blue brain project info

7312019 Blue Brain Project Info

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Blue Brain Project

The Blue Brain Project is an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the

molecular levelThe aim of the project founded in May 2005 by the Brain and Mind Institute of the Eacutecole Polytechnique

Feacutedeacuterale de Lausanne (Switzerland) is to study the brains architectural and functional principles The project is headed by the

Institutes director Henry Markram Using a Blue Gene supercomputer running Michael Hiness NEURON software thesimulation does not consist simply of an artificial neural network but involves a biologically realistic model of neurons[1][2][not in

citation given ] It is hoped that it will eventually shed light on the nature of consciousness[citation needed ]There are a number of sub-

projects including the Cajal Blue Brain coordinated by the Supercomputing and Visualization Center of Madrid (CeSViMa)

and others run by universities and independent laboratories in the UK US and Israel

Goals

[edit]Neocortical column modelling

The initial goal of the project completed in December 2006[3] was the simulation of a rat neocortical column which can be

considered the smallest functional unit of the neocortex (the part of the brain thought to be responsible for higher functions such

as conscious thought) Such a column is about 2 mm tall has a diameter of 05 mm and contains about 60000 neurons inhumans rat neocortical columns are very similar in structure but contain only 10000 neurons (and 108 synapses) Between

1995 and 2005 Markram mapped the types of neurons and their connections in such a column

[edit]Whole brain simulation

A longer term goal is to build a detailed functional simulation of the physiological processes in the human brain It is not

impossible to build a human brain and we can do it in 10 years Henry Markram director of the Blue Brain Project said in 2009

at the TED conference in Oxford[4] In a BBC World Service interview he said If we build it correctly it should speak and have

an intelligence and behave very much as a human does[4]

[edit]Progress

In November 2007[5] the project reported the end of the first phase delivering a data-driven process for creating validating

and researching the neocortical column

By 2005 the first single cellular model was completed The first artificial cellular neocortical column of 10000 cells was built by

2008 By July 2011 a cellular mesocircuit of 100 neocortical columns with a million cells in total was built A cellular rat brain is

planned for 2014 with 100 mesocircuits totalling a hundred million cells Finally a cellular human brain is predicted possible by

2023 equivalent to 1000 rat brains with a total of a hundred billion cells[6][7]

Now that the column is finished the project is currently busying itself with the publishing of initial results in scientific literature

and pursuing two separate goals

1 construction of a simulation on the molecular leve l [1] which is desirable since it allows studying the effects of gene

expression

2 simplification of the column simulation to allow for parallel simulation of large numbers of connected columns with

the ultimate goal of simulating a whole neocortex (which in humans consists of about 1 million cortical columns)

[edit]Funding

The project is funded primarily by the Swiss government and secondarily by grants and some donations from private

individuals The EPFL bought the Blue Gene computer at a reduced cost because at that stage it was still a prototype and IBM

was interested in exploring how different applications would perform on the machine BBP was a kind of beta tester[8]

The project is a candidate for a Future and Emerging Technologies (FET) research grant from the European Commission The

grant would bring in euro1 billion over 10 years The final decision on the grant is expected in the second half of 2012 If the grant

is awarded the project will be renamed the Human Brain Project [9]



Cajal Blue Brain (Spain)

The Cajal Blue Brain[10] is coordinated by the Technical University of Madrid and uses the facilities of the Supercomputing and

Visualization Center of Madridand its supercomputer Magerit The Cajal Institute also participates in this collaboration The

main lines of research currently being pursued at Cajal Blue Brain include neurological experimentation and computer

simulations Nanotechnology in the form of a newly designed brain microscope plays an important role in its research plans[11]

Mind uploading

Whole brain emulation or mind uploading (sometimes called mind transfer) is the hypothetical process of transferring or

copying a conscious mind from a brain to a non-biological substrate byscanning and mapping a biological brain in detail and

copying its state into a computer system or another computational device The computer would have to run a simulation model

so faithful to the original that it would behave in essentially the same way as the original brain or for all practical purposes

indistinguishably[1] The simulated mind is assumed to be part of a virtual reality simulated world supported by an anatomic 3D

body simulation model Alternatively the simulated mind could be assumed to reside in a computer inside (or connected to)

a humanoid robot or a biological body replacing its brain

Whole brain emulation is discussed by futurists as a logical endpoint[1] of the topical computational

neuroscience and neuroinformatics fields both about brain simulation for medical research purposes It is discussed in artificial

intelligence research publications[2] as an approach to strong AI Among futurists and within the transhumanist movement it is

an important proposed life extensiontechnology originally suggested in biomedical literature in 1971[3] It is a central conceptual

feature of numerous science fiction novels and films

Whole brain emulation is considered by some scientists as a theoretical and futuristic but possible technology[1] although

mainstream research funders and scientific journals remain skeptical Several contradictory predictions have been made about

when a whole human brain can be emulated some of the predicted dates have already passed Substantial mainstream

research and development are however being done in relevant areas including development of faster super computers virtual

reality brain-computer interfaces animal brain mapping and simulation connectomics and information extraction from

dynamically functioning brains[4]

The question whether an emulated brain can be a human mind is debated by philosophers and may be viewed as impossible

by those who hold a dualistic view of the world which is common in many religions

[edit]Theoretical benefits

Overview



Neuron anatomical model

Simple artificial neural network

The human brain contains about 100 billion nerve cells called neurons each individually linked to other neurons by way of

connectors called axons anddendrites Signals at the junctures (synapses) of these connections are transmitted by the release

and detection of chemicals known as neurotransmitters The established neuroscientific consensus is that the human mind is

largely an emergent property of the information processing of this neural network

Importantly neuroscientists have stated that important functions performed by the mind such as learning memory and

consciousness are due to purely physical and electrochemical processes in the brain and are governed by applicable laws For

example Christof Koch and Giulio Tononi wrote in IEEE Spectrum

Consciousness is part of the natural world It depends we believe only on mathematics and logic and on the imperfectly

known laws of physics chemistry and biology it does not arise from some magical or otherworldly quality[5]

The concept of mind uploading is based on this mechanistic view of the mind and denies the vitalist view of human life and

consciousness

Many eminent computer scientists and neuroscientists have predicted that computers will be capable of thought and even

attain consciousness including Koch and Tononi[5] Douglas Hofstadter[6] Jeff Hawkins[6] Marvin Minsky[7] Randal A

Koene[8] and Rodolfo Llinas[9]

Such a machine intelligence capability might provide a computational substrate necessary for uploading

However even though uploading is dependent upon such a general capability it is conceptually distinct from general forms of

AI in that it results from dynamic reanimation of information derived from a specific human mind so that the mind retains a

sense of historical identity (other forms are possible but would compromise or eliminate the life-extension feature generally

associated with uploading) The transferred and reanimated information would become a form ofartificial intelligence

sometimes called an infomorph or nooumlmorph

Many theorists have presented models of the brain and have established a range of estimates of the amount of computing

power needed for partial and complete simulations[citation needed ] Using these models some have estimated that uploading may

become possible within decades if trends such asMoores Law continue[10]

The prospect of uploading human consciousness in this manner raises many philosophical questions involving identity

individuality and if the soul and mindcan be defined as the information content of the brain as well as numerous problems

of animal experiments medical ethics and morality of the process


Theoretical benefits

[edit]Immortalitybackup

Main article Digital immortality



In theory if the information and processes of the mind can be disassociated from the biological body they are no longer tied to

the individual limits and lifespan of that body Furthermore information within a brain could be partly or wholly copied or

transferred to one or more other substrates (including digital storage or another brain) thereby reducing or eliminating mortality

risk This general proposal appears to have been first made in the biomedical literature in 1971 by biogerontologist George M

