Information-Based Multivariate Decoding Reveals Neural Encoding of Attentional Interference During Visual Selective Attention

Visual attention is one of the fundamental abilities underlying human perception, learning, and goal-directed behavior, enabling individuals to prioritize information relevant to current goals while effectively suppressing irrelevant or competing stimuli. While previous studies have revealed the role of top-down attentional control mechanisms in visual processing, particularly in the anticipatory activation of brain regions during target expectation, the precise influence of this regulation on the neural decoding of targets and distractors remains underexplored. This study combines a classical visual search task with a developed multivariate decoding framework to systematically investigate the effects of distractor interference on the neural decoding of target location under conditions of prior spatial knowledge. Through multivariate decoding analysis, we compared the decoding accuracy of target locations in both T-only (only one unique shape-defined target) and T-with-D (shape-defined target with a distractor sharing the same shape) conditions. We found that distractor interference significantly reduced the precision of target location decoding and diminished the temporal generalization of target representations, indicating that interference disrupted the stability of neural decoding. Furthermore, decoding accuracy in both conditions was positively correlated with the amplitude of the N2pc component, further demonstrating the critical role of spatially selective attention in target location decoding. Although preprocessing was applied to the existing decoding methods in this study, it enhanced both the stability and decoding accuracy without affecting the overall trend of the results. Overall, these findings suggest that information-based multivariate decoding offers important empirical support for understanding the neural mechanisms of internal spatial attention under distraction.