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      Sounds facilitate visual motion discrimination via the enhancement of late occipital visual representations

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          Abstract

          Sensory discriminations, such as judgements about visual motion, often benefit from multisensory evidence. Despite many reports of enhanced brain activity during multisensory conditions, it remains unclear which dynamic processes implement the multisensory benefit for an upcoming decision in the human brain. Specifically, it remains difficult to attribute perceptual benefits to specific processes, such as early sensory encoding, the transformation of sensory representations into a motor response, or to more unspecific processes such as attention. We combined an audio-visual motion discrimination task with the single-trial mapping of dynamic sensory representations in EEG activity to localize when and where multisensory congruency facilitates perceptual accuracy. Our results show that a congruent sound facilitates the encoding of motion direction in occipital sensory - as opposed to parieto-frontal - cortices, and facilitates later - as opposed to early (i.e. below 100 ms) - sensory activations. This multisensory enhancement was visible as an earlier rise of motion-sensitive activity in middle-occipital regions about 350 ms from stimulus onset, which reflected the better discriminability of motion direction from brain activity and correlated with the perceptual benefit provided by congruent multisensory information. This supports a hierarchical model of multisensory integration in which the enhancement of relevant sensory cortical representations is transformed into a more accurate choice.

          Highlights

          • Feature specific multisensory integration occurs in sensory not amodal cortex.

          • Feature specific integration occurs late, i.e. around 350 ms post stimulus onset.

          • Acoustic and visual representations interact in occipital motion regions.

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          Most cited references90

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          Information-based functional brain mapping.

          The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. The complexity of the data creates a need for statistical summary, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest. In neuroimaging, for example, brain mapping analysis has focused on the discovery of activation, i.e., of extended brain regions whose average activity changes across experimental conditions. Here we propose to ask a more general question of the data: Where in the brain does the activity pattern contain information about the experimental condition? To address this question, we propose scanning the imaged volume with a "searchlight," whose contents are analyzed multivariately at each location in the brain.
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            On the interpretation of weight vectors of linear models in multivariate neuroimaging.

            The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
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              Is neocortex essentially multisensory?

              Although sensory perception and neurobiology are traditionally investigated one modality at a time, real world behaviour and perception are driven by the integration of information from multiple sensory sources. Mounting evidence suggests that the neural underpinnings of multisensory integration extend into early sensory processing. This article examines the notion that neocortical operations are essentially multisensory. We first review what is known about multisensory processing in higher-order association cortices and then discuss recent anatomical and physiological findings in presumptive unimodal sensory areas. The pervasiveness of multisensory influences on all levels of cortical processing compels us to reconsider thinking about neural processing in unisensory terms. Indeed, the multisensory nature of most, possibly all, of the neocortex forces us to abandon the notion that the senses ever operate independently during real-world cognition.
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                Author and article information

                Contributors
                Journal
                Neuroimage
                Neuroimage
                Neuroimage
                Academic Press
                1053-8119
                1095-9572
                01 March 2017
                01 March 2017
                : 148
                : 31-41
                Affiliations
                [0005]Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
                Author notes
                [* ]Corresponding author. Stephanie.Kayser@ 123456glasgow.ac.uk
                Article
                S1053-8119(17)30011-3
                10.1016/j.neuroimage.2017.01.010
                5349847
                28082107
                0e6c0619-e69d-40f9-8327-06facaa07ce7
                © 2017 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 28 October 2016
                : 5 January 2017
                Categories
                Article

                Neurosciences
                audio-visual,eeg,single trial decoding,sensory decision making,motion discrimination
                Neurosciences
                audio-visual, eeg, single trial decoding, sensory decision making, motion discrimination

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