Martin of the University of Washington[3]

[edit]Speedup

A computer-based intelligence such as an upload could potentially think much faster than a human even if it were no more

intelligent Human neurons exchange electrochemical signals with a maximum speed of about 150 meters per second whereas

the speed of light is about 300 million meters per second about two million times faster Also neurons can generate a

maximum of about 200 to 1000 action potentials or spikes per second whereas the number of signals per second in

modern[when ] computer chips is about 3 GHz[citation needed ] (about two million times greater) and expected to increase by at least a

factor 100 Therefore even if the computer components responsible for simulating a brain were not significantly smaller than a

biological brain and even if the temperature of these components was not significantly lower Eliezer Yudkowsky of

the Singularity Institute for Artificial Intelligence calculates a theoretical upper bound for the speed of a future artificial neural

network It could in theory run about 1 million times faster than a real brain experiencing about a year of subjective time in only

31 seconds of real time[11][12][13]

However in practice this massively parallel implementation would require separate computational units for each of the hundred

billion neurons and each of the hundred trillion synapses That requires an enormously large computer or artificial neural

network in comparison with todays super-computers[12] In a less futuristic implementation time-sharing would allow several

neurons to be emulated sequentially by the same computational unit Thus the size of the computer would be restricted but the

speedup would be lower Assuming that cortical minicolumns organized into hypercolumns are the computational units

mammal brains can be emulated by todays super computers but with slower speed than in a biological brain[14]

[edit]Space travel

Mind uploading poses potential benefits for interstellar space travel because it would allow immortal beings to travel the

cosmos without suffering from extreme acceleration A whole society of uploads can be emulated by a computer on a very

small spaceship that would consume much less energy than traditional space travels The uploads would have control of the

ship and would be able to make decisions about the crafts voyage in real time independent of signals from Earth that might

eventually take months or years to reach the craft as it journeys out into the cosmos Because a virtual conscious can be set

into a state of hibernation or slowed down the virtual minds need not experience the boredom of hundreds if not thousands of

years of travel Instead they would only awake when on board computers detected that the craft had arrived at its destination

Another hypothetical benefit is that in the unlikely event that the craft comes in contact with intelligent extra terrestrial life it

would be able to make rational decisions whether or not contact is feasible[citation needed ] In the book Omega point the author

suggests that the universe eventually would be colonialized by such machine intelligence

Another possibility for travel would be to transmit a mind via laser or via radio between two already inhabited locations Such

travel would require only the energy to transmit enough powerful signals so that they reach the target destination The travelers

experienced time from transmitter to receiver would be instantaneous

[edit]Multipleparallel existence

Another concept explored in science fiction is the idea of more than one running copy of a human mind existing at once Such

copies could potentially allow an individual to experience many things at once and later integrate the experiences of all

copies into a central mentality at some point in the future effectively allowing a single sentient being to be many places at

once and do many things at once this concept has been explored in fiction Such partial and complete copies of a sentient

being raise interesting questions regarding identity and individuality



[edit]Relevant technologies and techniques

Computational capacity

Advocates of mind uploading point to Moores law to support the notion that the necessary computing power is expected to

become available within a few decades However the actual computational requirements for running an uploaded human mind

are very difficult to quantify potentially rendering such an argument specious

Regardless of the techniques used to capture or recreate the function of a human mind the processing demands are likely to

be immense due to the large number of neurons in the human brain along with the considerable complexity of each neuron

In 2004 Henry Markram lead researcher of the Blue Brain Project has stated that it is not [their] goal to build an intelligent

neural network based solely on the computational demands such a project would have[15]

It will be very difficult because in the brain every molecule is a powerful computer and we would need to simulate the structure

and function of trillions upon trillions of molecules as well as all the rules that govern how they interact You would literally need

computers that are trillions of times bigger and faster than anything existing today[16]

Five years later after successful simulation of part of a rat brain the same scientist was much more bold and optimistic In

2009 when he was director of the Blue Brain Project he claimed that

A detailed functional artificial human brain can be built within the next 10 years [17]

Simulation model scale

Since the function of the human mind and how it might arise from the working of the brains neural network are poorly

understood issues mind uploading relies on the idea of neural network emulation Rather than having to understand the high-

level psychological processes and large-scale structures of the brain and model them using classical artificial

intelligencemethods and cognitive psychology models the low-level structure of the underlying neural network is captured

mapped and emulated with a computer system In computer science terminology rather than analyzing and reverse

engineering the behavior of the algorithms and data structures that resides in the brain a blueprint of its source code is

translated to another programming language The human mind and the personal identity then theoretically is generated by the

emulated neural network in an identical fashion to it being generated by the biological neural network

On the other hand a molecule-scale simulation of the brain is not expected to be required provided that the functioning of the

neurons is not affected byquantum mechanical processes The neural network emulation approach only requires that the

functioning and interaction of neurons and synapses are understood It is expected that it is sufficient with a black-box signal

processing model of how the neurons respond to nerve impulses (electrical as well aschemical synaptic transmission)

A sufficiently complex and accurate model of the neurons is required A traditional artificial neural network model for

example multi-layer perceptron network model is not considered as sufficient A dynamic spiking neural network model is

required which reflects that the neuron fires only when a membrane potential reaches a certain level It is likely that the modelmust include delays non-linear functions and differential equations describing the relation between electrophysical parameters

such as electrical currents voltages membrane states (ion channel states) and neuromodulators

Since learning and long-term memory are believed to result from strengthening or weakening the synapses via a mechanism

known as synaptic plasticity or synaptic adaptation the model should include this mechanism The response of sensory

receptors to various stimuli must also be modeled

Furthermore the model may have to include metabolism ie how the neurons are affected by hormones and other chemical

substances that may cross the blood-brain barrier It is considered likely that the model must include currently

unknown neuromodulators neurotransmitters and ion channels It is considered unlikely that the simulation model has to

include protein interaction which would make it computationally complex[1]



A digital computer simulation model of an analog system such as the brain is an approximation that introduces

random quantization errors and distortion However the biological neurons also suffer from randomness and limited precision

for example due to background noise The errors of the discrete model can be made smaller than the randomness of the

biological brain by choosing a sufficiently high variable resolution and sample rate and sufficiently accurate models of non-

linearities The computational power and computer memory must however be sufficient to run such large simulations

preferably in real time

[edit]Scanning and mapping scale of an individual

When modelling and simulating the brain of a specific individual a brain map or connectivity database showing the connections

between the neurons must be extracted from an anatomic model of the brain For whole brain simulation this network map

should show the connectivity of the whole nervous system including the spinal cord sensory receptors and muscle cells

Destructive scanning of a small sample of tissue from a mouse brain including synaptic details is possible as of 2010[18]

However if short-term memory and working memory include prolonged or repeated firing of neurons as well as intra-neural

dynamic processes the electrical and chemical signal state of the synapses and neurons may be hard to extract The uploaded

mind may then perceive a memory loss of the events and mental processes immediately before the time of brain scanning[1]

A full brain map would occupy less than 2 x 1016 bytes (20000 TB) and would store the addresses of the connected neurons

the synapse type and the synapse weight for each of the brains 1015 synapses[1][not in citation given ]

[edit]Serial sectioning

Serial sectioning of a brain

A possible method for mind uploading is serial sectioning in which the brain tissue and perhaps other parts of the nervous

system are frozen and then scanned and analyzed layer by layer which for frozen samples at nano-scale requires a cryo-

ultramicrotome thus capturing the structure of the neurons and their interconnections[19] The exposed surface of frozen nerve

tissue would be scanned and recorded and then the surface layer of tissue removed While this would be a very slow and labor

intensive process research is currently underway to automate the collection and microscopy of serial sections[20] The scans

would then be analyzed and a model of the neural net recreated in the system that the mind was being uploaded into

