Interacting rhythms enhance sensitivity of target detection in a fronto-parietal computational model of visual attention

Author:

Aussel Amélie12ORCID,Fiebelkorn Ian C34,Kastner Sabine45ORCID,Kopell Nancy J12,Pittman-Polletta Benjamin Rafael12ORCID

Affiliation:

1. Cognitive Rhythms Collaborative, Boston University

2. Department of Mathematics and Statistics, Boston University

3. Department of Neuroscience and Del Monte Institute for Neuroscience, University of Rochester Medical Center, University of Rochester

4. Princeton Neuroscience Institute, Princeton University

5. Department of Psychology, Princeton University

Abstract

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at α, β, and γ frequencies—rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by θ-rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

Funder

National Institutes of Health

National Institute of Mental Health

National Eye Institute

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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