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      Decoding Sound and Imagery Content in Early Visual Cortex

      brief-report
      1 , 2 , , 1 , 3 , 1 , ∗∗
      Current Biology
      Cell Press

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          Summary

          Human early visual cortex was traditionally thought to process simple visual features such as orientation, contrast, and spatial frequency via feedforward input from the lateral geniculate nucleus (e.g., [ 1]). However, the role of nonretinal influence on early visual cortex is so far insufficiently investigated despite much evidence that feedback connections greatly outnumber feedforward connections [ 2–5]. Here, we explored in five fMRI experiments how information originating from audition and imagery affects the brain activity patterns in early visual cortex in the absence of any feedforward visual stimulation. We show that category-specific information from both complex natural sounds and imagery can be read out from early visual cortex activity in blindfolded participants. The coding of nonretinal information in the activity patterns of early visual cortex is common across actual auditory perception and imagery and may be mediated by higher-level multisensory areas. Furthermore, this coding is robust to mild manipulations of attention and working memory but affected by orthogonal, cognitively demanding visuospatial processing. Crucially, the information fed down to early visual cortex is category specific and generalizes to sound exemplars of the same category, providing evidence for abstract information feedback rather than precise pictorial feedback. Our results suggest that early visual cortex receives nonretinal input from other brain areas when it is generated by auditory perception and/or imagery, and this input carries common abstract information. Our findings are compatible with feedback of predictive information to the earliest visual input level (e.g., [ 6]), in line with predictive coding models [ 7–10].

          Highlights

          • Early visual cortex receives nonretinal input carrying abstract information

          • Both auditory perception and imagery generate consistent top-down input

          • Information feedback may be mediated by multisensory areas

          • Feedback is robust to attentional, but not visuospatial, manipulation

          Abstract

          Vetter et al. show that category-specific information from both complex natural sounds and imagery can be read out from early visual cortex activity in blindfolded participants. This is evidence for nonretinal abstract information feedback to early visual cortex, compatible with predictive coding models.

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          Most cited references41

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          Decoding reveals the contents of visual working memory in early visual areas

          Visual working memory provides an essential link between perception and higher cognitive functions, allowing for the active maintenance of information regarding stimuli no longer in view1,2. Research suggests that sustained activity in higher-order prefrontal, parietal, inferotemporal and lateral occipital areas supports visual maintenance3-11, and may account for working memory’s limited capacity to hold up to 3-4 items9-11. Because higher-order areas lack the visual selectivity of early sensory areas, it has remained unclear how observers can remember specific visual features, such as the precise orientation of a grating, with minimal decay in performance over delays of many seconds12. One proposal is that sensory areas serve to maintain fine-tuned feature information13, but early visual areas show little to no sustained activity over prolonged delays14-16. Using fMRI decoding methods17, here we show that orientations held in working memory can be decoded from activity patterns in the human visual cortex, even when overall levels of activity are low. Activity patterns in areas V1-V4 could predict which of two oriented gratings was held in memory with mean accuracy levels upwards of 80%, even in participants exhibiting activity that fell to baseline levels after a prolonged delay. These orientation-selective activity patterns were sustained throughout the delay period, evident in individual visual areas, and similar to the responses evoked by unattended, task-irrelevant gratings. Our results demonstrate that early visual areas can retain specific information about visual features held in working memory, over periods of many seconds when no physical stimulus is present.
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            The proactive brain: using analogies and associations to generate predictions.

            Moshe Bar (2007)
            Rather than passively 'waiting' to be activated by sensations, it is proposed that the human brain is continuously busy generating predictions that approximate the relevant future. Building on previous work, this proposal posits that rudimentary information is extracted rapidly from the input to derive analogies linking that input with representations in memory. The linked stored representations then activate the associations that are relevant in the specific context, which provides focused predictions. These predictions facilitate perception and cognition by pre-sensitizing relevant representations. Predictions regarding complex information, such as those required in social interactions, integrate multiple analogies. This cognitive neuroscience framework can help explain a variety of phenomena, ranging from recognition to first impressions, and from the brain's 'default mode' to a host of mental disorders.
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              On the computational architecture of the neocortex. II. The role of cortico-cortical loops.

              D. Mumford (1992)
              This paper is a sequel to an earlier paper which proposed an active role for the thalamus, integrating multiple hypotheses formed in the cortex via the thalamo-cortical loop. In this paper, I put forward a hypothesis on the role of the reciprocal, topographic pathways between two cortical areas, one often a 'higher' area dealing with more abstract information about the world, the other 'lower', dealing with more concrete data. The higher area attempts to fit its abstractions to the data it receives from lower areas by sending back to them from its deep pyramidal cells a template reconstruction best fitting the lower level view. The lower area attempts to reconcile the reconstruction of its view that it receives from higher areas with what it knows, sending back from its superficial pyramidal cells the features in its data which are not predicted by the higher area. The whole calculation is done with all areas working simultaneously, but with order imposed by synchronous activity in the various top-down, bottom-up loops. Evidence for this theory is reviewed and experimental tests are proposed. A third part of this paper will deal with extensions of these ideas to the frontal lobe.
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                Author and article information

                Contributors
                Journal
                Curr Biol
                Curr. Biol
                Current Biology
                Cell Press
                0960-9822
                1879-0445
                02 June 2014
                02 June 2014
                : 24
                : 11
                : 1256-1262
                Affiliations
                [1 ]Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, College of Medical, Veterinary and Life Sciences, University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, UK
                [2 ]Laboratory for Behavioral Neurology and Imaging of Cognition, Department of Neuroscience, Medical School and Swiss Center for Affective Sciences, University of Geneva, Campus Biotech, Case Postale 60, 1211 Geneva, Switzerland
                Author notes
                []Corresponding author petra.vetter@ 123456unige.ch
                [∗∗ ]Corresponding author lars.muckli@ 123456glasgow.ac.uk
                [3]

                Present address: School of Psychology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK

                Article
                S0960-9822(14)00458-8
                10.1016/j.cub.2014.04.020
                4046224
                24856208
                0690f9d8-a236-436c-bab0-e53a96cf8bde
                © 2014 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/).

                History
                : 29 November 2013
                : 28 February 2014
                : 8 April 2014
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                Life sciences
                Life sciences

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