Schedule of Events | Symposia

How States of Attention Are Represented by EEG Microstate Temporal Dynamics

Poster Session A - Saturday, March 29, 2025, 3:00 – 5:00 pm EDT, Back Bay Ballroom/Republic Ballroom

David DiStefano¹ (david.distefano@tufts.edu); ¹Tufts University

Our ability to focus attention can change over short periods of time, where one moment may be characterized as an “in-the-zone” state of attention that is passive yet efficient, and the next moment may be characterized as “out-of-the-zone” where focus lapses and attentional control must be re-exerted back to a task at hand. However, it is not well understood how the brain exhibits neural markers of these attentional states at fast time scales. The present work analyzes EEG microstates as a robust, and promising way of understanding the spatial-temporal neural dynamics of attentional states in the context of a continuous performance task in which participants promptly press a button in response to target images in a visual detection task. To identify epochs of these attentional states, a well-validated measure of response time variability is used as an objective marker of behavioral attention. Microstate topographies are discovered using a spatialized k-means algorithm which converges to seven representative microstate maps (A through G). The microstate analyses presented focus on quantitative differences in classical univariate measures and first-order transition probabilities compared between the two states of attention. Results reveal that univariate measures of global field power, duration, and proportion of microstate C are more prevalent during the ”out-of-the-zone” periods. Transition probabilities also differed between attentional states, with more frequent transitions from microstate C to D, and G to D during “out-of-the-zone” compared to “in-the-zone” periods. These results indicate that momentary attentional states are well represented by patterns of short-lived (~100 msec) spatial-temporal microstates.

Topic Area: ATTENTION: Nonspatial