Dharmendra S. Modha

My Work and Thoughts.

Rapid Erasure of Long-Term Memory Associations in the Cortex by an Inhibitor of PKM zeta

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Science published an interseting study (Science 17 August 2007:
Vol. 317. no. 5840, pp. 951 – 953) by Reut Shema, Todd Charlton Sacktor, and Yadin Dudai.

Abstract:

Little is known about the neuronal mechanisms that subserve long-term memory persistence in the brain. The components of the remodeled synaptic machinery, and how they sustain the new synaptic or cellwide configuration over time, are yet to be elucidated. In the rat cortex, long-term associative memories vanished rapidly after local application of an inhibitor of the protein kinase C isoform, protein kinase M zeta (PKM zeta). The effect was observed for at least several weeks after encoding and may be irreversible. In the neocortex, which is assumed to be the repository of multiple types of long-term memory, persistence of memory is thus dependent on ongoing activity of a protein kinase long after that memory is considered to have consolidated into a long-term stable form.

DARPATECH 2007

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Last week, I had the opportunity to attend DARPATECH 2007 at which DARPA presented its vision. The Urban Challenge was also announced. The event attracted huge media attention:

http://www.popularmechanics.com/technology/military_law/4220413.html
http://blog.wired.com/defense/2007/08/darpatech-the-b.html
http://www.hardocp.com/news.html?news=Mjc0MDMsLCxoZW50aHVzaWFzdCwsLDE=
http://www.engadget.com/2007/08/09/new-military-robots-showcased-at-darpatech-2007/
http://science.slashdot.org/article.pl?sid=07/08/11/1527243
http://www.designnews.com/blog/320000232/post/1590012959.html

Elizabeth Torres: Three building blocks of the mind to autonomously control the body

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Elizabeth TorresWe had a wonderful talk today from Dr. Elizabeth Torres who is currently at CalTech.

Abstract:

We propose three necessary components for autonomous behavior that any biological organism with sensors, a nervous system subject to the inevitable sensory-processing internal delays and equipped with memories should have. The first component deals with spatio-temporal disparities between the internal and the external mediums of the organism to facilitate comparisons of signals that may be misaligned in space and time. The second component evaluates the similarities between current and old (memories) information to select a course of action (storing a new memory from scratch, using an old memory as it is, or updating an old memory to turn it into a new one as part of a family). The third component regulates the level of relevance for storage, retrieval and update of memories according to the consequences that a given situation my have for the survival and reproduction of the organism.

We provide an example of how these three blocks manifest in primates within the domain of voluntary arm movements. As other systems in the brain, the sub-systems involved in these autonomous behaviors have to deal with sensory-motor maps and transformations involving disparate spatio-temporal representations, internal sensory-processing delays and memories (in the motor domain). Thus these subsystems need to store, retrieve and update memories, which (in primates) we define as associations between the allocentric representation of internal delays (anchored to an early sensory receptor like those in the retina) and a given set of external contextual cues according to their relevance (consequence). We show empirical data from humans and monkeys that strongly suggest that in primates, given a situation such binding computation can be allocentric encoded retinotopically independent of body motions. This evidence changes the way in which we currently think of episodic memory and provides a fresh look at how our conscious notion of the passage of time may have come about.

PC Magazine’s Covery Story: “The Man-made Brain”

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PC Magazine‘s July 17, 2007 issue features a Cover Story on “Five Ideas That Will Reinvent Modern Computing”. One of the five technologoies is on IBM Research’s work on Cognitive Computing.  The following is an excerpt from the story.

It could be the most ambitious computer science project of all time. At IBM’s Almaden Research Center, just south of South Francisco, Dharmendra Modha and his team are chasing the holy grail of artificial intelligence. They aren’t looking for ways of mimicking the human brain, they’re looking to build one-neuron by neuron, synapse by synapse.

“We’re trying to take the entire range of qualitative neuroscientific data and integrate it into a single unified computing platform,” says Modha. “The idea is to re-create the ‘wetware’ brain using hardware and software.”

The project is particularly daunting when you consider that modern neurology has yet to explain how the brain actually works. Yes, we know the fundamentals. But we can’t be sure of every biological transaction, all the way down to the cellular level. Three years into this Cognitive Computing project, Modha’s team isn’t just building a brain from an existing blueprint. They’re helping to create the blueprint as they build. It’s reverse engineering of the highest order.

Their first goal is to build a “massively parallel cortical simulator” that re-creates the brain of a mouse, an organ 3,500 times less complex than a human brain (if you count each individual neuron and synapse). But even this is an undertaking of epic proportions. A mouse brain houses over 16 million neurons, with more than 128 billion synapses running between them. Even a partial simulation stretches the boundaries of modern hardware. No, we don’t mean desktop hardware. We’re talkin’ supercomputers.

So far, the team has been able to fashion a kind of digital mouse brain that needs about 6 seconds to simulate 1 second of real thinking time. That’s still a long way from a true mouse-size simulation, and it runs on a Blue Gene/L supercomputer with 8,192 processors, four terabytes of memory, and 1 Gbps of bandwidth running to and from each chip. “Even a mouse-scale cortical simulation places an extremely heavy load on a supercomputer,” Modha explains. “We’re leveraging IBM’s technological resources to the limit.”

Written with ordinary C code, this initial simulation is a remarkable proof of concept. As neuroscience and computing power continue to advance, Modha and his team are confident they can build cortical simulators of even greater complexity. And as they do, they hope to advance neuroscience even further, learning more and more about the inner workings of the brain and getting closer and closer to their ultimate goal.

Once they’ve simulated a mouse brain in real time, the team plans on tackling a rat cortex, which is about three and a half times larger. And then a cat brain, which is ten times larger than that. And so on, until they’ve built a cortical simulator on a human scale.

What’s that good for? Anything and everything. “What we’re seeking with cognitive computing is a universal cognitive mechanism, something that can give rise to the entire range of mental phenomena exhibited by humans,” says Modha. “That is the ultimate goal.”