only his thoughts. He could change the channel and adjust the volume on a television, even while conversing. He was ultimately able to open and close the fingers of a prosthetic hand and use a robotic limb to grasp and move objects. Despite a decline in neural signals after few months, Nagle remained an active participant in the trial and continued to aid the clinical team in producing valuable feedback 11

12 concerning the BrainGate` technology. NAGLE S STATEMENT: I can't put it into words. It's just I use my brain. I just thought it. I said, "Cursor go up to the top right." And it did, and now I can control it all over the screen. It will give me a sense of independence. OTHE Software Behind Braingate: System uses algorithms and pattern-matching techniques to facilitate communication. The algorithms are written in C, JAVA and MATLAB.. Signal processing software algorithms analyze the electrical activity of neurons and translate it into control signals for use in various computer-based applications. OTHEAPPLICATIONS: 12

13 Rats implanted with BCIs in Theodore Berger's experiments. Several laboratories have managed to record signals from monkey and rat cerebral cortexes in order to operate BCIs to carry out movement. Monkeys have navigated computer cursors on screen and commanded robotic arms to perform simple tasks simply by thinking about the task and without any motor output. Other research on cats has decoded visual signals. Garrett Stanley's recordings of cat vision using a BCI implanted in the lateral geniculate nucleus (top row: original image; bottom row: recording) In 1999, researchers led by Garrett Stanley at Harvard University decoded neuronal firings to reproduce images seen by cats. The team used an array of electrodes embedded in the thalamus (which integrates all of the brain s sensory input) of sharp-eyed cats. Researchers targeted 177 brain cells in the thalamus lateral geniculate nucleus area, which decodes signals from the retina. The cats were shown eight short movies, and their neuron firings were recorded. Using mathematical filters, the researchers decoded the signals to generate movies of what the cats saw and were able to reconstruct recognisable scenes and moving objects. In the 1980s, Apostolos Georgopoulos at Johns Hopkins University found a mathematical relationship between the (based on a cosine function). He also found that dispersed groups of neurons in different areas of the brain collectively controlled motor commands but was only able to record the firings of neurons in one area at a time because of technical limitations imposed by his equipment. There has been rapid development in BCIs since the mid-1990s. Several groups have been able to capture complex brain motor centre signals using recordings from (groups of neurons) and use these to control external devices, including research groups led by Richard Andersen, John Donoghue, Phillip Kennedy, Miguel Nicolelis, and Andrew Schwartz. 13

14 Diagram of the BCI developed by Miguel Nicolelis and collegues for use on Rhesus onkeys Later experiments by Nicolelis using rhesus monkeys, succeeded in closing the feedback loop and reproduced monkey reaching and grasping movements in a robot arm. With their deeply cleft and furrowed brains, rhesus monkeys are considered to be better models for human neurophysiology than owl monkeys. The monkeys were trained to reach and grasp objects on a computer screen by manipulating a joystick while corresponding movements by a robot arm were hidden.the monkeys were later shown the robot directly and learned to control it by viewing its movements. The BCI used velocity predictions to control reaching movements and simultaneously predicted hand gripping force. Other labs that develop BCIs and algorithms that decode neuron signals include John Donoghue from Brown University, Andrew Schwartz from the University of Pittsburgh and Richard Andersen from Caltech. These researchers were able to produce working BCIs even though they recorded signals from far fewer neurons than Nicolelis (15 30 neurons versus neurons). Donoghue's group reported training rhesus monkeys to use a BCI to track visual targets on a computer screen with or without assistance of a joystick (closed-loop BCI). Schwartz's group created a BCI for three-dimensional tracking in virtual reality and also reproduced BCI control in a robotic arm. CONCLUSION: The idea of moving robots or prosthetic devices not by manual control, but by mere thinking (i.e., the brain activity of human subjects) has been a fascinated approach. Medical cures are unavailable for many forms of neural and muscular paralysis. The enormity of the deficits caused by paralysis is a strong 14

15 motivation to pursue BMI solutions. So this idea helps many patients to control the prosthetic devices of their own by simply thinking about the task. This technology is well supported by the latest fields of Biomedical Instrumentation, Microelectronics, signal processing, Artificial Neural Networks and Robotics which has overwhelming developments. Hope these systems will be effectively implemented for many Biomedical applications. 15