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      Coexisting representations of sensory and mnemonic information in human visual cortex

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          Abstract

          Traversing sensory environments requires keeping relevant information in mind while simultaneously processing new inputs. Visual information is kept in working memory via feature selective responses in early visual cortex, but recent work had suggested that new sensory inputs obligatorily wipe out this information. Here we show region-wide multiplexing abilities in classic sensory areas, with population-level response patterns in early visual cortex representing the contents of working memory alongside new sensory inputs. In a second experiment, we show that when people get distracted, this leads to both disruptions of mnemonic information in early visual cortex and decrements in behavioral recall. Representations in the intraparietal sulcus reflect actively remembered information encoded in a transformed format, but not task-irrelevant sensory inputs. Together these results suggest that early visual areas play a key role in supporting high resolution working memory representations that can serve as a template for comparing incoming sensory information.

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          Most cited references60

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          How does the brain solve visual object recognition?

          Mounting evidence suggests that 'core object recognition,' the ability to rapidly recognize objects despite substantial appearance variation, is solved in the brain via a cascade of reflexive, largely feedforward computations that culminate in a powerful neuronal representation in the inferior temporal cortex. However, the algorithm that produces this solution remains poorly understood. Here we review evidence ranging from individual neurons and neuronal populations to behavior and computational models. We propose that understanding this algorithm will require using neuronal and psychophysical data to sift through many computational models, each based on building blocks of small, canonical subnetworks with a common functional goal. Copyright © 2012 Elsevier Inc. All rights reserved.
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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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              ‘Activity-silent’ working memory in prefrontal cortex: a dynamic coding framework

              Highlights • WM is thought to depend on persistent maintenance of stationary activity states. • However, population-level analyses reveal that brain activity is highly dynamic. • Accumulating evidence implicates activity-silent neural states for WM. • Dynamic coding suggests that WM is encoded in patterns of functional connectivity.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                24 May 2019
                01 July 2019
                August 2019
                01 January 2020
                : 22
                : 8
                : 1336-1344
                Affiliations
                [1 ]Psychology Department, University of California San Diego, La Jolla, California, USA
                [2 ]Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands
                [3 ]Neurosciences Graduate Program, University of California San Diego, La Jolla, California, USA
                [4 ]Kavli Institute for Brain and Mind, University of California, San Diego, La Jolla, CA 92093
                Author notes

                Author contribution statement: This study was designed by RLR, CC, and JTS. Data were collected by RLR and CC, and RLR preprocessed the data. RLR and JTS did the main analyses and wrote the manuscript.

                Article
                NIHMS1529569
                10.1038/s41593-019-0428-x
                6857532
                31263205
                af069fe3-cce4-4e91-96a9-b75a07c54524

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                Neurosciences
                Neurosciences

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