4th International Conference on System Modeling & Advancement in Research Trends (SMART)
College of Computing Sciences and Information Technology (CCSIT) ,Teerthanker Mahaveer University , Moradabad
[2015]
VIRTUAL BRAIN
Bringing Blue Brain Advance Technology To Life
Dr. Ambuj Kumar Agarwal1, Shruti Shukla2
1
Associate Professor, College of Computing Science and Information Technology,
Teerthanker Mahaveer University Moradabad, India
2
Department of Biomedical Engineering-B.Tech Graduate (BME), Babu Banarsi Das-Northern India
Engineering College, BBD City, Faizabad Road, Lucknow, Uttar Pradesh 226028
1
ambuj4u@gmail.com
shrutishukla.281290@gmail.com
2
Abstract— Famously known as the world’s first virtual brain,
“BLUE BRAIN” is a very appropriate application of an artificial
intelligence human brain. That means a machine can function as
human brain. It’s a known fact that human does not live for a
decade but the information contained in his mind could certainly
be stored for a decade with this technology. So with advancement
in technology, even after a person is dead, the virtual brain will
serve as the man. Therefore, the main idea behind this is
uploading human brain into machine. Hence this research paper
consists of the concepts of Blue Brain, its requirements, Blue
Brain project, strategies undertaken to build a Blue Brain,
advantages and disadvantages and many more.
Keywords— Artificial Brain, Simulation, Nanobots,Neuron
I.
INTRODUCTION
II.
WHAT IS BLUE BRAIN?
Although it’s very clear by the general introduction
of what Blue brain is. So, to define Blue brain, it
can be said that it is like uploading a mind in a
computer. That is, it is a concept or technology or
system which allows transferring all the contents of
a human brain into a virtual brain that resides inside
a Super computer, known as Blue Gene.
Now, How is it possible? This could be explained if
a series of steps is followed carefully. An
interesting paper on this topic describing both
invasive and noninvasive techniques has been
provided by Raymond Kurzweil, suggesting the use
of nanobots (very small robots). These robots being
small enough will travel throughout our circulatory
system proceeding towards the spine and brain, and
will monitor the activity and structure of our CNS.
They could scan the structure of how our brain is
made, making it easier and viewable for us about all
the connections between each neuron while
recording the current state of the brain. This
information can be entered immediately into a
computer which results into functioning of the
machine as a human brain. But for such operation
computer having really large storage space and
processing power will be required.
An artificial brain means the one that is able to
think, process, memorise, store and respond. The
technology helpful in this activity is Blue Brain,
and scientists today are in this direction to create
one. The pioneer of Blue Brain Project is Henry
Markram at EPFL in Lausanne, Switzerland. He
founded the project in May, 2005. The aim of this
project is to study architectural and functional
principles of a brain as well as its construction in a
super computer. Under a microscope and using
patch clamp electrodes, living tissues of brains are
critically examined.
All the data with this study is collected about
different neuron types which is then used to build
III. NATURAL BRAIN V/S SIMULATED BRAIN
biologically authentic models of neurons. The
simulations are carried out on a supercomputer Before even getting started with Blue Brain
known as ‘Blue Gene’ built by IBM, and from building, it is extremely important to know how
natural brain works in contrast to simulated brain.
where comes the name "Blue Brain".
And to better understand this, below is provided a
tabular difference between the operational function
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4th International Conference on System Modeling & Advancement in Research Trends (SMART)
College of Computing Sciences and Information Technology (CCSIT) ,Teerthanker Mahaveer University , Moradabad
[2015]
of the two, taking into account all their points, i.e.
input given, how it is interpreted, stored in memory
producing output and the processing.
TABLE: COMPARISON BETWEEN NATURAL BRAIN AND SIMULATED BRAIN
Natural
Brain
Simulated Brain
INPUT
Natural neurons
responsible for conveying
message in nervous
system using electric
impulses.
INPUT
Artificial neurons created using
silicon chips are used and
messages are transferred using
sensory cells.
INTERPRETATION
Received electric impulses
are interpreted in the
brain.
INTERPRETATION
Using registers, the received
impulses are interpreted by
artificial/virtual brain.
OUTPUT
The response after the
interpretation is sent by
the brain in the form of
electric pulses to sensory
cells.
