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Brain gate system 2012-2013 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 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
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Page 1: Brain gate system 2012-2013 - gistroyalcse.weebly.com · Brain gate system 2012-2013 3 Parietal Lobe The parietal lobe is a part of the brain positioned above (superior to) the occipital

Brain gate system 2012-2013

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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

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

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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.

Frontal Lobe

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.

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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

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.

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.

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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,

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

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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 low-

level 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.

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 fine-

tuning 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

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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

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

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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 cross-

membrane voltage can alter the function of

voltage-dependent ion channels. If the voltage

changes by a large enough amount, an all-or-

none 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

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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."

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

into computer commands.

NUERO CHIP:

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.

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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.

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PREPROCESSING:

The raw EEG signal requires some

preprocessing before the feature extraction.

This preprocessing includes removing

unnecessary frequency bands, averaging the

current brain activity level, transforming the

measured scalp potentials to cortex potentials

and denoising. Frequency bands of the EEG :

. Band

Frequency [Hz]

Amplitude [_V]

Location

Alpha (_) 8-12 10 -150 Occipital/Parietal regions µ-rhythm 9-11 varies Precentral/Postcentral regions Beta (_) 14 -30 25 typically frontal regions Theta (_) 4-7 varies varies Delta (_) <3 varies varies DETECTION:

The detection of the input from the user and

them translating it into an action could be

considered as key part of any BCI system. This

detection means to try to find out these mental

tasks from the EEG signal. It can be done in

time-domain, e.g. by.

comparing amplitudes of the EEG and in

frequency-domain. This involves usually

digital signal processing for sampling and band

pass filtering the signal, then calculating these

time -or frequency domain features and then

classifying them. These classification

algorithms include simple comparison of

amplitudes linear and non-linear equations and

artificial neural networks. By constant

feedback from user to the system and vice

versa, both partners gradually learn more from

each other and improve the overall

performance.

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

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.

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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 2001. 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 e-mail, 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

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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.”

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: OTHE

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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.

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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 50–200 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

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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.


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