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THE NEXT BIG THING: BRAIN MEMORY INTERFACE
COURSE: Management and Information Systems
INSTRUCTOR: Dr. Prithwis Mukerjee
Karingula Navneeth Rao
Vinod Gupta School of Management, IIT Kharagpur
In the present world of modernization where humans of this planet are able to conquer everything it
comes on his way. One thing which needs attention and need of the hour is how to store and retain so
many complex situations, things in the limited memory, and the solution to this problem leads us to
brain memory interface technology. Brain memory interface technology is the most important and
highly unexplored technology which has wide applications right from ranging the retention of memory
even after the so-called death of the brain and it can also be implemented in senses retention.
Brain interface Technology is the leveraging of technology in interfacing brain with external devices.
This is possible with the use of interfaces known as neuron silicon interfaces. This acts as a means of
communication between the human brains, even animals with the devices, which transmits and
receives to and from the brain. The signals then can be used to restore and retain the movements of
the sensory organs and data in the brain. The devices can range from simple circuits to silicon chips.
As of today, the interfaces have been successful in restoring damaged sights, movements and
hearing. The success stems from the fact that the brain is able to adapt to brain computer interfaces
and treat implant control prosthesis as natural limbs. Taking the Technology forward we can even
augment the human memory and retention capacity of the brain. Through this technology in the long
run can benefit the overall development of the human beings .
How different is Brain Interface technology from prosthesis?
Neuroprosthetics is an area of neuroscience concerned with neural prostheses which is using artificial
devices to replace the function of impaired nervous systems or sensory organs. Neuroprosthetics
typically connect the nervous system to a device, whereas Brain interface technology usually
connects the brain or nervous system with an interface system which can be a computer or any other
device. Practical neuroprosthetics can be linked to any part of the nervous system like peripheral
nerves where as brain interface technology is usually concentrated at a narrower class of systems
which interface with the central nervous system.Although there is difference between the way of
approach, neuroprosthetics and Brain interface technology seek to achieve the same aims.
TWO LEARNING SYSTEM
An interesting question for the development of a brain interface system is how to handle two learning
systems: The machine should learn to discriminate between different patterns of brain activity as
accurate as possible and the user of the BCI should learn to perform different mental tasks in order to
produce distinct brain signals.
Brain Interface research makes high demands on the system and software used. Parameter
extraction, pattern recognition and classification as well as the generation of neurofeedback for a
successful training of the user has to run in real-time.
Early research extensively focused on animals where in the initial stages several laboratories have
been successful in recording the signals from monkey’s cerebral tissues in order to operate brain
interface devices to carry out movement. Monkeys have been successful navigating the computer
cursors on screen and commanded robotic arms to perform simple tasks simply by thinking about the
task and without any motor output.
Monkey operating a Robotic arm with the use of brain machine interface technology
The studies of Fetz showed that monkeys could learn to control the deflection of a feedback meter
arm with neural activity. Such work in the 1970s established that monkeys could quickly learn to
voluntarily control the firing rates of individual and multiple neurons in the primary tissue. Studies that
developed algorithms to reconstruct movements from neurons, which control movement, date back as
early as 1970s.
Works by Apostolos found a mathematical relationship between the electrical responses of single
motor-cortex neurons that moved their arms based on a cosine function. He also found that dispersed
groups of neurons in different areas of the brain collectively controlled motor commands.
Rapid technological advancements have played a pivotal role in success of brain interface devices. In
early 20 century major breakthrough has occurred when scientists have decoded neuronal firings to
reproduce images seen by cats which can easily extended to human brains thereby serving a means
to restore memory. The team used an array of electrodes embedded in brain tissues which integrates
all of the brain’s sensory input of cat. Mathematical filters were used to decode the signals to generate
movies of what the cats saw .similar results in humans have been since then achieved by Scientists.
MODEL DEPICTING HOW BRAIN INTERFACE TECHNOLOGY CAN BE USED
BRAIN INTERFACE – WHAT IS ACHIEVED, WHAT IS THERE FOR THE FUTURE.
Invasive Brain interface
Invasive brain interface devices are those implanted directly into the brain and have the highest
quality signals. These devices extensively used to provide functionality to the people suffering from
paralysis. They are used to restore vision by connecting the brain with the external cameras and to
restore the use of limbs by using brain controlled robotic arms and legs.
