Event Date
MARK CHURCHLAND, PH.D.
Associate Professor, Department of Neuroscience
Co-Director, Grossman Center for the Statistics of Mind
Columbia University Medical Center
Host: Sergey Stavisky, PhD, sstavisky@ucdavis.edu
This is an in-person event. Please register here: http://tinyurl.com/Neuroeng-Feb24
Registration for remote attendance is limited to colleagues from the Sacramento campus and those working remotely: https://tinyurl.com/NeuroengFeb24
Abstract
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 and the flow of information is recurrent. To understand computation, one thus requires appropriate abstractions.
An increasingly common abstraction is the neural ‘factor’. Factors are central to many explanations in systems neuroscience. Factors provide a framework for describing computational mechanism, and offer a bridge between data and concrete models. 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 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 embracing factor-level descriptions affords remarkable power when decoding neural activity for neural engineering purposes.
Bio
Professor Churchland is an Associate Professor in the Department of Neuroscience at Columbia University Medical Center. 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 at Stanford University. Professor Churchland’s research focuses on how the brain controls voluntary movement, and addresses on questions such as: how does the brain prepare and generate voluntary movement? What is the key event that triggers a movement, and in doing so turns thought into action? Can we reduce the problem of movement generation to a problem of characterizing the neural dynamics that are necessary to generate muscle activity? If so, how should we then think of upstream ‘cognitive’ processes that determine which movement to make and when to make it?
Professor Churchland is a recipient of the 2012 NIH Directors’ New Innovator Award. He received a 2015 Klingenstein-Simons Fellowship Award, a 2013 McKnight Scholar Award, a 2013 Sloan Research Fellowship, and a 2012 Searle Scholars Award. He was a 2006 recipient of the Burroughs Wellcome Fund Career Award and a 2003 recipient of the Helen Hay Whitney Research Fellowship.