Brain signatures indexing variation in internal processing during perceptual decision-making.

ABSTRACT: Brain activity is highly variable during simple and cognitively demanding tasks ^1,2 impacting performance ^3,4 . Discovering, characterizing, and linking variability in brain activity to internal processes has primarily relied on experimentally inducing changes (e.g., via attention manipulation) to identify neuronal and behavioral consequences ⁵ or studying spontaneous changes in ongoing brain dynamics ⁶ . However, changes in internal processing could arise from many factors, such as variation in strategy or arousal ⁷ , that are independent of experimental conditions ⁸ . Here we utilize a data-driven clustering method based on modularity-maximation to identify consistent spatial-temporal EEG activity patterns across individual trials and relate this activity to behavioral performance. Subjects (N = 25) performed a motion direction discrimination task with six interleaved levels of motion coherence. We identify two subsets of trials, Subtype 1 and Subtype 2, with distinct spatial-temporal brain activity. Surprisingly, even though Subtype 1 occurred more frequently with lower motion coherences, it was nonetheless associated with faster response times. Computational modeling suggested that Subtype 1 was characterized by a lower amount of information required to reach a decision. These results open a new way to identify brain states relevant to cognition and behavior not associated with experimental factors.

SUBMITTER: Nakuci J 

PROVIDER: S-EPMC9882071 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature