Reconciling coherent oscillation with modulation of irregular spiking activity in selective attention: Gamma-range synchronization between sensory and executive cortical areas

Salva Ardid, Xiao Jing Wang, David Gomez-Cabrero, Albert Compte

Research output: Contribution to journalArticlepeer-review

Abstract

In this computational work, we investigated gamma-band synchronization across cortical circuits associated with selective attention. Themodel explicitly instantiates a reciprocally connected loop of spiking neurons between a sensory-type (area MT) and an executive-type (prefrontal/parietal) cortical circuit (the source area for top-down attentional signaling). Moreover, unlike models in which neurons behave as clock-like oscillators, in our model single-cell firing is highly irregular (close to Poisson), while local field potential exhibits a population rhythm. In this "sparsely synchronized oscillation" regime, the model reproduces and clarifies multiple observations from behaving animals. Top-down attentional inputs have a profound effect on network oscillatory dynamics while only modestly affecting single-neuron spiking statistics. In addition, attentional synchrony modulations are highly selective: interareal neuronal coherence occurs only when there is a close match between the preferred feature of neurons, the attended feature, and the presented stimulus, a prediction that is experimentally testable. When interareal coherence was abolished, attention-induced gain modulations of sensory neurons were slightly reduced. Therefore, our model reconciles the rate and synchronization effects, and suggests that interareal coherence contributes to large-scale neuronal computation in the brain through modest enhancement of rate modulations as well as a pronounced attention-specific enhancement of neural synchrony.

Original languageEnglish (US)
Pages (from-to)2856-2870
Number of pages15
JournalJournal of Neuroscience
Volume30
Issue number8
DOIs
StatePublished - Feb 24 2010

ASJC Scopus subject areas

  • General Neuroscience

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