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