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Updated: Jun 9, 2025

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
Published on: January 23, 2017
Distinguishing expectation and attention effects in processing temporal patterns of visual input
Joann Huizhen Tang1, Selina S Solomon1, Adam Kohn2
1Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.
Abstract:
The current study investigated how the brain sets up expectations from stimulus regularities by evaluating the neural responses to expectations driven implicitly (by the stimuli themselves) and explicitly (by task demands). How the brain uses prior information to create expectations and what role attention plays in forming or holding predictions to efficiently respond to incoming sensory information is still debated. We presented temporal patterns of visual input while recording EEG under two different task conditions. When the patterns were task-relevant and pattern recognition was required to perform the button press task, three different event-related brain potentials (ERPs) were elicited, each reflecting a different aspect of pattern expectation. In contrast, when the patterns were task-irrelevant, none of the neural indicators of pattern recognition or pattern violation detection were observed to the same temporally structured sequences. Thus, results revealed a clear distinction between expectation and attention that was prompted by task requirements. These results provide complementary pieces of evidence that implicit exposure to a stimulus pattern may not be sufficient to drive neural effects of expectations that lead to predictive error responses. Task-driven attentional control can dissociate from stimulus-driven expectations, to effectively minimize distracting information and maximize attentional regulation.