OUTPUT
States of register means
different states of brain , and
based on them, output signals
are provided to artificial
neurons in the body.
MEMORY
Some neurons
permanently store
information or data and
this way whenever
required, it can be easily
fetched.
MEMORY
Secondary memory makes it
possible to serve the same
purpose storing data
permanently which can later be
obtained whenever needed.
PROCESSING
Implementing decision
making through past
experience, any logics
applied that are already
stored can be used along
with states of neurons to
alter & produce the output.
PROCESSING
Implementing decision making
becomes easier for the machine
and computer can easily take
decisions and perform any
logics & computation using
stored past experience giving
the output.
Fig 1: Neuron Anatomical Model
Fig 2: Simple Artificial Neural Network
IV.
Steps To Building A Blue Brain
There are three main steps:A. Data collection
B. Data simulation
C. Visualization
A. Data collection:
It involves microscopic study of the shape and
electrical behavior of each neuron by using slices of
living brain. These neurons lie within the cerebral
cortex, and their population density. A 12 patch
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4th International Conference on System Modeling & Advancement in Research Trends (SMART)
College of Computing Sciences and Information Technology (CCSIT) ,Teerthanker Mahaveer University , Moradabad
clamp instrument is used for the study of
electrophysiological behavior of neuron, and this
very instrument forms the foundation of the
research and was developed as the tool for only this
project. It is implemented by concurrently patching
twelve living neurons and recording their electrical
activity. The observations obtained with this are
converted into accurate algorithms defining the
whole process, alignment of neurons and operations
generating biologically-original appearing virtual
neurons prepared for the next step, i.e. simulation.
Fig 3: The 12 patch clamp(close up view)
Data simulation:
In the 1990s, a software package known as
NEURON was developed by Michael Hines. This is
used for neural simulations. It is written in
languages like C, C++, and FORTRAN. The
current version at which software is working is 7.2
and it is still under development.
Data Simulation has two major aspects:
 Simulation speed
 Simulation workflow
1)
Simulation speed- Simulations of one cortical column
(more than 10,100 neurons) run about two hundred times
slower than real time. It takes about five minutes to complete
one second of stimulated time. And display unevenly line
scaling. It might be possible to trim components in order to
improve performance, if the biological validity is understood.
The simulation timestep varies as it is 0.025 ms for numerical
integrations and 0.1 ms for writing the output to the disk.
[2015]
millions of proteins and each protein is simulated. First a body
or structure of network is built using all the different kinds of
synthesized neurons. After this, cells are connected with
experimentally defined rules. And, finally the neurons become
functional and the simulation is achieved.
The blueprints showing the changing behavior of neurons are
seen via visualization software. Every two weeks a column
model is run; column here is cortical column that is the basic
unit of cerebral cortex and each of them can be mapped into
one function. The results that are seen in living neurons are
simulations causing to reproduce serving our ultimate aim.
Fig 4: NEURON cell builder window
3)
BBP-SDK- Abbreviated as Blue Brain Project Software Development Kit, it is a set of software classes that
allows researchers to examine models and simulations and
use them. The software kit is a C++ library enfolded in Java
and Python.
B.
Visualization:
1)
RT Neuron: RT Neuron is the main application that
Blue Brain Project uses for visualization of neural simulations.
It is a software specifically written for neural simulations not
generalizable to other kinds of simulation. The output is
obtained from Hodgkin-Huxley simulations as input in
NEURON and is produced in 3D, making it visible to
researchers and programmers as potentials activated propagate
through or within the neurons. The researchers can then
interact with the model since the animations can be paused,
stopped, started and zoomed .A 32-processor Silicon Graphics
Inc. (SGI) system with 300 Gb of shared memory is used for
visualization of results.
2)
Simulation overflow- Main work of this step is to
make virtual cells use the algorithms, written to define the real
neurons. According to the characteristics of the stage species
like their age, type and disease that it has, of the animal is
being simulated. In a single cell, there are hundreds of
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4th International Conference on System Modeling & Advancement in Research Trends (SMART)
College of Computing Sciences and Information Technology (CCSIT) ,Teerthanker Mahaveer University , Moradabad
Fig 6: Outer view of processing system of Blue
fig 5: Visualization of neuron(RT Neuron)
V.