Although the devices have wide applications, the problem with these types of devices is that they form
scar tissues over the devices as a reaction of the foreign matter. This reduces the efficiency of the
device and increases the risk of the patient.
In Vision science direct brain implants have been used to treat acquired blindness. A single array
Brain interface device containing 68 electrodes was implanted onto visual cortex and succeeded in
producing the sensation of seeing light. The system consists of cameras mounted on glasses to send
signals to the implant. Initially, the implant allowed seeing shades of grey in a limited field of vision at
a low frame-rate. Shrinking electronics and faster computers made his artificial eye more portable and
now enable him to perform simple tasks unassisted. In the future the technology can take us through
the use of devices to restore dead brain and memory.
Partially invasive Brain interface
Partially invasive brain interface devices are implanted inside the skull but outside the brain. Though
the signal strength is a bit low, it increases the safety of the patient as they eliminate the problem of
scar tissue formation. In this, the Electrocardiography measures the electrical activity of the brain
taken from beneath the skull similar to that of the non invasive one but the electrodes are embedded
in a thin plastic pad that is placed above the cortex.
The popular use of Technology has started in 2004 in which the first trail was done on a small boy
who played space invaders using the electrocardiography implant. This indicates that the control is
rapid which requires minimal training in usage of technology and can be ideal trade off between signal
fidelity and levels of invasiveness. In this the device directly is not connected to the brain tissue rather
than it is connected to the outside brain.
Light Reactive Imaging brain interface technology devices are still in the realm of theory. These would
involve implanting a laser inside the skull. The laser would be trained on a single neuron and the
neuron's reflectance measured by a separate sensor. When the neuron fires, the laser light pattern
and wavelengths it reflects would change slightly which allows monitoring single neurons which
require less contact with tissue and reduce the risk of scar-tissue build-up. It has not been studied
extensively until recently due to the limited access of technology and data.
Electrocardiography is a very promising intermediate Brain Interface modality as it possess
Higher spatial resolution
Better signal-to-noise ratio
Wider frequency range
Less training requirements and
Long term stability.
Non Invasive Brain interface
Non invasive Brain interface devices are the safest devices to use, though they are weak in
communicating with brain when it comes to signal quality and data. They are extensively used in
limbs movements and organs. The most widely used technology is used under this category is EEG.
This is capable of producing fine temporal resolution. They are relatively easy to use and cheap.
EEG is the most studied potential non invasive interface, mainly due to its fine temporal resolution
and ease of use, portability and low set up cost, however due to technological susceptibility to noise,
extensive training is required before the user can actually work on this technology.
Recordings of brainwaves produced by an electroencephalogram
Magentoencephalogram (MEG) is also widely used non invasive brain interfaces . It scanned humans
to play pong in real time by altering their brain blood flow through bio feedback techniques.
Magnetic resonance imaging (MRI) also works in the same way as that of MEG and used in non
invasive brain interfaces.
Recent advancements in technology made possible to develop Advanced Telecommunications
Research which reconstructs images directly from the brain and displays them on the computer.
Further extension of this technology can lead us to record the dreams in the minds and future is
about to become reality.
How Close Is a Workable Brain-Computer Interface?
It’s now just few moments away that brain interface is possible in this planet with the extensive
research conducted by the eminent scientist all over the world
Scientists led by Eduardo of Miguel Hernandez University have for the first time combined a number
of desirable features into a single brain computer interface that is non invasive, spontaneous and
Previous attempts at non invasive brain computer interfaces required that users only direct the
computer during certain time slots but now it can be done asynchronously .This is been possible
overcoming the bandwidth limitations of recording brain activity through EEGs external electrodes .
Eduardo and colleagues' approach gets around this limitation by using four different models, each
with assumptions that are sometimes the opposite others.
Intended application like spelling device, control of orthotic/prosthetic device, environmental control
STATISTICS OF PEOPLE WITH DISORDER IN INDIA
According to the Census 2001, there are 2.19 crore people with disabilities in India who constitute
2.13 per cent of the total population. This includes persons with visual, hearing, speech, locomotor
and mental disabilities.
Seventy five per cent of persons with disabilities live in rural areas, 49 per cent of disabled population
is literate and only 34 per cent are employed. The earlier emphasis on medical rehabilitation has now
been replaced by an emphasis on social rehabilitation.
