The human brain simulation project (Blue Brain) wins a billion euros!!


In one of the biggest funding exercises ever, European Commission has selected Prof. Henry Markrams (pictured above) dream project – The Human Brain Simulation Project for a mammoth grant of € 1 billion over a period of ten years.

The Human Brain Simulation Project or the Blue Brain project has been a center of quite a controversy ever since it started in 2005 at the  École Polytechnique Fédérale de Lausanne (Switzerland). It aims to create a synthetic brain by reverse engineering a human brain down to its molecular details. It uses the famed Blue GENE supercomputer  and uses Michael Hine’s NEURON software to recreate neural connections not just by using Artificial Neural Networks but by a closer approximate model of neurons.

What is it all about?

Neuroscientists have been trying to understand the inner workings of our human brain for some centuries now. First came, the detailed anatomical drawings by Rufus of Ephesus, Galen and Leonardo da VinciThen English physician Thomas Willis published his Anatomy of the Brain which assimilated all its inner structures. The goal of understanding what brain is and how it does work started from these anatomical drawings and has continued on to constructing detailed mathematical models of how each of the cells within it work. Of course, i am talking about the famous Hodgkin-Huxley model which for the first time describes how action potentials in neurons are initiated and propagated.

The quest for understanding how billions of neurons come together in a complex network with millions of feedback loops and yet function so harmoniously without any hint of chaos is considered to be one of the Holy Grails of Science. In this picture comes Prof Markram’s Human Brain Simulation project. With advanced supercomputer at one side, and brilliant electrophysiologists at the other the aim has been to model not just the neural circuits involved in, say, the sense of smell, but to model everything,

“from the genetic level, the molecular level, the neurons and synapses, how microcircuits are formed, macrocircuits, mesocircuits, brain areas — until we get to understand how to link these levels, all the way up to behaviour and cognition”


Progress until now?

Obviously to even start off this mammoth task, one has to first demonstrate this so-called unified approach on a smaller scale. And that was indeed what he started off with. From 1995 to 2006 he collected data on 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 0.5 mm and contains about 60,000 neurons in humans; rat neocortical columns are very similar in structure but contain only 10,000 neurons (and 108 synapses). By December 2006, Markram was able to map all the types of neurons and their connections in that column.

By 2008, the researchers had linked about 10,000 such models into a simulation of a tube-shaped piece of cortex known as a cortical column. Now, using a more advanced version of Blue Gene, they have simulated 100 interconnected columns.This has indeed proven that  such unifying models can, as promised, serve as repositories for data on cortical structure and function.

Source: Human Brain Project

All of this has only been possible due to the large-scale advances in supercomputing technology and data storage facilities. The computer power required to run such a grand unified theory of the brain would be roughly an exaflop, or 1018 operations per second, which were quite hopeless in the 1990’s when Markram started off the project. But as available computer power doubles roughly every 18 months, so exascale computers might be available by the 2020’s.


Source: Human Brain Project

There has been some criticisms to this project, and that has to do with the media hype generated by Markram. His critics argue that he has been making his case through talks, media interviews, well-placed ads, and through the traditional means of publishing articles, reviews etc. The detractors also argue that the Markram’s bottom-up approach might yield such a model  which could be so detailed that it is no easier to understand than the real brain. Also, the progress till now has not been daunting either, as the rat neocortex has no inputs from sensory organs or outputs to other parts of the brain, and produces almost no interesting behaviour.

But despite all the criticism, one hopes that this gargantuan project with its lofty aim would yield interesting results, even if not a complete replica of human brain but at least a shadow simulacrum would be enough. For all the critics, who are too afraid of Markram’s bold new ideas I would reiterate James Russell Lowell:

 “Creativity is not the finding of a thing, but the making something out of it after it is found.”

More on this:

  1. Turing at 100: Legacy of a universal mind, Nature News, 2012.
  2. European researchers chase billion-euro technology prize, Nature News, 2011.
  3. Bioinformatics: Industrializing neuroscience, Markram, Nature, 2007.
  4. The Blue Brain Project, Markram H, Nature, 2006.
  5. Human Brain Project, EU Initiative.
  6. The Blue Brain Project @ EPFL


Is having a large brain a good idea? Research suggests otherwise !!


Well, we have all heard the age-old adage of bigger brains being the better and how humans have the largest brain-to-body ratio among all animals. So, scientists have been asking this question: What would happen if the size of brains continue to increase? Would the organism become more intelligent? Would there be any cost?

Evolutionary biologists in 1990’s proposed the The Expensive Tissue Hypothesis to account for the costs and benefits of brain size. Brains are highly useful organs; more amount of brain cells would allow for more flexibility in doing different behaviours, better control of larger bodies, and, obviously intelligence. But if bigger brains were always better, then every animal would have them. So, the biologists reasoned, there has to be a downside of such increased brain size. Hence, the hypothesis suggests that while having larger brains are awesome, however their extremely high energetic cost limits their size and tempers their growth.

