Encoding and Decoding with Neural Populations in the Primate Cortex

Abstract

Environmental stimuli are encoded by large neural populations in sensory cortical areas and subsequently decoded into motor plans by large neural populations in motor cortical areas. Furthermore, large populations of neurons are likely to exhibit new emergent properties that are difficult or impossible to infer from the activity of single neurons, recorded one at a time. Thus, to understand encoding and decoding in the cortex, it is essential to measure and analyze neural population responses, ideally in behaving subjects. In this chapter we review recent progress in experimental techniques for measuring simultaneously the activity of large neural populations; we discuss several important emergent properties of neural population responses; and we describe a Bayesian ideal observer framework that, when applied to simultaneous measurements of neural population responses and behavioral performance, can be used to rigorously explore encoding and decoding strategies at the level of neural populations.