Selective attention warps the representation of space throughout cortical visual networks
Poster Presentation: Monday, May 19, 2025, 8:30 am – 12:30 pm, Pavilion
Session: Attention: Features, objects
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Jen D. Holmberg1, Emily X. Meschke1, Yuerou Tang1, Amanda LeBel1, Jack L. Gallant1; 1UC Berkeley
Visual attention systems in the brain selectively enhance visual information that is relevant to the target or goal (Cukur et al., 2013). Most object-based visual attention studies have focused on how attention affects the representations of high-level semantic categories or objects. However, high-level semantic category representations rely on the integration of low-level visual representations from earlier stages of visual processing. Given that the visual system is densely interconnected, it is important to understand how object-based attention modulates low-level visual representations to facilitate downstream object-based perception. Here we examine whether object-based attention affects spatial representations across cortical regions of interest (ROIs) during a naturalistic movie-watching task. Six participants watched compilations of movie clips either while fixating passively or while covertly searching for “humans” or “vehicles” in the movies (Cukur et al., 2013). High-level semantic features and low-level visual features were recovered from the movies, and these were used to fit voxelwise encoding models to predict brain responses in each participant, under each attention condition (Dupré la Tour et al., 2022). Task-specific functional networks were recovered using model connectivity (Meschke et al., 2022), and were used as ROIs in the analyses. To assess semantic representation changes across attention conditions, the semantic model weights were correlated with ‘human’ and ‘vehicle’ semantic templates (as in Cukur et al., 2013). To assess spatial representation changes across attention conditions, the visual model weights were correlated with a spatial template that partitioned the visual field into ‘center’ and ‘periphery’. These analyses revealed that selective attention to either semantic target shifts spatial representations towards the periphery in the majority of networks. Furthermore, in some networks, the magnitude of the spatial representation shift was correlated with the magnitude of the semantic representation shift. These results suggest that object-based selective attention is supported by changes in low-level spatial representations.