Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data.

ABSTRACT: Tuning curves are the functions that relate the responses of sensory neurons to various values within one continuous stimulus dimension (such as the orientation of a bar in the visual domain or the frequency of a tone in the auditory domain). They are commonly determined by fitting a model e.g. a Gaussian or other bell-shaped curves to the measured responses to a small subset of discrete stimuli in the relevant dimension. However, as neuronal responses are irregular and experimental measurements noisy, it is often difficult to determine reliably the appropriate model from the data. We illustrate this general problem by fitting diverse models to representative recordings from area MT in rhesus monkey visual cortex during multiple attentional tasks involving complex composite stimuli. We fin

SUBMITTER: Helmer M 

PROVIDER: S-EPMC4718600 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature