Cognitive computing aims to develop a coherent, unified, universal mechanism inspired by the mind’s capabilities. Rather than assemble a collection of piecemeal solutions, whereby different cognitive processes are each constructed via independent solutions, we seek to implement a unified computational theory of the mind.
Neuroanatomy places critical constraints on the functional connectivity of the cerebral cortex. To understand and model these constraints, the brain network has to be extracted and and its properties analyzed. We have derived a unique network incorporating 410 anatomical tracing studies of the macaque brain. The network consists of 383 hierarchically organized regions spanning cortex, thalamus, and basal ganglia and models the presence of 6,602 directed long-distance connections.
Important network-theoretic properties that we found include: the brain has a exponential degree distribution; the pre-frontal cortex, the region implicated in executive functions, is central under many different topological centrality measures; and there exists a tighly integrated core in the brain network. In this talk I will discuss the brain network, its properties, and how this is useful in the cognitive computing paradigm.
Bio - Raghavendra Singh is a Research Staff member at IBM Research - India (Delhi). He is currently a member of the Cognitive Computing group. His research interests are in the area of information theory, signal processing and representation as applied to a spectrum of problems in neuro-science, compression and transmission of multimedia data, and monitoring of large-scale data centers.
He did his PhD. in Electrical Engineering from University of Southern California (2001). His undergraduate degree is from BITS Pilani, India (1993). He is a Senior Member of the IEEE.