Travis Powell¹ (), Megan Wong¹, Atticus Mackey¹, Mingzhou Ding², George R. Mangun¹; ¹University of California, Davis, ²University of Florida, Gainesville

Task performance fluctuates in the theta-band (4—8 Hz) when the deployment of visuospatial attention is sampled across a variable range of cue-target intervals. This behavioral periodicity bears evidence that attentional sampling of external stimuli is discrete. A conventional model of this phenomenon implicates the dorsal attention network (DAN) utilizing a common theta rhythm to coordinate oculomotor potentiation and visual sensitivity in an antiphasic relationship. This facilitates an orderly separation of shifting and sensing when scanning visual space. Recent evidence is emerging that extends these rhythmic behavioral findings to other domains, pointing toward an expanded model of rhythmic cognition. We contribute to this effort with a modified Posner paradigm, cueing participants to two temporally distinct variable ranges of target onsets, while acquiring scalp electroencephalography (EEG). Temporal attention recruits a cortical network distinguished from the DAN — notably by its exclusion of the FEF and reliance on the left intraparietal sulcus (LIPS) — thereby rendering it a useful candidate to extend the study of rhythmic attention beyond visual space. Mean reaction time oscillated predominantly in the theta band. Cue condition was decodable via support vector machines (SVM) trained on RT time series data, indicating a systematic effect of temporal cue on behavioral rhythms and suggesting temporal orienting modulates attentional rhythms. Topographical distribution of EEG, consistent with extant literature, provided confirmatory evidence that the temporal orienting network was recruited for the task. The relationship between behavioral rhythms and theta (4—8) and alpha (9—13 Hz) EEG bands in relevant electrode sites suggested RT oscillations covaried with activity in the temporal orienting network. These results indicate that temporal attention also utilizes oscillations to coordinate functions that share a common neural resource.