There are uncertainties with this approach using current microscopy techniques If it is possible to replicate neuron function

from its visible structure alone then the resolution afforded by a scanning electron microscope would suffice for such a

technique[20] However as the function of brain tissue is partially determined by molecular events (particularly at synapses but

also at other places on the neurons cell membrane) this may not suffice for capturing and simulating neuron functions It may

be possible to extend the techniques of serial sectioning and to capture the internal molecular makeup of neurons through theuse of sophisticated immunohistochemistry staining methods which could then be read via confocal laser scanning microscopy



However as the physiological genesis of mind is not currently known this method may not be able to access all of the

necessary biochemical information to recreate a human brain with sufficient fidelity

[edit]Brain imaging

It may also be possible to create functional 3D maps of the brain activity using advanced neuroimaging technology such

as functional MRI (fMRI for mapping change in blood flow)Magnetoencephalography (MEG for mapping of electrical

currents) or combinations of multiple methods to build a detailed three-dimensional model of the brain using non-invasive and

non-destructive methods Today fMRI is often combined with MEG for creating functional maps of human cortex during more

complex cognitive tasks as the methods complement each other Even though current imaging technology lacks the spatial

resolution needed to gather the information needed for such a scan important recent and future developments are predicted to

substantially improve both spatial and temporal resolutions of existing technologies[22]

[edit] Brain-computer interfaces

Brain-computer interface (BCI)

Brain-computer interfaces (BCI) (also known as neuro-computer interfaces direct neuron interfaces or cerebral interfaces)

constitute one of the hypothetical technologies for the reading of information in the dynamically functioning brain[citation needed ] The

production of this or a similar device may be essential to the possibility of mind uploading a living human subject

[edit]Current research

Mouse brain simulation

An artificial neural network described as being as big and as complex as half of a mouse brain was run on an IBM blue

gene supercomputer by a University of Nevada research team in 2007 A simulated time of one second took ten seconds of

computer time The researchers said they had seen biologically consistent nerve impulses flowed through the virtual cortex

However the simulation lacked the structures seen in real mice brains and they intend to improve the accuracy of the neuron

model[29]

Blue Brain is a project launched in May 2005 by IBM and the Swiss Federal Institute of Technology in Lausanne with the aim

to create a computer simulation of a mammalian cortical column down to the molecular level[30] The project uses

a supercomputer based on IBMs Blue Gene design to simulate the electrical behavior of neurons based upon their synaptic

connectivity and complement of intrinsic membrane currents The initial goal of the project completed in December

2006[31] was the simulation of a rat neocortical column which can be considered the smallest functional unit of

theneocortex (the part of the brain thought to be responsible for higher functions such as conscious thought) containing 10000

neurons (and 108 synapses) Between 1995 and 2005 Henry Markrammapped the types of neurons and their connections in

such a column In November 2007[32] the project reported the end of the first phase delivering a data-driven process for

creating validating and researching the neocortical column The project seeks to eventually reveal aspects of human cognition

and various psychiatric disorders caused by malfunctioning neurons such as autism and to understand how pharmacological

agents affect network behavior



An organization called the Brain Preservation Foundation was founded in 2010 and is offering a Brain Preservation Technology

prize to promote exploration of brain preservation technology in service of humanity The Prize currently $106000 will be

awarded in two parts 25 to the f irst international team to preserve a whole mouse brain and 75 to the first team to

preserve a whole large animal brain in a manner that could also be adopted for humans in a hospital or hospice setting

immediately upon clinical death Ultimately the goal of this prize is to generate a whole brain map which may be used in support

of separate efforts to upload and possibly reboot a mind in virtual space

[edit]Issues

Legal ethical political and economical issues

If simulated worlds would come true it may be difficult to ensure the protection of human rights For example social science

researchers might be tempted to secretly expose simulated minds or whole isolated societies of simulated minds to controlled

experiments in which many copies of the same minds are exposed (serially or simultaneously) to different test conditions

The only limited physical resource to be expected in a simulated world is the computational capacity and thus the speed and

complexity of the simulation Wealthy or privileged individuals in a society of uploads might thus experience more subjective

time than others in the same real time or may be able to run multiple copies of themselves or others and thus produce moreservice and become even more wealthy Others may suffer from computational resource starvation and show a slow

motion behavior

The development of reliable whole human brain emulation technology may require extensive and sometimes painful animal

experiments[citation needed ]

[edit]Copying vs moving

Another philosophical issue with mind uploading is whether an uploaded mind is really the same sentience or simply an exact

copy with the same memories and personality or indeed what the difference could be between such a copy and the original

(see the Swampman thought experiment) This issue is especially complex if the original remains essentially unchanged by the

procedure thereby resulting in an obvious copy which could potentially have rights separate from the unaltered obvious

original

Most projected brain scanning technologies such as serial sectioning of the brain would necessarily be destructive and the

original brain would not survive the brain scanning procedure But if it can be kept intact the computer-based consciousness

could be a copy of the still-living biological person It is in that case implicit that copying a consciousness could be as feasible

as literally moving it into one or several copies since these technologies generally involve simulation of a human brain in a

computer of some sort and digital files such as computer programs can be copied precisely It is usually assumed that once

the versions are exposed to different sensory inputs their experiences would begin to diverge but all their memories up until

the moment of the copying would remain the same

The problem is made even more serious by the possibility of creating a potentially infinite number of initially identical copies of

the original person which would of course all exist simultaneously as distinct beings The most parsimonious view of thisphenomenon is that the two (or more) minds would share memories of their past but from the point of duplication would simply

be distinct minds (although this is complicated by merging) Many complex variations are possible

Depending on computational capacity the simulation may run at faster or slower simulation time as compared to the elapsed

physical time resulting in that the simulated mind would perceive that the physical world is running in slow motion or fast

motion respectively while biological persons will see the simulated mind in fast or slow motion respectively

A brain simulation can be started paused backed-up and rerun from a saved backup state at any time The simulated mind

would in the latter case forget everything that has happened after the instant of backup and perhaps not even be aware that it

is repeating itself An older version of a simulated mind may meet a younger version and share experiences with it



[edit]Bekenstein bound

The Bekenstein bound is an upper limit on information that can be contained within a given finite region of space which has a

finite amount of energy or conversely the maximum amount of information required to perfectly describe a given physical

system down to the quantum level[33]

An average human brain has a weight of 15 kg and a volume of 1260 cm3 The energy (E = mmiddotc2) will be 134813middot1017 J and if

the brain is approximate to a sphere then the radius (V = 4middotπmiddotr 3 3) will be 670030middot10minus2 m

The Bekenstein bound (I le 2middotπmiddotrmiddotEħmiddotcmiddotln 2) for an average human brain would be 258991middot1042 bit and represents an upper

bound on the information needed to perfectly recreate the average human brain down to the quantum level This implies that

the number of different states (Ω=2I) of the human brain (and of the mind if the physicalism is true) is at most 10779640middot1041

However as described above many mind uploading advocates expect that quantum-level models and molecule-scale

simulation of the neurons will not be needed so the Bekenstein bound only represents a maximum upper limit

The hippocampus of a human adult brain has been estimated to store a limit of up to 25 petabyte of binary data equivalent[34]

[edit]Mind uploading in science fiction

Main article Mind uploading in fiction

[edit]Mind uploading advocates

Followers of Raeumllism advocate mind uploading in the process of human cloning to achieve eternal life Living inside of a

computer is also seen by followers as an eminent possibility[35]