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Gene/P
F
HARDWARE/COMPUTER USED
The hardware used is a BlueGene supercomputer. It
is built by IBM and is installed on the EPFL
campus in Lausanne, Switzerland managed by
CADMOS(Center for Advanced Modeling Science).
1. Blue Gene/L(till 2009)
2. Blue Gene/P(upgraded from Blue Gene/L and
was in use till 2011)
3. JuQUEEN(Blue Gene/Q, upgraded from Blue
Gene/P in 2012 with more racks and currently
performs at more than 1.7 Petaflops)
Fig 7: JuQUEEN(Blue Gene/Q) installed at Julich Research Center in
Germany
A. Technical Specifications: 4096 quad-core nodes
 Each core is a PowerPC 450, 850 MHz

Total- 56 teraflops, 16 terabytes of memory

1 PB disk space, GPFS parallel file system
 Operating system: Linux SuSE SLES 10
 4 racks, 1 row, wired as 16*16*16 3D torus
Fig 8: Blue Brain Storage Hierarchy
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VI.
4th International Conference on System Modeling & Advancement in Research Trends (SMART)
College of Computing Sciences and Information Technology (CCSIT) ,Teerthanker Mahaveer University , Moradabad
ADVANTAGES, DISADVANTAGES and
APPLICATIONS
Advantages
1. A person can
remember and recollect
anything without any
effort.
2. Decision can be
made by the computer
by itself without any
external help.
3. The activity of
different animals could
be understood easily.
4. Helpful for a deaf
person & for many
psychological
disorders, as they can
easily get any
information through
this.
Disadvantages
1. Increased risk of
dependency of a person on
Blue Brain technology, all
the time.
2. Susceptible to higher
forms of risks and critical
threats, like hacking issues
& computer viruses etc.
That means, when a
machine becomes so
intelligent, it could use his
brain against him and it
may cause war between
machine and the man.
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In 2009, a more advanced version of Blue Gene
was used. With it, 100 interconnected columns were
stimulated by 2012 . And in April, same year, FET
flagships one year pilot phase was completed. By
2014, entire rat brain neocortical cellular level
simulation was achieved. So, until now, all
simulations have been performed at the neuron
level. A simulation at the actual molecular level is
on the way now. And by 2020, it is hoped that
Exascale simulations would be started on DEEP
Cluster-Booster prototype at Julich. Following this
kind of structure, by 2023, entire human brain’s
simulation will finally be possible (that is, the one
containing about 1 million cortical columns) ,
offcourse if needed funding is provided.
VIII.
CONCLUSION
To conclude this journal research paper, it can be
said that focusing on preserving the original vision
of reconstruction and simulation of the brain, this
project promises to have a profound impact on
neuroscience, neuroinformatics, neurorobotics &
By including molecular-level simulation, blue brain high performance computing. Although, it’s
project could be used for determining the effects of potential goes far beyond the limitations of
new pharmaceutical compounds on virtual brain of neurobiology and above mentioned fields as
any specie of any age, & stage of diseases. It also transforming whole human brain into a
hopes to build a better and bigger platform for computational machine that processes on multi
experimenting by neuroscientists. Besides these, scales is way beyond exceptional. Understanding
there are various other applications, viz.
the natural brain’s biological functioning through a
1. Hundreds of year’s data can be gathered and
virtual brain will not only make it easier for people
tested.
with psychological disorders and other brain
2. Neural Code could be cracked.
diseases but will also benefit the other areas of
3. Foundational model for whole brain simulations. science. And one of the important things to
4. Detection and curing of brain disorders.
remember is to make use of connectivity available
5. Becoming accessible to all.
to other scientists(with the use of BBP-SDK,
6. Focusing to create physiological simulations for
already mentioned in the paper) and also provide
biomedical simulations.
the infrastructure to enable several applications
mentioned.
VII.
RELATED WORK
IX.
ACKNOWLEDGMENT
Founded in 2005, the Blue Brain project was
I would like to thank Associate Professor, Dr. Ambuj Agrawal
for providing with the relevant information and support.
initiated by integrating all the relevant data into a
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4th International Conference on System Modeling & Advancement in Research Trends (SMART)
College of Computing Sciences and Information Technology (CCSIT) ,Teerthanker Mahaveer University , Moradabad
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[2015]
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