Georgia Tech Neuro Seminar Series
"From Spikes to Factors: Understanding Large-scale Neural Computations”
Mark Churchland, Ph.D.
Department of Neuroscience
It is widely accepted that human cognition is the product of spiking neurons. Yet even for basic cognitive functions, such as the ability to make decisions or prepare and execute a voluntary movement, the gap between spikes and computation is vast. Only for very simple circuits and reflexes can one explain computations neuron-by-neuron and spike-by-spike. This approach becomes infeasible when neurons are numerous the flow of information is recurrent. To understand computation, one thus requires appropriate abstractions. An increasingly common abstraction is the neural ‘factor’. Yet there remains some discomfort with this abstraction, and with any attempt to provide mechanistic explanations above that of spikes, neurons, cell-types, and other comfortingly concrete entities. I will explain why, for many networks of spiking neurons, factors are not only a well-defined abstraction, but are critical to understanding network computation mechanistically. Indeed, factors are as real as other abstractions we now accept: pressure, temperature, conductance, and even the action potential itself. I use recent empirical results to illustrate how factor-based hypotheses have become essential to the forming and testing of scientific hypotheses. I will also show how fully embracing factor-level descriptions affords remarkable power when decoding neural activity for neural engineering purposes.
Professor Churchland is an Associate Professor in the Department of Neuroscience at Columbia University. He is the co-director of the Grossman Center for the Statistics of Mind. He received his BA in mathematics and psychology from Reed College in Portland Oregon. He received his PhD in neuroscience from the University of California San Francisco. His postdoctoral work was in the Neural Prosthetic Systems Laboratory of Professor Krishna Shenoy at Stanford University. Professor Churchland’s laboratory focuses on how the brain controls voluntary movement.
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