Cross-correlation between auditory and visual signals promotes multisensory integration. 2013

Cesare V Parise, and Vanessa Harrar, and Marc O Ernst, and Charles Spence
Max Planck Institute for Biological Cybernetics and Bernstein Center for Computational Neuroscience, Tübingen, Germany. cesare.parise@uni-bielefeld.de

Humans are equipped with multiple sensory channels that provide both redundant and complementary information about the objects and events in the world around them. A primary challenge for the brain is therefore to solve the 'correspondence problem', that is, to bind those signals that likely originate from the same environmental source, while keeping separate those unisensory inputs that likely belong to different objects/events. Whether multiple signals have a common origin or not must, however, be inferred from the signals themselves through a causal inference process. Recent studies have demonstrated that cross-correlation, that is, the similarity in temporal structure between unimodal signals, represents a powerful cue for solving the correspondence problem in humans. Here we provide further evidence for the role of the temporal correlation between auditory and visual signals in multisensory integration. Capitalizing on the well-known fact that sensitivity to crossmodal conflict is inversely related to the strength of coupling between the signals, we measured sensitivity to crossmodal spatial conflicts as a function of the cross-correlation between the temporal structures of the audiovisual signals. Observers' performance was systematically modulated by the cross-correlation, with lower sensitivity to crossmodal conflict being measured for correlated as compared to uncorrelated audiovisual signals. These results therefore provide support for the claim that cross-correlation promotes multisensory integration. A Bayesian framework is proposed to interpret the present results, whereby stimulus correlation is represented on the prior distribution of expected crossmodal co-occurrence.

UI MeSH Term Description Entries
D010775 Photic Stimulation Investigative technique commonly used during ELECTROENCEPHALOGRAPHY in which a series of bright light flashes or visual patterns are used to elicit brain activity. Stimulation, Photic,Visual Stimulation,Photic Stimulations,Stimulation, Visual,Stimulations, Photic,Stimulations, Visual,Visual Stimulations
D001931 Brain Mapping Imaging techniques used to colocalize sites of brain functions or physiological activity with brain structures. Brain Electrical Activity Mapping,Functional Cerebral Localization,Topographic Brain Mapping,Brain Mapping, Topographic,Functional Cerebral Localizations,Mapping, Brain,Mapping, Topographic Brain
D003463 Cues Signals for an action; that specific portion of a perceptual field or pattern of stimuli to which a subject has learned to respond. Cue
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000161 Acoustic Stimulation Use of sound to elicit a response in the nervous system. Auditory Stimulation,Stimulation, Acoustic,Stimulation, Auditory
D001307 Auditory Perception The process whereby auditory stimuli are selected, organized, and interpreted by the organism. Auditory Processing,Perception, Auditory,Processing, Auditory
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D014796 Visual Perception The selecting and organizing of visual stimuli based on the individual's past experience. Visual Processing,Perception, Visual,Processing, Visual

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