Mimickingbrain, in silicon

Mimicking the brain, in silicon

2:22 AM, 17th November 2011
Mimicking the brain, in silicon
Fabricated analog very-large-scale integration (VLSI) chip used to mimic neuronal processes involved in memory and learning.


CAMBRIDGE, US: For decades, scientists have dreamed of building computer systems that could replicate the human brain’s talent for learning new tasks.

MIT researchers have now taken a major step toward that goal by designing a computer chip that mimics how the brain’s neurons adapt in response to new information. This phenomenon, known as plasticity, is believed to underlie many brain functions, including learning and memory.

With about 400 transistors, the silicon chip can simulate activity of a single brain synapse - a connection between two neurons that allows information to flow from one to the other. “Neuroscientists can learn about how the brain works and could also be used in neural prosthetic devices,” said Chi-Sang Poon, Principal Research Scientist in the Harvard-MIT Division of Health Sciences and Technology.

Poon is the Senior author of the paper, in the National Academy of Sciences the week of Nov 14. Guy Rachmuth, a former Postdoc in Poon’s lab, is Lead author of the paper. Other authors are Mark Bear, Picower Professor of Neuroscience at MIT and Harel Shouval of the University of Texas Medical School.

There are about 100 billion neurons in the brain, each of which forms synapses, the gap between two neurons, with many other neurons. All the synaptic activity depends on ion channels, which control flow of charged atoms such as sodium, potassium and calcium. The MIT researchers designed their computer chip so that transistors could mimic the activity of different ion channels. Current flows through transistors on the new brain chip in analog, not digital, fashion. “We can tweak the parameters of the circuit to match specific ion channels. We now have a way to capture each and every ionic process that’s going on in a neuron,” said Poon.

The MIT researchers plan to use their chip to build systems to model specific neural functions, such as visual processing system. Such systems could be much faster than digital computers. Another potential application is enabling communication between neural prosthetic devices such as artificial retinas and the brain and also for artificial intelligence devices.

The MIT researchers have already used their chip to propose a resolution to a longstanding debate over how long term depression (LTD) occurs. Both require the involvement of ion channels known as NMDA receptors, which detect postsynaptic activation. Both models could be unified if there were a second type of receptor involved in detecting that activity. One candidate for that second receptor is the endo-cannabinoid receptor.

When researchers included on their chip transistors that model endo-cannabinoid receptors, they were able to accurately simulate both LTD and long-term potentiation (LTP). “Nobody had put all this together and demonstrated computationally that indeed this works and this is how it works,” said Poon.

(C)  Massachusetts Institute of Technology News




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