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UT Professor of Computer Science Dr. Dana Ballard recently published a new book, titled "Brain Computation as Hierarchical Abstraction." Please see below for a complete overview. The following was originally published by MIT Press.

Brain Computation as Hierarchical Abstraction

By Dana H. Ballard 


The vast differences between the brain’s neural circuitry and a computer’s silicon circuitry might suggest that they have nothing in common. In fact, as Dana Ballard argues in this book, computational tools are essential for understanding brain function. Ballard shows that the hierarchical organization of the brain has many parallels with the hierarchical organization of computing; as in silicon computing, the complexities of brain computation can be dramatically simplified when its computation is factored into different levels of abstraction.

Drawing on several decades of progress in computational neuroscience, together with recent results in Bayesian and reinforcement learning methodologies, Ballard factors the brain’s principal computational issues in terms of their natural place in an overall hierarchy. Each of these factors leads to a fresh perspective. A neural level focuses on the basic forebrain functions and shows how processing demands dictate the extensive use of timing-based circuitry and an overall organization of tabular memories. An embodiment level organization works in reverse, making extensive use of multiplexing and on-demand processing to achieve fast parallel computation. An awareness level focuses on the brain’s representations of emotion, attention and consciousness, showing that they can operate with great economy in the context of the neural and embodiment substrates.

About the Author

Dana H. Ballard is Professor in the Department of Computer Sciences at the University of Texas at Austin, where he has appointments in Psychology, the Institute for Neuroscience, and the Center for Perceptual Systems. He is the author of An Introduction to Natural Computation (MIT Press).


“Levels of abstraction is a key architectural approach in computer science. This approach to hierarchical systems is not sufficiently utilized in other fields. In this important volume Dana Ballard explores how computation in the human brain can be effectively modeled using levels of abstraction.”
Joel Moses, Institute Professor and former Provost, MIT

“This is a straightforward and highly readable formalization of brain function that has been needed for many years. The author synthesizes widely diverse material and concepts and presents a charming text derived from many years of intensive reflections and thoughtful dialogues.”
Wolfram Schultz, University of Cambridge

“Neuroscientists see molecules, spikes, and synapses, yet fail to grasp the computing essence of neural processes; computational scientists are not yet fluent in the language of evolution to graduate from engineering to reverse engineering. Hopping on the giant shoulders of David Marr and Churchland & Sejnowski, Ballard finds a remarkable vantage point on brain computation.”
Giorgio Ascoli, University Professor, Department of Molecular Neuroscience, George Mason University; author of Trees of the Brain, Roots of the Mind

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