Temporal binding in multisensory and motor-sensory contexts: toward a unified model

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dc.contributor.author Jagini, Kishore Kumar
dc.coverage.spatial Switzerland
dc.date.accessioned 2021-04-01T15:04:33Z
dc.date.available 2021-04-01T15:04:33Z
dc.date.issued 2021-03
dc.identifier.citation Jagini, Kishore Kumar, "Temporal binding in multisensory and motor-sensory contexts: toward a unified model", Frontiers in Human Neuroscience, DOI: 10.3389/fnhum.2021.629437, vol. 15, Mar. 2021. en_US
dc.identifier.issn 1662-5161
dc.identifier.uri https://doi.org/10.3389/fnhum.2021.629437
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/6399
dc.description.abstract Our senses receive a manifold of sensory signals at any given moment in our daily lives. For a coherent and unified representation of information and precise motor control, our brain needs to temporally bind the signals emanating from a common causal event and segregate others. Traditionally, different mechanisms were proposed for the temporal binding phenomenon in multisensory and motor-sensory contexts. This paper reviews the literature on the temporal binding phenomenon in both multisensory and motor-sensory contexts and suggests future research directions for advancing the field. Moreover, by critically evaluating the recent literature, this paper suggests that common computational principles are responsible for the temporal binding in multisensory and motor-sensory contexts. These computational principles are grounded in the Bayesian framework of uncertainty reduction rooted in the Helmholtzian idea of unconscious causal inference.
dc.description.statementofresponsibility by Kishore Kumar Jagini
dc.format.extent vol. 15
dc.language.iso en_US en_US
dc.publisher Frontiers Media en_US
dc.subject Temporal binding en_US
dc.subject Multisensory en_US
dc.subject Motor-sensory en_US
dc.subject Causal inference en_US
dc.subject Bayesian models en_US
dc.subject Precision en_US
dc.title Temporal binding in multisensory and motor-sensory contexts: toward a unified model en_US
dc.type Article en_US
dc.relation.journal Frontiers in Human Neuroscience


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