Brain Computation as Hierarchical Abstraction
An argument that the complexities of brain function can be understood hierarchically, in terms of different levels of abstraction, as silicon computing is.
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.
HardcoverOut of Print ISBN: 9780262028615 456 pp. | 9 in x 6 in 167 color illus.
Paperback$46.00 S ISBN: 9780262534123 456 pp. | 9 in x 6 in 167 color illus.
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.
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.
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.
University Professor, Department of Molecular Neuroscience, George Mason University; author of Trees of the Brain, Roots of the Mind