However mind uploading is also advocated by a number of secular researchers in neuroscience and artificial intelligence such

as Marvin Minsky In 1993 Joe Strout created a small web site called the Mind Uploading Home Page and began advocating

the idea in cryonics circles and elsewhere on the net That site has not been actively updated in recent years but it has

spawned other sites including MindUploadingorg run by Randal A Koene PhD who also moderates a mailing list on the

topic These advocates see mind uploading as a medical procedure which could eventually save countless lives

Many transhumanists look forward to the development and deployment of mind uploading technology with transhumanists

such as Nick Bostrom predicting that it will become possible within the 21st century due to technological trends such

as Moores Law[1]

The book Beyond Humanity CyberEvolution and Future Minds by Gregory S Paul amp Earl D Cox is about the eventual (and to

the authors almost inevitable) evolution of computers into sentientbeings but also deals with human mind transfer Richard

Doyles Wetwares Experiments in PostVital Living deals extensively with uploading from the perspective of distributed

embodiment arguing for example that humans are currently part of the artificial life phenotype Doyles vision reverses the

polarity on uploading with artificial life forms such as uploads actively seeking out biological embodiment as part of their

reproductive strategy Raymond Kurzweil a prominent advocate of transhumanism and the likelihood of a technological

singularity has suggested that the easiest path to human-level artificial intelligence may lie in reverse-engineering the human

brain which he usually uses to refer to the creation of a new intelligence based on the general principles of operation of the

brain but he also sometimes uses the term to refer to the notion of uploading individual human minds based on highly detailed

scans and simulations This idea is discussed on pp 198 ndash203 of his book The Singularity is Near for example

In the basement of a university in Lausanne Switzerland sit four black boxes each about the size of a refrigerator and

filled with 2000 IBM microchips stacked in repeating rows Together they form the processing core of a machine that can

handle 228 trillion operations per second It contains no moving parts and is eerily silent When the computer is turned on the

only thing you can hear is the continuous sigh of the massive air conditioner This is Blue Brain



The name of the supercomputer is literal Each of its microchips has been programmed to act just like a real neuron in a real

brain The behavior of the computer replicates with shocking precision the cellular events unfolding inside a mind ldquoThis is the

first model of the brain that has been built from the bottom-uprdquo says Henry Markram a neuroscientist at Ecole Polytechnique

Feacutedeacuterale de Lausanne (EPFL) and the director of the Blue Brain project ldquoThere are lots of models out there but this is the only

one that is totally biologically accurate We began with the most basic facts about the brain and just worked from thererdquo

Before the Blue Brain project launched Markram had likened it to the Human Genome Project a comparison that some found

ridiculous and others dismissed as mere self-promotion When he launched the project in the summer of 2005 as a joint

venture with IBM there was still no shortage of skepticism Scientists criticized the project as an expensive pipedream a blatant

waste of money and talent Neuroscience didn‟t need a supercomputer they argued it needed more molecular biologists Terry

Sejnowski an eminent computational neuroscientist at the Salk Institute declared that Blue Brain was ldquobound to failrdquo for the

mind remained too mysterious to model But Markram‟s attitude was very different ldquoI wanted to model the brain because we

didn‟t understand itrdquo he says ldquoThe best way to figure out how something works is to try to build it from scratchrdquo

The Blue Brain project is now at a crucial juncture The first phase of the projectmdashldquothe feasibility phaserdquomdashis coming to a close

The skeptics for the most part have been proven wrong It took less than two years for the Blue Brain supercomputer to

accurately simulate a neocortical column which is a tiny slice of brain containing approximately 10000 neurons with about 30

million synaptic connections between them ldquoThe column has been built and it runsrdquo Markram says ldquoNow we just have to scale

it uprdquo Blue Brain scientists are confident that at some point in the next few years they will be able to start simulating an entire

brain ldquoIf we build this brain right it will do everythingrdquo Markram says I ask him if that includes selfconsciousness Is it really

possible to put a ghost into a machine ldquoWhen I say everything I mean everythingrdquo he says and a mischievous smile spreads

across his face

Henry Markram is tall and slim He wears jeans and tailored shirts He has an aquiline nose and a lustrous mop of dirty

blond hair that he likes to run his hands through when contemplating a difficult problem He has a talent for speaking in

eloquent soundbites so that the most grandiose conjectures (ldquoIn ten years this computer will be talking to usrdquo) are tossed off

with a casual air If it weren‟t for his bloodshot blue eyesmdashldquoI don‟t sleep muchrdquo he admitsmdashMarkram could pass for a European

playboy

But the playboy is actually a lab rat Markram starts working around nine in the morning and usually doesn‟t leave his office

until the campus is deserted and the lab doors are locked Before he began developing Blue Brain Markram was best known for

his painstaking studies of cellular connectivity which one scientist described to me as ldquobeautiful stuffhellipand yet it must have

been experimental hellrdquo He trained under Dr Bert Sakmann who won a Nobel Prize for pioneering the patch clamp technique

allowing scientists to monitor the flux of voltage within an individual brain cell or neuron for the first time (This involves

piercing the membrane of a neuron with an invisibly sharp glass pipette) Markram‟s technical innovation was ldquopatchingrdquo

multiple neurons at the same time so that he could eavesdrop on their interactions This experimental breakthrough promised

to shed light on one of the enduring mysteries of the brain which is how billions of discrete cells weave themselves into

functional networks In a series of elegant papers published in the late 1990s Markram was able to show that these electrical

conversations were incredibly precise If for example he delayed a neuron‟s natural firing time by just a few milliseconds the

entire sequence of events was disrupted The connected cells became strangers to one another

When Markram looked closer at the electrical language of neurons he realized that he was staring at a code he couldn‟t break ldquoI

would observe the cells and I would think bdquoWe are never going to understand the brain‟ Here is the simplest possible circuitmdash

just two neurons connected to each othermdashand I still couldn‟t make sense of it It was still too complicatedrdquo



Neuroscience is a reductionist science It describes the brain in terms of its physical details dissecting the mind into the

smallest possible parts This process has been phenomenally successful Over the last 50 years scientists have managed to

uncover a seemingly endless list of molecules enzymes pathways and genes The mind has been revealed as a Byzantine

machine According to Markram however this scientific approach has exhausted itself ldquoI think that reductionism peaked five

years agordquo he says ldquoThis doesn‟t mean we‟ve completed the reductionist project far from it There is still so much that we don‟t

know about the brain But now we have a different and perhaps even harder problem We‟re literally drowning in data We

have lots of scientists who spend their life working out important details but we have virtually no idea how all these details

connect together Blue Brain is about showing people the wholerdquo

In other words the Blue Brain project isn‟t just a model of a neural circuit Markram hopes that it represents a whole new k ind

of neuroscience ldquoYou need to look at the history of physicsrdquo he says ldquoFrom Copernicus to Einstein the big breakthroughs

always came from conceptual models They are what integrated all the facts so that they made sense You can have all the data

in the world but without a model the data will never be enoughrdquo

Markram has good reason to cite physicsmdashneuroscience has almost no history of modeling It‟s a thoroughly empirical

discipline rooted in the manual labor of molecular biology If a discovery can‟t be parsed into something observablemdashlike a line

on a gel or a recording from a neuronmdashthen generally it‟s dismissed The sole exception is computational neuroscience a

relatively new field that also uses computers to model aspects of the mind But Markram is dismissive of most computational

neuroscience ldquoIt‟s not interested enough in the biologyrdquo he says ldquoWhat they typically do is begin with a brain function they

want to modelrdquomdashlike object detection or sentence recognitionmdashldquoand then try to see if they can get a computer to replicate that

function The problem is that if you ask a hundred computational neuroscientists to build a functional model you‟ll get a

hundred different answers These models might help us think about the brain but they don‟t really help us understand it If you

want your model to represent reality then you‟ve got to model it onrealityrdquo

Of course the hard part is deciphering that reality in the first place You can‟t simulate a neuron until you know how a neuron is

supposed to behave Before the Blue Brain team could start constructing their model they needed to aggregate a dizzying

amount of data The collected works of modern neuroscience had to be painstakingly programmed into the supercomputer so

that the software could simulate our hardware The problem is that neuroscience is still woefully incomplete Even the simple

neuron just a sheath of porous membrane remains a mostly mysterious entity How do you simulate what you can‟t

understand

Markram tried to get around ldquothe mystery problemrdquo by focusing on a specific section of a brain a neocortical column in a two-

week-old rat A neocortical column is the basic computational unit of the cortex a discrete circuit of flesh that‟s 2 mm long and