Disability People suffering with disabiity in %
MOVEMENT 28 %
SPEECH DISABILTY 7%
In India alone there are 2.1 crore people suffering from disability and with the help of brain interface
technology one can change the life of the people.
Not just from the humanitarian perspective but also from business one there are huge amount of
potential which needs to be untapped.
Following applications are generally adapted by many companies
The wide use of brain interface technology can be applied to medical science and movements of
physical work which would otherwise not possible .An example to illustrate this motor imagery
example is taken
Based on a cue -arrow on the screen pointing to the left or to the right, the subject performs left and
right hand movement imageries which are of duration 3-4 seconds. To train the classifier between 40
and 160 trials are recommended. EEG should be recorded from electrode positions and the patterns
are displayed on the screen.
IN THE GAMING INDUSTRIES : An example to illustrate this is taken in ping pong game
Everybody knows the famous Ping-Pong game that was played in the seventies on TV sets. In this example
two persons are connected to the BCI system and each one is controlling the racket with motor imagery.
The racket moves upwards by left hand movement imagination and downwards by right hand movement
P300 Spelling devices:
The P300 paradigm presents e.g. 36 letters in a 6 x 6 matrix on the computer monitor. Each letter is
flashing up in a random order and the subject has to be concentrated on the letter it wants to write. As
soon as the corresponding letter is flashing up a P300 component is produced inside the brain. The
algorithms are analyzing the EEG data and select the letter with the highest P300 component. Then
this letter is written onto the screen .The number is dependent on the electrode position used, the
training level of the subject and the individual height of the P300 response of the subject.
In Copy Spelling mode first a word or a sentence has to be entered. The task of the subject is to copy
exactly each letter as shown in the following picture:
This allows calculating the error rate of the spelling device and is mainly used for the
training of the subject.
ECOG RECORDING: Widely used application in the developed countries and can be brought to
under and developing countries as the use of Brain interface technology treduces the cost of curing
the devices to minimal.
US Bamp is a CF recording device and therefore it can also be used for invasive recordings. The
picture below shows an ECoG electrode grid overlaying the brain. The electrode grid is connected to
the BCI system for real-time analysis and paradigm presentaion.
with the THIS
use of LEADS TO
The Multimodal Brain Orchestra: This application can serve as huge business applications to music
industries where the music devices can be interfaced with the brain interface technologies and can
change the way music industries are working. The science behind this is explained below.
4 members in the orchestra playing music with the power of their thoughts. They used two different non-
invasive Brain-Computer Interface Technology concepts to control their virtual and multi-modal instruments.
Two of them controlled the volume with the so-called Steady-State Visual-Evoked Potentials (SSVEP). The
other two members of the orchestra played the music with the so called P300 response.
Some of the most commonly used strategies to realize Brain interface technology by the business companies
are listed below with the introduction to it being at the top.
Imagery of movements of different limbs cause changes in oscillatory EEG activity over sensorimotor
areas of the central cortex. These changes can be classified by weighting spectral parameters of different
frequency bands for different electrode positions.
A P300 component is produced if an unlike event occurs. The P300 occurs about 300 ms after the event
and has to be detected by specific algorithms. The P300 components are mainly used to create a spelling
device for paralyzed patients.
Slow shifts of cortical potentials occur when a subject performs an imagery of expecting an event (like
waiting for a traffic light turning to green). The resulting DC-shift can be used for biofeedback to improve
the training effects and to generate a control signal for communication.
Also other mental tasks such as mental arithmetic, mental cube rotation or attention versus relaxation are
used to produce characteristic changes of EEG patterns. One attempt has also been not to guide the
subjects with any strategy but use specific EEG-biofeedback, so that the user attempts to find his/her own
strategy for producing the required changes in the EEG.
Another method uses steady-state visually evoked potentials (SSVEP) from flickering light sources.
Directing attention to a source with a specific flicker frequency enlarges evoked components in the EEG
with the same frequency.
Commercialization and companies in the foray of the business
The Company markets its electrode arrays under the BrainGate product name and has set the
development of practical BCIs for humans as its major goal. The BrainGate is based on the Utah
Array developed by Dick Normann.
