Decoding Cognitive Processes from Neural Ensembles

An intrinsic difficulty in studying cognitive processes is that they are unobservable states that exist in between observable responses to the sensory environment. Cognitive states must be inferred from indirect behavioral measures. Neuroscience potentially provides the tools necessary to measure cognitive processes directly, but it is challenged on two fronts. First, neuroscientific measures often lack the spatiotemporal resolution to identify the neural computations that underlie a cognitive process. Second, the activity of a single neuron, which is the fundamental building block of neural computation, is too noisy to provide accurate measurements of a cognitive process. In this paper, I examine recent developments in neurophysiological recording and analysis methods that provide a potential solution to these problems. Recent advances in analytic methods and high-channel count recordings have raised the possibility of reading out cognitive processes directly from the brain, as opposed to inferring cognitive processes indirectly from behavior. Decoding neural activity has been used to understand decision making by using place cell activity in the hippocampus or value-selective neural responses in orbitofrontal cortex. Decoding could have broad applications for measuring other cognitive processes directly from neural activity, such as attention, working memory and reasoning.