05 mm in diameter The gelatinous cortex consists of thousands of these columnsmdasheach with a very precise purpose like

processing the color red or detecting pressure on a patch of skin and a basic structure that remains the same from mice to

men The virtue of simulating a circuit in a rodent brain is that the output of the model can be continually tested against the

neural reality of the rat a gruesome process that involves opening up the skull and plunging a needle into the brain The point is

to electronically replicate the performance of the circuit to build a digital doppelganger of a biological machine

Felix Schuumlrmann the project manager of Blue Brain oversees this daunting process He‟s 30 years old but looks even younger

with a chiseled chin lean frame and close-cropped hair His patient manner is that of someone used to explaining complex

ideas in simple sentences Before the Blue Brain project Schuumlrmann worked at the experimental fringes of computer science



developing simulations of quantum computing Although he‟s since mastered the vocabulary of neuroscience referencing

obscure acronyms with ease Schuumlrmann remains most comfortable with programming He shares a workspace with an

impressively diverse groupmdashthe 20 or so scientists working full-time on Blue Brain‟s software originate from 14 different

countries When we enter the hushed room the programmers are all glued to their monitors fully absorbed in the hieroglyphs

on the screen Nobody even looks up We sit down at an empty desk and Schuumlrmann opens his laptop

The computer screen is filled with what look like digitally rendered tree branches Schuumlrmann zooms out so that the branches

morph into a vast arbor a canopy so dense it‟s practically opaque ldquoThisrdquo he proudly announces ldquois a virtual neuron What

you‟re looking at are the thousands of synaptic connections it has made with other [virtual] neuronsrdquo When I look closely I can

see the faint lines where the virtual dendrites are subdivided into compartments At any given moment the supercomputer is

modeling the chemical activity inside each of these sections so that a single simulated neuron is really the sum of 400

independent simulations This is the level of precision required to accurately imitate just one of the 100 billion cellsmdasheach of

them uniquemdashinside the brain When Markram talks about building a mind from the ldquobottom-uprdquo these intracellular

compartments are the bottom They are the fundamental unit of the model

But how do you get these simulated compartments to act in a realistic manner The good news is that neurons are electrical

processors They represent information as ecstatic bursts of voltage just like a silicon microchip Neurons control the flow of

electricity by opening and closing different ion channels specialized proteins embedded in the cellular membrane When the

team began constructing their model the first thing they did was program the existing ion channel data into the supercomputer

They wanted their virtual channels to act just like the real thing However they soon ran into serious problems Many of the

experiments used inconsistent methodologies and generated contradictory results which were too irregular to model After

several frustrating failuresmdashldquoThe computer was just churning out craprdquo Markram saysmdashthe team realized that if they wanted to

simulate ion channels they needed to generate the data themselves

That‟s when Schuumlrmann leads me down the hall to Blue Brain‟s ldquowet labrdquo At first glance the room looks like a generic

neuroscience lab The benches are cluttered with the usual salt solutions and biotech catalogs There‟s the familiar odor of agar

plates and astringent chemicals But then I notice tucked in the corner of the room is a small robot The machine is about the

size of a microwave and consists of a beige plastic tray filled with a variety of test tubes and a delicate metal claw holding a

pipette The claw is constantly moving back and forth across the tray taking tiny sips from its buffet of different liquids I ask

Schuumlrmann what the robot is doing ldquoRight nowrdquo he says ldquoit‟s recording from a cell It does this 24 hours a day seven days a

week It doesn‟t sleep and it never gets frustrated It‟s the perfect postdocrdquo

The science behind the robotic experiments is straightforward The Blue Brain team genetically engineers Chinese hamster

ovary cells to express a single type of ion channelmdashthe brain contains more than 30 different types of channelsmdashthen they

subject the cells to a variety of physiological conditions That‟s when the robot goes to work It manages to ldquopatchrdquo a neuron

about 50 percent of the time which means that it can generate hundreds of data points a day or about 10 times more than an

efficient lab technician Markram refers to the robot as ldquoscience on an industrial scalerdquo and is convinced that it‟s the future of

lab work ldquoSo much of what we do in science isn‟t actually sciencerdquo he says ldquoI say let robots do the mindless work so that we can

spend more time thinking about our questionsrdquo



According to Markram the patch clamp robot helped the Blue Brain team redo 30 years of research in six months By analyzing

the genetic expression of real rat neurons the scientists could then start to integrate these details into the model They were

able to construct a precise map of ion channels figuring out which cell types had which kind of ion channel and in what density

This new knowledge was then plugged into Blue Brain allowing the supercomputer to accurately simulate any neuron anywhere

in the neocortical column ldquoThe simulation is getting to the pointrdquo Schuumlrmann says ldquowhere it gives us better results than an

actual experiment We get the same data but with less noise and human errorrdquo The model in other words has exceeded its

own inputs The virtual neurons are more real than reality

Every brain is made of the same basic parts A sensory cell in a sea slug works just like a cortical neuron in a human brain It

relies on the same neurotransmitters and ion channels and enzymes Evolution only innovates when it needs to and the neuron

is a perfect piece of design

In theory this meant that once the Blue Brain team created an accurate model of a single neuron they could multiply it to get a

three-dimensional slice of brain But that was just theory Nobody knew what would happen when the supercomputer began

simulating thousands of brain cells at the same time ldquoWe were all emotionally prepared for failurerdquo Markram says ldquoBut I

wasn‟t so prepared for what actually happenedrdquo

After assembling a three-dimensional model of 10000 virtual neurons the scientists began feeding the simulation electrical

impulses which were designed to replicate the currents constantly rippling through a real rat brain Because the model focused

on one particular kind of neural circuitmdasha neocortical column in the somatosensory cortex of a two-week-old ratmdashthe scientists

could feed the supercomputer the same sort of electrical stimulation that a newborn rat would actually experience

It didn‟t take long before the model reacted After only a few electrical jolts the artificial neural circuit began to act just like a

real neural circuit Clusters of connected neurons began to fire in close synchrony the cells were wiring themselves together

Different cell types obeyed their genetic instructions The scientists could see the cellular looms flash and then fade as the cells

wove themselves into meaningful patterns Dendrites reached out to each other like branches looking for light ldquoThis all

happened on its ownrdquo Markram says ldquoIt was entirely spontaneousrdquo For the Blue Brain team it was a thrilling breakthrough

After years of hard work they were finally able to watch their make-believe brain develop synapse by synapse The microchips

were turning themselves into a mind

But then came the hard work The model was just a first draft And so the team began a painstaking editing process By

comparing the behavior of the virtual circuit with experimental studies of the rat brain the scientists could test out the

verisimilitude of their simulation They constantly fact-checked the supercomputer tweaking the software to make it more

realistic ldquoPeople complain that Blue Brain must have so many free parametersrdquo Schuumlrmann says ldquoThey assume that we can

just input whatever we want until the output looks good But what they don‟t understand is that we are very constrained by

these experimentsrdquo This is what makes the model so impressive It manages to simulate a real neocortical columnmdasha functional

slice of mindmdash by simulating the particular details of our ion channels Like a real brain the behavior of Blue Brain naturally

emerges from its molecular parts

In fact the model is so successful that its biggest restrictions are now technological ldquoWe have already shown that the model can

scale uprdquo Markram says ldquoWhat is holding us back now are the computersrdquo The numbers speak for themselves Markram

estimates that in order to accurately simulate the trillion synapses in the human brain you‟d need to be able to process about



