Correlation detection as a stimulus computable account for audiovisual perception, causal inference, and saliency maps in mammals.

ABSTRACT: Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of stimulus-computable perceptual models fundamentally limits our understanding of how the brain extracts and combines task-relevant cues from the continuous flow of natural multisensory stimuli. Here, we introduce an image- and sound-computable population model for audiovisual perception, based on biologically plausible units that detect spatiotemporal correlations across auditory and visual streams. In a large-scale simulation spanning 69 psychophysical, eye-tracking, and pharmacological experiments, our model replicates human, monkey, and rat behaviour in response to diverse audiovisual stimuli

SUBMITTER: Parise CV 

PROVIDER: S-EPMC12585176 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature