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Dharmendra S. Modha

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Archives for 2011

Communications of the ACM

July 27, 2011 By dmodha

The August 2011 issue of the Communications of the ACM published our paper on Cognitive Computing.

Authors:
Dharmendra S. Modha
Rajagopal Ananthanarayanan
Steven K. Esser
Anthony Ndirango
Anthony J. Sherbondy
Raghavendra Singh

Abstract:
Unite neuroscience, supercomputing, and nanotechnology to discover, demonstrate, and deliver the brain’s core algorithms.

Filed Under: Accomplishments, Brain-inspired Computing, Papers

Neural network computation with DNA strand displacement cascades

July 21, 2011 By dmodha

Today, Lulu Qian, Erik Winfree & Jehoshua Bruck published an interesting paper in Nature.

Abstract: The impressive capabilities of the mammalian brain—ranging from perception, pattern recognition and memory formation to decision making and motor activity control—have inspired their re-creation in a wide range of artificial intelligence systems for applications such as face recognition, anomaly detection, medical diagnosis and robotic vehicle control. Yet before neuron-based brains evolved, complex biomolecular circuits provided individual cells with the ‘intelligent’ behaviour required for survival. However, the study of how molecules can ‘think’ has not produced an equal variety of computational models and applications of artificial chemical systems. Although biomolecular systems have been hypothesized to carry out neural-network-like computations in vivo and the synthesis of artificial chemical analogues has been proposed theoretically experimental work has so far fallen short of fully implementing even a single neuron. Here, building on the richness of DNA computing and strand displacement circuitry, we show how molecular systems can exhibit autonomous brain-like behaviours. Using a simple DNA gate architecture that allows experimental scale-up of multilayer digital circuits, we systematically transform arbitrary linear threshold circuits (an artificial neural network model) into DNA strand displacement cascades that function as small neural networks. Our approach even allows us to implement a Hopfield associative memory with four fully connected artificial neurons that, after training in silico, remembers four single-stranded DNA patterns and recalls the most similar one when presented with an incomplete pattern. Our results suggest that DNA strand displacement cascades could be used to endow autonomous chemical systems with the capability of recognizing patterns of molecular events, making decisions and responding to the environment.

Filed Under: Brain-inspired Computing

Early Tagging of Cortical Networks Is Required for the Formation of Enduring Associative Memory

March 7, 2011 By dmodha

I read a thought-provoking article in Science (18 Feb 2011) by Edith Lesburguères, Oliviero L. Gobbo, Stéphanie Alaux-Cantin, Anne Hambucken, Pierre Trifilieff, and Bruno Bontempi.

Abstract: Although formation and stabilization of long-lasting associative memories are thought to require time-dependent coordinated hippocampal-cortical interactions, the underlying mechanisms remain unclear. Here, we present evidence that neurons in the rat cortex must undergo a “tagging process” upon encoding to ensure the progressive hippocampal-driven rewiring of cortical networks that support remote memory storage. This process was AMPA- and N-methyl-D-aspartate receptor–dependent, information-specific, and capable of modulating remote memory persistence by affecting the temporal dynamics of hippocampal-cortical interactions. Post-learning reinforcement of the tagging process via time-limited epigenetic modifications resulted in improved remote memory retrieval. Thus, early tagging of cortical networks is a crucial neurobiological process for remote memory formation whose functional properties fit the requirements imposed by the extended time scale of systems-level memory consolidation.

Filed Under: Brain-inspired Computing

Social Animal

February 7, 2011 By dmodha

My colleague, Raghavendra Singh, pointed out the following very interesting quote from the New Yorker:

"The information that comes from deep in the evolutionary past we call genetics. The information passed along from hundreds of years ago we call culture. The information passed along from decades ago we call family, and the information offered months ago we call education. But it is all information that flows through us. The brain is adapted to the river of knowledge and exists only as a creature in that river. Our thoughts are profoundly molded by this long historic flow, and none of us exists, self-made, in isolation from it."

Filed Under: Brain-inspired Computing

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