500 petabytes of data (peta being a million billion or 10 to the fifteenth power) That‟s about 200 times more information than

is stored on all of Google‟s servers (Given current technology a machine capable of such power would be the size of several

football fields) Energy consumption is another huge problem The human brain requires about 25 watts of electricity to

operate Markram estimates that simulating the brain on a supercomputer with existing microchips would generate an annual

electrical bill of about $3 billion But if computing speeds continue to develop at their current exponential pace and energy

efficiency improves Markram believes that he‟ll be able to model a complete human brain on a single machine in ten years or

less

For now however the mind is still the ideal machine Those intimidating black boxes from IBM in the basement are barely

sufficient to model a thin slice of rat brain The nervous system of an invertebrate exceeds the capabilities of the fastest

supercomputer in the world ldquoIf you‟re interested in computingrdquo Schuumlrmann says ldquothen I don‟t see how you can‟t be interested

in the brain We have so much to learn from natural selection It‟s really the ultimate engineerrdquo

Neuroscience describes the brain from the outside It sees us through the prism of the third person so that we are nothing

but three pounds of electrical flesh The paradox of course is that we don‟t experience our matter Self -consciousness at least

when felt from the inside feels like more than the sum of its cells ldquoWe‟ve got all these tools for studying the cortexrdquo Markram

says ldquoBut none of these methods allows us to see what makes the cortex so interesting which is that it generates worlds No

matter how much I know about your brain I still won‟t be able to see what you seerdquo

Some philosophers like Thomas Nagel have argued that this divide between the physical facts of neuroscience and the reality

of subjective experience represents an epistemological dead end No matter how much we know about our neurons we still

won‟t be able to explain how a twitch of ions in the frontal cortex becomes the Technicolor cinema of consciousness

Markram takes these criticisms seriously Nevertheless he believes that Blue Brain is uniquely capable of transcending the

limits of ldquoconventional neurosciencerdquo breaking through the mind-body problem According to Markram the power of Blue

Brain is that it can transform a metaphysical paradox into a technological problem ldquoThere‟s no reason why you can‟t get inside

Blue Brainrdquo Markram says ldquoOnce we can model a brain we should be able to model what every brain makes We should be able

to experience the experiences of another mindrdquo

When listening to Markram speculate it‟s easy to forget that the Blue Brain simulation is still just a single circuit confined

within a silent supercomputer The machine is not yet alive And yet Markram can be persuasive when he talks about his future

plans His ambitions are grounded in concrete steps Once the team is able to model a complete rat brainmdashthat should happen

in the next two yearsmdashMarkram will download the simulation into a robotic rat so that the brain has a body He‟s already

talking to a Japanese company about constructing the mechanical animal ldquoThe only way to really know what the model is

capable of is to give it legsrdquo he says ldquoIf the robotic rat just bumps into walls then we‟ve got a problemrdquo

Installing Blue Brain in a robot will also allow it to develop like a real rat The simulated cells will be shaped by their own

sensations constantly revising their connections based upon the rat‟s experiences ldquoWhat you ultimately wantrdquo Markram says

ldquois a robot that‟s a little bit unpredictable that doesn‟t just do what we tell it to dordquo His goal is to build a virtual animalmdasha

rodent robotmdash with a mind of its own



But the question remains How do you know what the rat knows How do you get inside its simulated cortex This is where

visualization becomes key Markram wants to simulate what that brain experiences It‟s a typically audacious goal a grand

attempt to get around an ancient paradox But if he can really find a way to see the brain from the inside to traverse our inner

space then he will have given neuroscience an unprecedented window into the invisible He will have taken the self and turned

it into something we can see

Schuumlrmann leads me across the campus to a large room tucked away in the engineering school The windows are hermetically

sealed the air is warm and heavy with dust A lone Silicon Graphics supercomputer about the size of a large armoire hums

loudly in the center of the room Schuumlrmann opens the back of the computer to reveal a tangle of wires and cables the knotted

guts of the machine This computer doesn‟t simulate the brain rather it translates the simulation into visual form The vast data

sets generated by the IBM supercomputer are rendered as short films hallucinatory voyages into the deep spaces of the mind

Schuumlrmann hands me a pair of 3-D glasses dims the lights and starts the digital projector The music starts first ldquoThe Blue

Danuberdquo by Strauss The classical waltz is soon accompanied by the vivid image of an interneuron its spindly limbs reaching

through the air The imaginary camera pans around the brain cell revealing the subtle complexities of its form ldquoThis is a

random neuron plucked from the modelrdquo Schuumlrmann says He then hits a few keys and the screen begins to fill with thousands

of colorful cells After a few seconds the colors start to pulse across the network as the virtual ions pass from neuron to neuron

I‟m watching the supercomputer think

Rendering cells is easy at least for the supercomputer It‟s the transformation of those cells into experience that‟s so hard Still

Markram insists that it‟s not impossible The first step he says will be to decipher the connection between the sensations

entering the robotic rat and the flickering voltages of its brain cells Once that problem is solvedmdashand that‟s just a matter of

massive correlationmdashthe supercomputer should be able to reverse the process It should be able to take its map of the cortex

and generate a movie of experience a first person view of reality rooted in the details of the brain As the philosopher David

Chalmers likes to say ldquoExperience is information from the inside physics is information from the outsiderdquo By shuttling

between these poles of being the Blue Brain scientists hope to show that these different perspectives aren‟t so different at all

With the right supercomputer our lucid reality can be faked

ldquoThere is nothing inherently mysterious about the mind or anything it makesrdquo Markram says ldquoConsciousness is just a massive

amount of information being exchanged by trillions of brain cells If you can precisely model that information then I don‟t

know why you wouldn‟t be able to generate a conscious mindrdquo At moments like this Markram takes on the def lating air of a

magician exposing his own magic tricks He seems to relish the idea of ldquodebunking consciousnessrdquo showing that it‟s no more

metaphysical than any other property of the mind Consciousness is a binary code the self is a loop of electricity A ghost will

emerge from the machine once the machine is built right

And yet Markram is candid about the possibility of failure He knows that he has no idea what will happen once the Blue Brain

is scaled up ldquoI think it will be just as interesting perhaps even more interesting if we can‟t create a conscious computerrdquo

Markram says ldquoThen the question will be bdquoWhat are we missing Why is this not enough‟rdquo

Niels Bohr once declared that the opposite of a profound truth is also a profound truth This is the charmed predicament of the

Blue Brain project If the simulation is successful if it can turn a stack of silicon microchips into a sentient being then the epic

problem of consciousness will have been solved The soul will be stripped of its secrets the mind will lose its mystery However

if the project failsmdashif the software never generates a sense of self or manages to solve the paradox of experiencemdashthen

neuroscience may be forced to confront its stark limitations Knowing everything about the brain will not be enough The



supercomputer will still be a mere machine Nothing will ha ve emerged from all of the information We will remain what can‟t

be known

The human brain has 100 billion neurons nerve cells that enable us to adapt quickly to an immense array of stimuli We use

them to understand and respond to bright sunlight a honking horn the smell of chicken frying and anything else our sensors

detect

To better understand some of those responses researchers in Lausanne Switzerland recently launched an ambitious projectcalled Blue Brain which uses IBMs eServer Blue Gene a supercomputer capable of processing 228 trillion floating pointoperations per second (TFLOPS) Blue Brain is modeling the behavior of 10000 highly complex neurons in rats neocorticalcolumns (NCC) which are very similar to the NCCs in a human brain The NCCs run throughout the brains gray matter andperform advanced computing They are 05mm in diameter and 2mm to 5mm in height and are arranged like the cells of ahoneycomb

