Rethinking simultaneous suppression in visual cortex via compressive spatiotemporal population receptive fields

• Published in: Nature communications 2024-08, Vol.15 (1), p.6885-19, Article 6885
• Main Authors: Kupers, Eline R., Kim, Insub, Grill-Spector, Kalanit
• Format: Article
• Language: English
• Subjects: 59/36; 631/378/116/2395; 631/378/2613/2614; 631/378/2649/1723; 631/477/2811; Adult; Brain Mapping; Computational neuroscience; Female; Functional magnetic resonance imaging; Humanities and Social Sciences; Humans; Hypotheses; Information processing; Magnetic Resonance Imaging; Male; Models, Neurological; multidisciplinary; Neurons; Photic Stimulation; Receptive field; Science; Science (multidisciplinary); Visual cortex; Visual Cortex - diagnostic imaging; Visual Cortex - physiology; Visual fields; Visual Fields - physiology; Visual Perception - physiology; Visual stimuli; Visual tasks; Young Adult
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-024-51243-7

When multiple visual stimuli are presented simultaneously in the receptive field, the neural response is suppressed compared to presenting the same stimuli sequentially. The prevailing hypothesis suggests that this suppression is due to competition among multiple stimuli for limited resources within receptive fields, governed by task demands. However, it is unknown how stimulus-driven computations may give rise to simultaneous suppression. Using fMRI, we find simultaneous suppression in single voxels, which varies with both stimulus size and timing, and progressively increases up the visual hierarchy. Using population receptive field (pRF) models, we find that compressive spatiotemporal summation rather than compressive spatial summation predicts simultaneous suppression, and that increased simultaneous suppression is linked to larger pRF sizes and stronger compressive nonlinearities. These results necessitate a rethinking of simultaneous suppression as the outcome of stimulus-driven compressive spatiotemporal computations within pRFs, and open new opportunities to study visual processing capacity across space and time. With fMRI and computational models, Kupers et al. found that visually-driven neural computations in space and time, rather than limited neural sources, explain why brain responses are lower when we view multiple things at once vs one after the other.