I have often wondered what parts of the brain interact with each other… Are there areas in the neural net that only directly link to others via hardwired links through neurone structures i.e. via axion and dendrite structural linkages, while indirectly effecting the overall patterns of other physically unconnected areas, via the release the of chemical signals? Do some areas remain completely independent of one another and operate as distinct control areas that regulate other critical functions of the Central Nervous System (CNS)? I mean, I’ve already proposed an idea as to how our brains might well use fractal/chaotic dynamics to modify behavioural patterns within our minds – so as to ensure survival of our biological bodies – by smashing through predefined, repetitive modes of behaviour, thus elucidating a fairly erratic and highly unusual modified behaviour. But, to date, this has only been based on observations and insinuations about behavioural modifications noted by other scientists.
But just the other day I Stumbled over this amazing article… One that seems to suggest that answering the questions I have been pondering over these last few years, while in various states of meditation, psychedelic inebriation, metaphysical wondering and simply while walking around Dunorlan Park most evenings, are closer to hand than I had previously thought.
IBM Scientists Create Most Comprehensive Map Of The Brain’s Network
The Proceedings of the National Academy of Sciences (PNAS) published Tuesday a landmark paper entitled “Network architecture of the long-distance pathways in the macaque brain” (an open-access paper) by Dharmendra S. Modha (IBM Almaden) and Raghavendra Singh (IBM Research-India) with major implications for reverse-engineering the brain and developing a network of cognitive-computing chips.
“We have successfully uncovered and mapped the most comprehensive long-distance network of the Macaque monkey brain, which is essential for understanding the brain’s behavior, complexity, dynamics and computation,” Dr. Modha says. “We can now gain unprecedented insight into how information travels and is processed across the brain.
“We have collated a comprehensive, consistent, concise, coherent, and colossal network spanning the entire brain and grounded in anatomical tracing studies that is a stepping stone to both fundamental and applied research in neuroscience and cognitive computing.”
The scientists focused on the long-distance network of 383 brain regions and 6,602 long-distance brain connections that travel through the brain’s white matter, which are like the “interstate highways” between far-flung brain regions, he explained, while short-distance gray matter connections (based on neurons) constitute “local roads” within a brain region and its sub-structures.
Their research builds upon a publicly available database called Collation of Connectivity data on the Macaque brain (CoCoMac), which compiles anatomical tracing data from over 400 scientific reports from neuroanatomists published over the last half-century.
“We studied four times the number of brain regions and have compiled nearly three times the number of connections when compared to the largest previous endeavor,” he pointed out. “Our data may open up entirely new ways of analyzing, understanding, and, eventually, imitating the network architecture of the brain, which according to Marian C. Diamond and Arnold B. Scheibel is “the most complex mass of protoplasm on earth—perhaps even in our galaxy.”
The center of higher cognition and consciousness?
The brain network they found contains a “tightly integrated core that might be at the heart of higher cognition and even consciousness … and may be a key to the age-old question of how the mind arises from the brain.” The core spans parts of premotor cortex, prefrontal cortex, temporal lobe, parietal lobe, thalamus, basal ganglia, cingulate cortex, insula, and visual cortex.
Prefrontal cortex: integrator-distributor of information
By ranking brain regions (similar to how search engines rank web pages), they found evidence that the prefrontal cortex, while physically located in the front of the brain, is a functionally central part of the brain that might act as an integrator and distributor of information. Think of it as a switchboard.
As they stated in the PNAS paper, “The network opens the door to the application of large-scale network-theoretic analysis that has been so successful in understanding the Internet, metabolic networks, protein interaction networks, various social networks, and in searching the world-wide web. The network will be an indispensable foundation for clinical, systems, cognitive, and computational neurosciences as well as cognitive computing.”
The findings will also help them design the routing architecture for a network of cognitive computing chips, they suggest.
The research was sponsored by the Defense Advanced Research Projects Agency, Defense Sciences Office, Program: Systems of Neuromorphic Adaptive Plastic Scalable Electronics.
Dr. Modha presented the exciting findings of this study in a talk I attended at the Toward A Science Of Consciousness conference in Tucson in April, but he asked us to hold off on covering this until the formal paper appeared in a peer-reviewed journal.
A detailed Powerpoint slide show with voice narration (60 slides, ~52 minutes, ~50 MB) is downloadable here.
by Amara D. Angelica
I like the author’s comparison to the “Mandala Of The Mind.” Could this reference be a coincidental incident relating to the Sanskrit word Mandala, which means circle? Certainly the psychoanalyst Carl Gustav Jung saw the mandala as “a representation of the unconscious self,” and believed his paintings of mandalas, which he made after patient contact, enabled him to identify emotional disorders within his subject and work towards developing a wholeness in their personality. But could these “scientific” studies demonstrate a clarity of understanding that allows mankind to understand his/her own basic behavioural tendencies in relation to the way we perceive reality?
This is something I will discuss further when I come to discussing what I have uncovered while studying the idea of the “Self.”
To find out where I sourced this article from, please click here.
To find out more about the author of this article, please click here
And to read more about Dharmendra S. Modha’s amazing work on mapping of our primate neural net, please click here.
