Identifying and Quantifying Multisensory Integration: A Tutorial Review

We process information from the world through multiple senses, and the brain must decide what information belongs together and what information should be segregated. One challenge in studying such multisensory integration is how to quantify the multisensory interactions, a challenge that is amplifie...

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Veröffentlicht in:Brain topography 2014-11, Vol.27 (6), p.707-730
Hauptverfasser: Stevenson, Ryan A., Ghose, Dipanwita, Fister, Juliane Krueger, Sarko, Diana K., Altieri, Nicholas A., Nidiffer, Aaron R., Kurela, LeAnne R., Siemann, Justin K., James, Thomas W., Wallace, Mark T.
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Sprache:eng
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Zusammenfassung:We process information from the world through multiple senses, and the brain must decide what information belongs together and what information should be segregated. One challenge in studying such multisensory integration is how to quantify the multisensory interactions, a challenge that is amplified by the host of methods that are now used to measure neural, behavioral, and perceptual responses. Many of the measures that have been developed to quantify multisensory integration (and which have been derived from single unit analyses), have been applied to these different measures without much consideration for the nature of the process being studied. Here, we provide a review focused on the means with which experimenters quantify multisensory processes and integration across a range of commonly used experimental methodologies. We emphasize the most commonly employed measures, including single- and multiunit responses, local field potentials, functional magnetic resonance imaging, and electroencephalography, along with behavioral measures of detection, accuracy, and response times. In each section, we will discuss the different metrics commonly used to quantify multisensory interactions, including the rationale for their use, their advantages, and the drawbacks and caveats associated with them. Also discussed are possible alternatives to the most commonly used metrics.
ISSN:0896-0267
1573-6792
DOI:10.1007/s10548-014-0365-7