Cross-frequency power coupling between hierarchically organized face-selective areas

Nicholas Furl, Richard Coppola, Bruno B. Averbeck, Daniel R. Weinberger

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Neural oscillations are linked to perception and behavior and may reflect mechanisms for long-range communication between brain areas. We developed a causal model of oscillatory dynamics in the face perception network using magnetoencephalographic data from 51 normal volunteers. This model predicted induced responses to faces by estimating oscillatory power coupling between source locations corresponding to bilateral occipital and fusiform face areas (OFA and FFA) and the right superior temporal sulcus (STS). These sources showed increased alpha and theta and decreased beta power as well as selective responses to fearful facial expressions. We then used Bayesian model comparison to compare hypothetical models, which were motivated by previous connectivity data and a well-known theory of temporal lobe function. We confirmed this theory in detail by showing that the OFA bifurcated into 2 independent, hierarchical, feedforward pathways, with fearful expressions modulating power coupling only in the more dorsal (STS) pathway. The power coupling parameters showed a common pattern over connections. Low-frequency bands showed same-frequency power coupling, which, in the dorsal pathway, was modulated by fearful faces. Also, theta power showed a cross-frequency suppression of beta power. This combination of linear and nonlinear mechanisms could reflect computational mechanisms in hierarchical feedforward networks.

Original languageEnglish (US)
Pages (from-to)2409-2420
Number of pages12
JournalCerebral Cortex
Volume24
Issue number9
DOIs
StatePublished - Sep 2014
Externally publishedYes

Keywords

  • Dynamic causal modeling
  • Face perception
  • Facial expression
  • Magnetoencephalography
  • Neural oscillations

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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