Xiao-Jing Wang
Yale University School of Medicine
Friday, September
26, 2008
4:00 pm in SPL 57
How stochastic neurons in the brain make decisions: theory meets experiments
Abstract: Decision making, which pervades our daily lives, is ultimately a computation carried out by the collective dynamics of millions of neurons in the brain. Can we understand the neural circuit mechanism of decision making, at the biophysical level, as we have so successively done in studies of much simpler systems such as signal processing in the retina? Recently, neurophysiologists have recorded from nerve cells in the brains of monkeys performing simple decision tasks. These studies have begun to reveal how neurons accumulate information in favor or against choice options in a deliberative decision process, eventually leading to a categorical response. In this talk, I will summarize experimental data and present a biophysically-based recurrent neural network model of decision making. I will show that this model accounts for a range of observations from two sets of monkey experiments: one on perceptual decisions in the visual system, the other on reward-based economic choice behavior. In particular, I will discuss the highly stochastic nature of neural activity, how it is generated and may be computationally harnessed. This model suggests a circuit mechanism for decision making that can be described theoretically in terms of stochastic attractor dynamical systems.
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