Alpha oscillations support the efficiency of guided visual search by inhibiting both target and distractor features in early visual cortex

Abstract

AbstractVisual search models have long emphasised that task-relevant items must be prioritized for optimal performance. While it is known that search efficiency also benefits from active distractor inhibition, the underlying neuronal mechanisms are debated. Here, we used MEG in combination with Rapid Invisible Frequency Tagging (RIFT) to understand the neural correlates of feature-guided visual search. RIFT served as a continuous read-out of the neuronal excitability to the search stimuli and revealed evidence for target boosting and distractor suppression in early visual cortex. These findings were complemented by an increase in occipital alpha power predicting faster responses and higher hit rates, as well as reduced RIFT responses to all stimuli, regardless of their task-relevance. We propose that alpha oscillations in early visual regions implement ablanket inhibitionthat reduces neuronal excitability to both target and distractor features. As the excitability of neurons encoding the target features is boosted, these neurons overcome the inhibition, facilitating guidance towards task-relevant stimuli. Our results provide novel insights on a mechanism in early visual regions that supports selective attention through inhibition.