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      Auditory modulation of visual stimulus encoding in human retinotopic cortex

      research-article
      * , , ,
      Neuroimage
      Academic Press
      Multisensory, Audio-visual, V2, Decoding, MVPA, fMRI

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          Abstract

          Sounds can modulate visual perception as well as neural activity in retinotopic cortex. Most studies in this context investigated how sounds change neural amplitude and oscillatory phase reset in visual cortex. However, recent studies in macaque monkeys show that congruence of audio-visual stimuli also modulates the amount of stimulus information carried by spiking activity of primary auditory and visual neurons. Here, we used naturalistic video stimuli and recorded the spatial patterns of functional MRI signals in human retinotopic cortex to test whether the discriminability of such patterns varied with the presence and congruence of co-occurring sounds. We found that incongruent sounds significantly impaired stimulus decoding from area V2 and there was a similar trend for V3. This effect was associated with reduced inter-trial reliability of patterns (i.e. higher levels of noise), but was not accompanied by any detectable modulation of overall signal amplitude. We conclude that sounds modulate naturalistic stimulus encoding in early human retinotopic cortex without affecting overall signal amplitude. Subthreshold modulation, oscillatory phase reset and dynamic attentional modulation are candidate neural and cognitive mechanisms mediating these effects.

          Highlights

          ► Multivariate decoding of video identity from fMRI signals in V1V3. ► Decoding accuracy in V2 is significantly reduced for incongruent sounds. ► Reduced decoding accuracy is associated with reduced inter-trial reliability. ► No modulation of univariate signal amplitude by sounds. ► Noise levels in sensory areas are affected by multisensory congruence.

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          Most cited references47

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          From sensation to cognition.

          M. Mesulam (1998)
          Sensory information undergoes extensive associative elaboration and attentional modulation as it becomes incorporated into the texture of cognition. This process occurs along a core synaptic hierarchy which includes the primary sensory, upstream unimodal, downstream unimodal, heteromodal, paralimbic and limbic zones of the cerebral cortex. Connections from one zone to another are reciprocal and allow higher synaptic levels to exert a feedback (top-down) influence upon earlier levels of processing. Each cortical area provides a nexus for the convergence of afferents and divergence of efferents. The resultant synaptic organization supports parallel as well as serial processing, and allows each sensory event to initiate multiple cognitive and behavioural outcomes. Upstream sectors of unimodal association areas encode basic features of sensation such as colour, motion, form and pitch. More complex contents of sensory experience such as objects, faces, word-forms, spatial locations and sound sequences become encoded within downstream sectors of unimodal areas by groups of coarsely tuned neurons. The highest synaptic levels of sensory-fugal processing are occupied by heteromodal, paralimbic and limbic cortices, collectively known as transmodal areas. The unique role of these areas is to bind multiple unimodal and other transmodal areas into distributed but integrated multimodal representations. Transmodal areas in the midtemporal cortex, Wernicke's area, the hippocampal-entorhinal complex and the posterior parietal cortex provide critical gateways for transforming perception into recognition, word-forms into meaning, scenes and events into experiences, and spatial locations into targets for exploration. All cognitive processes arise from analogous associative transformations of similar sets of sensory inputs. The differences in the resultant cognitive operation are determined by the anatomical and physiological properties of the transmodal node that acts as the critical gateway for the dominant transformation. Interconnected sets of transmodal nodes provide anatomical and computational epicentres for large-scale neurocognitive networks. In keeping with the principles of selectively distributed processing, each epicentre of a large-scale network displays a relative specialization for a specific behavioural component of its principal neurospychological domain. The destruction of transmodal epicentres causes global impairments such as multimodal anomia, neglect and amnesia, whereas their selective disconnection from relevant unimodal areas elicits modality-specific impairments such as prosopagnosia, pure word blindness and category-specific anomias. The human brain contains at least five anatomically distinct networks. The network for spatial awareness is based on transmodal epicentres in the posterior parietal cortex and the frontal eye fields; the language network on epicentres in Wernicke's and Broca's areas; the explicit memory/emotion network on epicentres in the hippocampal-entorhinal complex and the amygdala; the face-object recognition network on epicentres in the midtemporal and temporopolar cortices; and the working memory-executive function network on epicentres in the lateral prefrontal cortex and perhaps the posterior parietal cortex. Individual sensory modalities give rise to streams of processing directed to transmodal nodes belonging to each of these networks. The fidelity of sensory channels is actively protected through approximately four synaptic levels of sensory-fugal processing. The modality-specific cortices at these four synaptic levels encode the most veridical representations of experience. Attentional, motivational and emotional modulations, including those related to working memory, novelty-seeking and mental imagery, become increasingly more pronounced within downstream components of unimodal areas, where they help to create a highly edited subjective version of the world. (ABSTRACT TRUNCATED)
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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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              The free-energy principle: a rough guide to the brain?

              This article reviews a free-energy formulation that advances Helmholtz's agenda to find principles of brain function based on conservation laws and neuronal energy. It rests on advances in statistical physics, theoretical biology and machine learning to explain a remarkable range of facts about brain structure and function. We could have just scratched the surface of what this formulation offers; for example, it is becoming clear that the Bayesian brain is just one facet of the free-energy principle and that perception is an inevitable consequence of active exchange with the environment. Furthermore, one can see easily how constructs like memory, attention, value, reinforcement and salience might disclose their simple relationships within this framework.
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                Author and article information

                Journal
                Neuroimage
                Neuroimage
                Neuroimage
                Academic Press
                1053-8119
                1095-9572
                15 April 2013
                15 April 2013
                : 70
                : 100
                : 258-267
                Affiliations
                UCL Institute of Cognitive Neuroscience, 17 Queen Square, London WC1N 3BG, UK
                Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3AR, UK
                Author notes
                [* ]Corresponding author at: Institute of Cognitive Neuroscience, University College London, Alexandra House, 17 Queen Square, London WC1N 3AR, UK. benjamin.haas.09@ 123456ucl.ac.uk
                Article
                YNIMG10063
                10.1016/j.neuroimage.2012.12.061
                3625122
                23296187
                2fa887df-1bc9-4fd4-b203-9874739982fc
                © 2013 Elsevier Inc.

                This document may be redistributed and reused, subject to certain conditions.

                History
                : 23 December 2012
                Categories
                Article

                Neurosciences
                multisensory,audio-visual,v2,decoding,mvpa,fmri
                Neurosciences
                multisensory, audio-visual, v2, decoding, mvpa, fmri

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