The Center for Cognitive Neuroscience at Dartmouth presents:
Intersection information: a mathematical framework to study the contribution of neural codes to behavior
Given by STEFAN PANZERI, Director of the Neural Computation Laboratory; Senior Researcher Italian Institute of Technology Center for Neuroscience and Cognitive Systems
November 10, 2016
Abstract
The two basic processes underlying perceptual decisions - how neural responses encode stimuli, and how they inform behavioural choices - have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes", have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, I propose a mathematical framework centred on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behaviour; that is, the features that have an intersection between sensory and choice information. I will discuss how this framework leads to a new statistical analysis of neural activity recorded during behaviour that can identify such neural codes. I will illustrate these concepts with an application to study the role of millisecond-scale spike timing and spike rates to the performance of texture discrimination in rodents. Finally, I will briefly discuss how to combine intersection-based analysis of neural recordings with interventional manipulations of neural activity to determine definitively whether a neural code is involved in a task.
