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Poster Session B: Wednesday, August 13, 1:00 – 4:00 pm, de Brug & E‑Hall

Early Sensory Responses Track High-Level Visual Surprise

David Richter¹, Paula Pena, María Ruz; ¹Universidad de Granada

Presenter: David Richter

Predictive processing theories propose that the brain continuously generates expectations about incoming sensory information and compares these predictions to actual inputs, resulting in sensory prediction errors. However, it remains unclear which stimulus features are predicted by the brain and hence which errors drive neural responses. Here, we addressed this question by recording EEG while participants viewed object images that were expected or unexpected based on probabilistic cues. We used a deep neural network to quantify low- and high-level visual representational distances between expected and unexpected stimuli. Neural activity was then regressed onto these surprise metrics. Results showed a modulation of evoked activity over occipital electrodes approximately 200ms after stimulus onset by high-level, but not low-level, visual surprise. These findings suggest that high-level visual predictions are rapidly integrated into sensory processing.

Topic Area: Predictive Processing & Cognitive Control

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