Started in 1987 to develop Brain interfaces that would allow paralysed patients to communicate with
the outside world and control external devices. As well as an invasive BCI, the company also sells an
implant to restore speech. Neural Signals' Brain Communicator BCI device uses glass cones
containing microelectrodes coated with proteins to encourage the electrodes to bind to neurons.
Avery Biomedical Devices
Overall many paying patients were treated using William Dobelle's vision brain interface technology
device, the company is facing aversion in the licensing department.
Ambient developed the product The Audeo. The Audeo is being developed to create a human
machine interface for communication without the need of physical motor control or speech production.
Using signal processing, unpronounced speech representing the thought of the mind can be
translated from intercepted neurological signals.
Interactive Productline is a Swedish company whose objective is to develop and sell easy
understandable EEG products that train the ability to relax and focus. They developed a product
called Mindball in which players compete to control a ball's movement across a table by becoming
more relaxed and focused.
An Austrian company, Guger Technologies, has been offering Brain Computer Interface systems
since 1999. The company provides base Brain interface models as development platforms for the
research community to build upon, including the P300 Speller, Motor Imagery, and mu-rhythm. They
commercialized a Steady State Visual Evoked Potential BCI solution in 2008 with 4 degrees of
A Spanish company, Starlab, has entered this market in 2009 with a wireless 4-channel system called
ENOBIO. Designed for research purposes the system provides a platform for application
There are three main consumer-devices commercial-competitors in this area which have launched
such devices primarily for gaming- and PC-users are
Neural Impulse Actuator
Research is ongoing into synthetic or computer-mediated telepathy which would allow user-to-user
communication through analysis of neural signals. The research aims to detect and analyze the words
specific neural signals, using EEG which occurs before speech is vocalized, and to see if the patterns
are generalizable. The research extensively focused on military uses.
As number of companies are competing for the brain interface technology devices, one can select the
effectiveness of the device by the following parameters
Accuracy like classification error, hits vs. false, false positives.
Information transfer through decision speed, bit/min.
Number of classes like idling vs. activation of 1 class, 2 or more different classes.
Operation mode like synchronous: predefined decision intervals, asynchronous, free time decision
HURDLES OF BRAIN INTERFACE DEVICES
The major hurdles to better Brain Interfaces are both technical and rooted in neuroscience. Materials
science researcher must deliver more durable and better-tolerated implantable materials to prevent
failure and rejection. Engineers must craft smaller, higher resolution devices with more contacts,
higher density but that can also cover larger regions, to be able to record and activate the large
neuronal networks involved in brain functions. Better machine learning techniques to extract pertinent
information from neural signals without relying on human experts to identify them are required. Finally,
ways of dramatically increasing information transfer rates, and to optimize neuroplasticity are required
to get fast enough bandwidth from humans to devices to make their speed useful. Challenges on the
neuroscience side are equally important, most crucially determining on what scale to record neural
activity (e.g. single neurons, cortical columns, broad brain regions etc.), how much activity, and over
how large a region. We also need better techniques to map the diverse regions in the brain that work
together in cognition and other functions, both invasively and non-invasively in humans, in order to un
lock how they work.
FUTURE AHEAD OF US
The future of BCI research is extremely bright. The scientific community worldwide is making rapid
progress in each of the above challenge areas, as demonstrated by the number of devices being
invented, tested, deployed for human use, and the dramatically increasing research literature in the
area of BCI. Most crucially, the rate of information transfer from human brain to computers is rapidly
increasing, though in part by using more invasive technologies. Taking the step from repairing
damage and restoring function to augmenting our abilities to see, hear, move or think is a dramatic
one, and one with major ethical and moral implications. Devices to restore and enhance memory are
already being tested, and our growing understanding of how memories are encoded and retrieved
give dim glimpses of how information might be transferred from computer storage to human
consciousness, though this type of application seems far off now. Augmentation of strength, perhaps
reducible to mechanical design once appropriate control is established, seems much less challenging
by comparison. What seems most clear is that the pace of advancement in these areas is
accelerating. That BCI research will eventually transition from plasticity and repair to augmentation is
not in doubt. It is imperative that we think carefully about how and where, scientifically, this shift
should take place, and how we might best guide this process.
^ "WHO | Visual impairment and blindness
Emotiv Epoc "brain-wave" PC controller delayed until 2009
J. Vidal (1977). "Real-Time Detection of Brain Events in EEG". IEEE Proceedings 65: 633–