For example in humans, our brains take up just 2% of our bodies, but they take up a whopping 20% of our energy requirements. And one has to wonder: if our brains use up that much energy, which body parts have paid the price? The hypothesis suggested our guts have suffered, but the  extra intelligence gained by having more brain cells made up for more efficient foraging and hunting, hence overcoming the obstacle. Despite over a century of research on the evolution of brain size, empirical support for the trade-off between cognitive ability and energetic costs is based exclusively on correlative evidence and the theory remains controversial.



What they did?

A study published in Current Biology this month, led by Niclas Kolm and others have attempted to solve this question by conducting an empirical study on guppies (Poecilia reticulata, pictured above).  They used artificial selection on relative brain size in the guppy, to provide a direct test of the prediction that increased brain size is genetically associated with increased cognitive ability but that a large brain is also traded off against gut size and results in reduced reproductive performance. Breaking it down, they had four steps:

  1. To test the evolutionary response to divergent selection on relative brain size.
  2. The cognitive ability of large and small-brained individuals was tested using an associative learning assay designed to investigate numerical quantification, a relatively advanced form of cognition.
  3. The correlated evolutionary response of gut size in response to direct selection on brain size was also tested.
  4. Lastly, it was tested whether the important proxies of reproductive fitness (offspring number, offspring size, age at first reproduction) are anyhow affected by brain size evolution.

What they found?

First, the team selected for larger and smaller brains from the available natural variation in guppies. They  then successfully created smart guppies that had brains about 9% larger than their counterparts through artificial selection. Then, they put them to the test. While the males seemed to gain no benefits from possessing the larger brains, the females with bigger brains were significantly better at the tasks.What they found was that the evolution of relative brain size in guppies can be a fast process when under strong directional selection as in the study. Also, the relative brain size was found to be highly heritable in both sexes.


What was really remarkable was the cost of these larger brains. Gut size was found to be 20% smaller in large-brained males and 8% smaller in large-brained females. The reduced digestive system seemed to have serious reproductive consequences,  as the smarter fish produced 19% fewer offspring in their first clutch, even though they started breeding at the same age as their lesser bright counterparts. One thing to keep in mind here which the authors also noted, was  that this experiment was conducted in an idealized tank setting with all the guppies receiving plenty of food—So what about the wild, where resources are harder to come by? How much of a cost does a reduced gut have when resources are scarce?

Though, there are still many questions to be answered. For example, the authors aren’t entirely sure why females were the only ones to show cognitive improvement with larger brains. They suggest that, perhaps, the measure of intelligence used (the numerical task presented to the guppies) may be favourable toward female behaviors. As is known from literature, in the guppy, females are more active and innovative while foraging. As females feed more, so they may have had more time to associate the cue with food in the experimental design.

What now?

The clear trade-off which the authors see between brains and guts, is an important finding. By providing an empirical evidence for the physiological costs of brains, this study provides the first direct support for the expensive-tissue hypothesis, and can provide us with insights into how our own big brains evolved. One of the prevailing hypothesis for our own brain growth is that the incorporation of more animal products into our diets, through hunting or cooking or however, allowed us to obtain more energy from less food, thus offsetting the cost of a reduced gut. The less food we needed to eat for the same amount of energy, the more our brains could grow even if our guts suffered for it. The debate, however, is far from over. Comparative analyses in primates don’t support a gut-brain tradeoff, and there are certainly plenty of other hypothesis as to how and why we developed our massive lobes, and what prices our bodies paid for them.

Research suggests, Facebook chats are more memorable than books !!

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Online social networking is highly popular and allows its members to post their thoughts as micro-blogs. This opportunity is exploited by people on Facebook alone, over 30 million times an hour. One does think that such trivial ephemera, would vanish quickly from everyone’s memory. However, they may comprise the sort of information that our memories are tuned to recognize, if that which we readily generate, we also readily store. Recent research published in the journal Memory & Cognition by cognitive psychologist Laura Mickes of the University of California, San Diego, and her colleagues, suggests that Facebook posts are one-and-a-half times as memorable as book sentences.

How they did it?

The authors initially were not researching on Facebook chats per se, but were looking into the effects of emotions on memory, and they happened to be using Facebook posts to invoke various feelings. What they surprisingly found was that the status updates seemed to be memorable all on their own.  They gathered Facebook posts from the accounts of undergraduate research assistants and also randomly selected sentences from recently published books.  They then stripped the posts and book excerpts of their context, and then asked a few college undergraduate students  to study and memorize the selected phrases from either Facebook or books, assigning equal number of students to each group. Then they sat the volunteers in front of a computer screen and, one at a time, displayed either a sentence the volunteer had studied or a sentence that was new to the volunteer. The team asked the subjects if they had seen each before, and how sure they were about it.

What does it prove?

All of this points out to the fact that Facebook, Twitter and other such social messaging platforms have brought the fluidity of personal conversations into written text. And we all know how easily we remember social conversations better.

All of this however, does not mean that you can cram for exams by posting chitchats on Facebook, Twitter etc!!