A Refined Neuronal Population Measure of Visual Attention.

Published

Journal Article

Neurophysiological studies of cognitive mechanisms such as visual attention typically ignore trial-by-trial variability and instead report mean differences averaged across many trials. Advances in electrophysiology allow for the simultaneous recording of small populations of neurons, which may obviate the need for averaging activity over trials. We recently introduced a method called the attention axis that uses multi-electrode recordings to provide estimates of attentional state of behaving monkeys on individual trials. Here, we refine this method to eliminate problems that can cause bias in estimates of attentional state in certain scenarios. We demonstrate the sources of these problems using simulations and propose an amendment to the previous formulation that provides superior performance in trial-by-trial assessments of attentional state.

Full Text

Duke Authors

Cited Authors

  • Mayo, JP; Cohen, MR; Maunsell, JHR

Published Date

  • January 2015

Published In

Volume / Issue

  • 10 / 8

Start / End Page

  • e0136570 -

PubMed ID

  • 26296083

Pubmed Central ID

  • 26296083

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

International Standard Serial Number (ISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0136570

Language

  • eng