The first objective of Blue Brain is to build an accurate software replica or template of an NCC within two to three years

says Henry Markram the principal researcher on Blue Brain and a professor at Ecole Polytechnique Federale de

Lausanne (EPFL) That first template will be modified for NCCs found in different brain regions and species and then all

the NCCs will be replicated to build a model of the neocortices of different species he says

Such models will shed light on how memories are stored and retrieved Markram says This could reveal many exciting

aspects of the [brain] circuits such as the form of memories memory capacity and how memories are lost

The modeling can help find vulnerabilities in the neocortex which is useful because thats where brain disorders often

originate We may also be able to work out the best way to compensate and repair circuit errors Markram says The

model could be used to develop and test treatment strategies for neurological and psychiatric diseases such as autism

schizophrenia and depression he adds

Having an accurate computer-based model of the brain would mean that some major brain experiments could be done in

silicon rather than in a wet lab A simulation that might take seconds on the supercomputer could replace a full days

worth of lab research Markram estimates Ultimately simulated results of brain activity could be matched with recorded

brain activity in a person with a disease in order to reverse-engineer the circuit changes in diseases he says

The real value of a simulation is that researchers can have access to data for every single neuron adds IBMs Charles

Peck head of the Blue Brain project for IBM Research

Although science knows a lot of details about the brain we do not know how the parts fit together and how they are

related to thought and learning and perception he says

Peck says Markrams team will take measurements from a dozen neurons that have been sliced from rat brains and



mounted on a chip The research will examine the physical structure and the electrical properties of each neuron and

how neurons affect one another

Peck says that a model of multiple NCCs is still far from a model of the whole brain Once we have modeled the

neocortex we will have to include models of other brain regions such as the basal ganglia hippocampus cerebellum

and so on he explains

The Blue Gene supercomputer was installed in July and the first simulations were run in August with a simulation of

25000 simple neurons that took just 60 seconds This was just not possible before and even smaller networks of 1000

neurons would take weeks to run on a cluster so this is truly a quantum leap in size and speed Markram says Future

simulations of 10000 complex neurons will take much longer

A special room was built for Blue Gene at the EPFL and the machine sits on top of a large room that holds the cooling

equipment and computer cables Markram says Ice-cold water from Lake Geneva is pumped in to support the cooling

system The actual computer takes up only a small space Markram notes and is only about the size of four

refrigerators running on four racks

Blue Gene is an 8096-processor supercomputer and it will model one to 10 neurons per processor The computer could

allow simulations of as many as 100 million simple neurons which is about half the number of neurons in a rat brain A

PFLOPS Blue Gene which IBM says is several years away would make it possible to simulate nearly a billion simple

neurons Markram says But improvements in processing speed and memory could mean the entire human brain couldbe simulated within a decade he adds

IBMs Ajay Royyuru head of Blue Gene computing as applied to life sciences says the supercomputers role is another

indication that biology [has become] information science

The scale of this computing will reveal interesting things in biology We need that scale to get at the complexity that

biological systems have he says And the trickle-down effect from Blue Brain to other computing projects in science and

industry will be enormous he adds

For example Markram says ASIC designs that emulate neuron network behavior might be developed for use in

information processing in intelligent devices And more generally he says that Blue Brain will teach lessons about real -

time data processing as opposed to off-line processing

Theres plenty we can learn and bring back Royyuru says of the Blue Brain project

Blue Brain Illuminating the Mind

Scientists will use the blazingly fast supercomputer to do never-before-possible research into how we think and how

mental disorders arise

On July 1 the Blue Brain computer will wake up marking a monumental moment in the history of brain research says



neuroscientist Henry Markram founder of the Brain Mind Institute at Switzerlands Ecole Polytechnique Feacutedeacuterale de Lausanne

(EPFL) The event could usher in a new era of scientific discoveries about the workings of the human mind The Blue Brain

computer is the latest installation of IBMs (IBM ) BlueGeneL system a radically new approach in supercomputer design

EPFLs machine has a peak speed of some 228 teraflops -- meaning it can theoretically spit out 228 trillion calculations every

second That blazing speed should put Blue Brain among the worlds top 15 supercomputers (The world champ is the

BlueGene system at Lawrence Livermore National Laboratory -- when finished later this year it will have a peak speed of 367

teraflops)

A UNIQUE FACILITY Markrams EPFL team collaborating with IBM researchers and an online network of brain and

computer scientists will use Blue Brain to create a detailed computer model of the neocortex the largest and most complex

part of the human brain Thats going to take two to three years he says

Then with a bigger Blue Brain he hopes to build a cellular-level model of the entire brain This may take a decade -- even with

IBMs next-generation system BlueGeneP Markram cant wait to get his hands on one of these number-crunching beasts

BlueGeneP will have faster processors and could ultimately reach petaflops speeds-- quadrillions of calculations per second

Were planning on a very long-term effort notes Markram Were creating a unique facility for researchers worldwide Adds

Charles Peck the IBM researcher who leads the Blue Brain effort at IBMs research division in Yorktown Heights NY

Theres now a tremendous opportunity to do some science that up to this point just hasnt been possible

THINKING MYSTERY The Blue Brain Project will search for novel insights into how humans think and remember Plus by by

running accurate simulations of brain processes well be able to investigate questions about psychiatric disorders and howthey arise Markram says Scientists believe that autism schizophrenia depression and other psychological problems are

caused by defective or malfunctioning circuitry in the brain

Parkinsons disease is another target adds Markram Theres a group of cells deep down in the mid-brain that produce

dopamine and when these cells begin to die and dopamine production decreases you get Parkinsons he explains Well be

able to mimic this creating simulations that should make Blue Brain an invaluable tool for drug-company researchers on the

track of treatments or cures for Parkinsons

Learning how the brain works has been one of sciences great challenges Researchers still dont have a holistic grasp of how

we think One reason Most research so far has been conducted with wet experiments -- stimulating or dissecting the brains of

mice rats and other animals Markram notes that some wet-lab experiments are incredibly complicated taking up to three

years and costing $1 million

With simulations on Blue Brain he predicts well be able to do that same work in days maybe seconds Its going to beabsolutely phenomenal

CONSTANTLY CHANGING CIRCUITRY Markram first broached the idea of a BlueGene-based collaboration five years ago

right after IBM unveiled the supercomputer system Even before that Henry had been wanting to go down this path of

computer simulations says IBMs Peck But only now is it actually feasible

Thats because the brain is so extraordinarily complex that an enormously powerful computer is required The brains physical

structure and electrochemical operations are very intricate Complicating things still further is its constantly changing internal

circuitry The brain is in a very different state in the morning when you wake up than it is at noontime Markram points out

Fifty years ago he notes we believed that memories were somehow hardwired into the brain But our lab [EPFLs Laboratory

of Neural Microcircuitry] has been one of the main propagators of a new theory in which the brain is incredibly fluid Its

restructuring itself continuously -- self-organizing and reorganizing all the time

HUGE SIMULATION If brain circuitry is in a constant state of flux Markram insists that long-term memories cant be

permanent hardwired fixtures To explain how memories are preserved he and his colleagues cooked up the liquid-

computing theory Validating this concept with Blue Brain he hints might point to new types of silicon circuits that perform new

and more-complex functions -- which IBM could use to build a revolutionary brain-like computer