October 17, 2009
Not too long ago I discussed how Henry Markram is building a brain in an IBM supercomputer over at EPFL while suggesting patterns of strange attraction that might exist within the mind (see Self Similarity ~ Fractals, Fractals Everywhere…). Looks like we might be able to know in the next 10 years or so whether my intuition is actually fact, or just simply fiction… Also, we might be provided with the definiion of Life, as a sentient being is born within the mainframe of the computer… Perhaps this might preclude the advent of A.I. and justify the complex issues in stories such as Masamune Shirow’s “Ghost In The Shell” and the film “A.I.”?
Henry Markram says the mysteries of the mind can be solved — soon. Mental illness, memory, perception: they’re made of neurons and electric signals, and he plans to find them with a supercomputer that models all the brain’s 100,000,000,000,000 synapses.
About Henry Markram:
Henry Markram, Project Director of the Blue Brain Project, Director of the Center for Neuroscience & Technology and co-Director of EPFL’s Brain Mind Institute, obtained his B.Sc. (Hons) from Cape Town University, South Africa under the supervision of Rodney Douglas and his Ph.D from the Weizmann Institute of Science, Israel, under the supervision of Menahem Segal. During his PhD he discovered a link between acetylcholine and memory mechanisms by showing that acetylcholine modulates the primary receptor linked to synaptic plasticity.
He went to the USA as a Fulbright Scholar at the National Institutes of Health (NIH), where he studied ion channels on synaptic vesicles. He then went as a Minerva Fellow to the Laboratory of Bert Sakmann at the Max Planck Institute, Heidelberg, Germany, where he discovered calcium transients in dendrites evoked by sub-threshold activity, and by single action potentials propagating back into dendrites. He also began studying the connectivity between neurons, describing in great detail how layer 5 pyramidal neurons are interconnected.
He was the first to alter the precise millisecond relative timing of single pre- and post-synaptic action potentials to reveal a highly precise learning mechanism operating between neurons — now reproduced in many brain regions and known as spike timing-dependent synaptic plasticity (STDP). These experiments were carried out in 1993, four years before publication. Although there were some correlation-sensitive findings before, this was the first study that manipulated single pre- and post-synaptic spike times to monitor the effect of synaptic changes.
He was appointed assistant professor at the Weizmann Institute for Science, Israel, where he started systematically dissecting out the neocortical column. He discovered that synaptic learning can also involve a change in synaptic dynamics (called redistribution of synaptic efficacy) rather than merely changing the strengths of connections. He also revealed a spectrum of new principles governing neocortical microcircuit structure, function, and emergent dynamics. Based on the emergent dynamics of the neocortical microcircuit he and Wolfgang Maass developed the theory of liquid computing, or high entropy computing.
In 2002 he moved to EPFL as full professor and founder/director of the Brain Mind Institute and Director of the Center for Neuroscience and Technology. At the BMI, in the Laboratory for Neural Microcircuitry, Markram has continued to unravel the blueprint of the neocortical column, building state-of-the-art tools to carry out multi-neuron patch clamp recordings combined with laser and electrical stimulation as well as multi-site electrical recording ,chemical imaging and gene expression. Markram has received numerous awards and published over 75 papers.
For more information about Henry Markram and his amazing work, please click here.
September 5, 2009
Once again… To follow on from Susan Blackmore’s idea about the illusion of “self” and the notion that all ideas, are nothing more than mental infections, which we seem to pass on to one another… One thing that stands out in this article written by Colin Barras is how “the viral spread of information online has conventionally been modelled using epidemiological tools developed to analyse the spread of biological viruses.” Food for thought… Brought to you from the New Scientist magazine.
The way that certain images, videos or concepts can suddenly spread like wildfire across the web, using email and social websites to propagate, is one of online culture’s most unique phenomena.
Now Spanish researchers claim to have found a way to accurately predict how quickly and widely new pieces of information, or “memes” as they are called, will spread. The ability to forecast this “viral” behaviour would be of great interest to sociologists and marketeers, among others.
The secret, they say, is to recognise the fact that people vary in how “infectious” they are when it comes to sharing content online. While some people pass on things they receive right away, others do so after some delay, or not at all.
The viral spread of information online has conventionally been modelled using epidemiological tools developed to analyse the spread of biological viruses. One of the concepts borrowed is that of an infection’s R0, or basic reproductive number, which describes how many other people someone with the virus can be expected to infect.
Knowing the R0 number help predict the likelihood and extent of real life epidemics, such as H1N1 swine flu. But models that apply the idea to online information can only indicate whether an internet meme is likely to be successful or to die out quickly, says Esteban Moro at the Carlos III University of Madrid, Spain.
Moro, working with José Luis Iribarren at IBM in Madrid, used IBM’s company email newsletter to show the importance of variations between people’s infectiousness in propagating memes online.
Journal references: Moro and Iribarren study – Physical Review Letters (DOI: 10.1103/PhysRevLett.103.038702)
Liben-Nowell and Kleinberg study – Proceedings of the National Academy of Sciences (DOI: 10.1073/pnas.0708471105)