Physiology and Biophysics Department, University of Washington, USA
Tuesday 19 December 2006, 16:00
Seminar Room B10 (Basement)
Alexandra House, 17 Queen Square, London, WC1N 3AR
A neural mechanism for decision-making, or how I learned to stop worrying and love the bound
With little sophistication, the spike rates from sensory neurons can be used to approximate useful statistics for decision-making. In the context of deciding between two sensory hypotheses, a simple difference in spike rate between sensory neurons with opposite selectivity is proportional to the log likelihood ratio in favor of one sensory interpretation over another. I will describe neural recording and stimulation experiments from the alert monkey that demonstrate that the brain uses such a difference to make decisions about the direction of motion in a 2-alternative direction discrimination task. The accumulation of this difference to threshold explains the speed and accuracy of simple decisions. A new probabilistic classification task, similar to the .weather prediction task. reveals a direct representation of log probability in parietal cortex. And, if time permits, I will explain how the brain uses elapsed time to decode such probability. I will try to relate these observations to a more general computational framework for the encoding and read out of information by neurons in neocortex.