Margaret L. Duffy¹ (), M. Fiona Molloy², David E. Osher¹; ¹The Ohio State University, ²University of Michigan

The brain has the ability to filter and prioritize a cacophony of often extraneous visual stimuli via a mechanism called attention. Traditionally, attention is thought to be guided by either a goal-driven mechanism (top-down, supported by fronto-parietal brain networks) or a stimulus-driven mechanism (bottom-up, supported by visual networks). However, recent work has highlighted a type of attention that does not fit within this dichotomy: one guided by memory. There are multiple forms of memory, including habitual memory - inflexible, insensitive to outcome devaluation, and automatic. Contextual cueing has arguably demonstrated habit-like attention, but effect sizes are very small, especially for individual subjects. Within the domain of habit research, serial reaction time (SRT) tasks have demonstrated habitual properties; however, this type of task typically is used for motor habits. For the present study, we adapted the SRT with spatial-temporal demands to probe habit-like attention. Participants were tasked with making decisions about stimuli that appeared in blocks alternating between learned and novel locations. We assessed participants’ knowledge of the learned sequence with a short post-test that asked them to predict the next location of the image in this sequence. Finally, we altered the learned sequence to test perseveration errors of the attentional habit. This task produces very large reaction time and accuracy effects for the learned spatiotemporal attentional sequence, demonstrable in individual subjects. Participants appeared to possess explicit knowledge of the learned sequence, however, challenging the inclusion of implicitness as a criterion for attentional habits. Further, the altered sequence demonstrated a difference in reaction time between critical (altered) and non-critical trials in the learned sequence, and a trending effect for accuracy. Future directions include the implementation of the task using a more complex learned sequence and a more highly powered reversal task. This study is part of an undergraduate honors thesis.

Acknowledgements: Alkire Research Fund, Undergraduate Research Scholarship (Ohio State)