Thats a possibility says Tilak Agerwala a vice-president at IBM Research But were still very far from understanding how

the brain works so its much too early to know if we should build computers that way However the notion already has a fancy

moniker biometaphorical computing

For now Markram sees the BlueGene architecture as the best tool for modeling the brain Blue Brain has some 8000

processors and by mapping one or two simulated brain neurons to each processor the computer will become a silicon replica

of 10000 neurons Then well interconnect them with the rules [in software] that weve worked out about how the brain

functions says Markram

The result will be a full-fledged model of 10000 neurons jabbering back and forth -- a simulation 1000 times larger than any

similar model to date



FANTASTIC ACCELERATION This setup will form the foundation for studying neocortical columns -- the building blocks of

the cortex and the part of the brain that differentiates mammals from other animals Each column is a bundle of networked

neurons and is roughly 12 millimeter in diameter and 2 millimeters long Thats only about the size of a pinhead Markram

notes But packed inside are 50000 neurons and more than 5 kilometers [3 miles] of wiring he marvels

The neocortical column is the beginning of intelligence and adaptability Markram adds It marks the jump from reptiles to

mammals When it evolved it was like Mother Nature had discovered the Pentium chip he quips -- the circuitry was sosuccessful that its just duplicated with very little variation from mouse to man In the human cortex there are just more cortical

columns -- about 1 million

Since the neocortical column was first discovered 40 years ago researchers have been painstakingly unraveling how it helps

perform the miracles of thought that enable humans to be creative inventive philosophical creatures Thats been my passion

my mission for 10 years says Markram Now we know how information is transferred form one neuron to another We know

how they behave -- what they do and whom they talk to Weve actually mapped that out

Next that knowledge will be transferred into a torridly fast silicon simulator Blue Brain promises a fantastic acceleration in brain

research It could be as dramatic as the leap from chiseling numbers in Sumerian clay tablets 2500 years ago to crunching

them in modern computers And the Blue Brain Project just might culminate in a new breed of supersmart computers that will

make even BlueGeneL seem like a piker

Blue Brain Reversing Engineering the Human Brain to Figure Out How it Works Through Simulation

Kevin Klues

Web page httpwwweecsberkeleyedu~klueska

Bio and Interests Im a first year grad student working in the parlab with professors Eric Brewer and John Kubiatowicz In a past life Iworked in the area of distributed sensor networks on the design and implementation of the TinyOS operating system -- specifically on its

resource and energy management subsystems Now my focus is on the design and implementation of a new operating system for manycore

Specificially Im interested in figuring out how to structure the OS to provide parallel applications a flexible efficient framework within

which to express their parallelism

Class Goal Id like to obtain a deeper understanding of exactly what goes into the design and implement of parallel applications Thisincludes not just the structure of the code itself but also on the runtime behaviour of such applications as it influences the design of the OS

services that should be provided to them

Overview

The Blue Brain project begun in May 2005 is renouned as the first

comprehensive attempt to create a computer simulation of the

mammalian brain down to the molecular level The Blue Brain project

is NOT an attempt to create an artifical brain It is not an artificial

intelligence project at all in fact The Blue Brain Project is focused

exclusively on creating a physiological simulation for biomedical

applications



As the name suggests the software running simulations

for Blue Brain is spread accross an array of Blue Gene

supercomputers SGI Prism machines as well as a fewcommodity off the shelf PCs These simulations are run

within the MPI-based Neocortical Simulator

(NCS)developed at the University of Nevada Reno and a

variation of theNEURON software developed at Yale A

high level overview of the software architecture can be

seen in the figure to the right

While the Blue Gene supercomputer used to run these simulations is blazingly fast (ranked in the top 5 on the top 500 list) it is only justenough to really get the project rolling Simulations of about 100 million simple neurons are possible with the current computing power but

only 50000 fully complex neurons are possible at anything close to real-time (of which there are billions in the human brain)

Simulations are based on a complex understanding of the anatomical structures that make up the

brain combined with actual electrical recordings of the neurons and the synaptic pathways that

make up the microcircuit of the brain At the end of 2006 the Blue Brain project had created a model

of the basic functional unit of the brain the neocortical column At the push of a button the model

could reconstruct biologically accurate neurons based on detailed experimental data and

automatically connect them in a biological manner a task that involves positioning around 30 million

synapses in precise 3D locationsBelow is an actual a fly through of a running simulation of the

Neocortical Column of a rat based on such data

In November 2007 the Blue Brain project reached an important milestone and the conclusion of its first Phase with the announcement of an entirely new data-driven process for creating validating and researching the neocortical column

Until now all simulations have been performed at the neuron level The next steps of the project include the construction of a simulation atthe actual molecular level There are also plans to simplify the column simulation to allow for parallel simulation of large numbers of

connected columns Following this kind of structure a simulation of the entire neocortex will finally be possible (which in humans consists

of about 1 million cortical columns)

Resources



Cajal Blue Brain (Spain)

The Cajal Blue Brain[10] is coordinated by the Technical University of Madrid and uses the facilities of the Supercomputing and

Visualization Center of Madridand its supercomputer Magerit The Cajal Institute also participates in this collaboration The

main lines of research currently being pursued at Cajal Blue Brain include neurological experimentation and computer

simulations Nanotechnology in the form of a newly designed brain microscope plays an important role in its research plans[11]

Mind uploading

Whole brain emulation or mind uploading (sometimes called mind transfer) is the hypothetical process of transferring or

copying a conscious mind from a brain to a non-biological substrate byscanning and mapping a biological brain in detail and

copying its state into a computer system or another computational device The computer would have to run a simulation model

so faithful to the original that it would behave in essentially the same way as the original brain or for all practical purposes

indistinguishably[1] The simulated mind is assumed to be part of a virtual reality simulated world supported by an anatomic 3D

body simulation model Alternatively the simulated mind could be assumed to reside in a computer inside (or connected to)

a humanoid robot or a biological body replacing its brain

Whole brain emulation is discussed by futurists as a logical endpoint[1] of the topical computational

neuroscience and neuroinformatics fields both about brain simulation for medical research purposes It is discussed in artificial

intelligence research publications[2] as an approach to strong AI Among futurists and within the transhumanist movement it is

an important proposed life extensiontechnology originally suggested in biomedical literature in 1971[3] It is a central conceptual

feature of numerous science fiction novels and films

Whole brain emulation is considered by some scientists as a theoretical and futuristic but possible technology[1] although

mainstream research funders and scientific journals remain skeptical Several contradictory predictions have been made about

when a whole human brain can be emulated some of the predicted dates have already passed Substantial mainstream

research and development are however being done in relevant areas including development of faster super computers virtual

reality brain-computer interfaces animal brain mapping and simulation connectomics and information extraction from

dynamically functioning brains[4]

The question whether an emulated brain can be a human mind is debated by philosophers and may be viewed as impossible

by those who hold a dualistic view of the world which is common in many religions


Overview















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Kevin Klues








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[edit]Speedup

















[edit]Space travel
































































































[edit]Brain imaging



















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Resources








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[edit]Space travel
































































































[edit]Brain imaging



















model[29]




















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as Moores Law[1]




































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Kevin Klues








Overview







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[edit]Issues








motion behavior








original











































as Moores Law[1]




































across his face





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Kevin Klues








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Resources



























as Moores Law[1]




































across his face





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teraflops)






























































Kevin Klues








Overview







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Resources






















across his face





playboy











































understand






























































































less







































































be known



detect





























































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Kevin Klues








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Resources





























understand






























































































less







































































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Kevin Klues








Overview







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be known



detect





























































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Kevin Klues








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teraflops)






























































Kevin Klues








Overview







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teraflops)






























































Kevin Klues








Overview







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Kevin Klues








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Resources

blue brain project info

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