September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Oscillatory Dynamics in Widespread Cortical Networks During Feature-Based Attention: Coupling Across and Between Frequencies
Author Affiliations
  • Nina Thigpen
    University of Florida
  • Amy Trongnetrpunya
    University of Florida
  • Jean Cibula
    University of Florida
  • Aysegul Gunduz
    University of Florida
  • Forest Gruss
    University of Florida
  • Ke Bo
    University of Florida
  • Enrico Opri
    University of Florida
  • Mingzhou Ding
    University of Florida
  • Andreas Keil
    University of Florida
Journal of Vision September 2018, Vol.18, 14. doi:10.1167/18.10.14
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      Nina Thigpen, Amy Trongnetrpunya, Jean Cibula, Aysegul Gunduz, Forest Gruss, Ke Bo, Enrico Opri, Mingzhou Ding, Andreas Keil; Oscillatory Dynamics in Widespread Cortical Networks During Feature-Based Attention: Coupling Across and Between Frequencies. Journal of Vision 2018;18(10):14. doi: 10.1167/18.10.14.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Feature-based attention is essential for quickly and accurately selecting information from the environment for further, in-depth processing. The animal model provides a strong understanding of the neural correlates of feature-based selective attention from the level of single-cell recordings to large-scale networks. Here, we aim to translate these findings from the animal model to human observers, using electrocorticogram (ECoG) data collected from five patients undergoing evaluation for chronic epilepsy, directly from the left frontal, orbitofrontal, anterior and posterior inferior temporal (IT) cortex. Participants completed a feature-based selective attention task, where they viewed a series of Gabor patches that were either a match or a distractor, relative to a target stimulus. Distractors could differ from the target along three feature dimensions: color (red/green), orientation (left/right), and shape (oval/circle). Results suggest that target features prompt robust amplification of oscillatory gamma and theta activity, in most of the recorded locations. The latency of these changes was consistent with re-entrant bias signals, in which attention effects occur earlier at frontal sites and later (>200 ms) at posterior sites. Gamma power in the inferior temporal cortex showed a parametric reduction as a function of similarity with the target, consistent with inhibitory interactions between similar feature conjunctions. Notably, IT areas showed interference, which varied parametrically with confusability. This suggests that feature conjunctions are represented in IT, and that similar conjunctions inhibit each other. Although evidence for strong signaling was found from frontal to IT cortex from a granger causality analysis, the suppressive interactions in IT were not inherited from frontal locations. Together, the findings support a model of block-wise biasing of target features from frontal areas, aided by sharpening through local inhibitory interactions.

Meeting abstract presented at VSS 2018

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