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      Organization of high-level visual cortex in human infants

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          Abstract

          How much of the structure of the human mind and brain is already specified at birth, and how much arises from experience? In this article, we consider the test case of extrastriate visual cortex, where a highly systematic functional organization is present in virtually every normal adult, including regions preferring behaviourally significant stimulus categories, such as faces, bodies, and scenes. Novel methods were developed to scan awake infants with fMRI, while they viewed multiple categories of visual stimuli. Here we report that the visual cortex of 4–6-month-old infants contains regions that respond preferentially to abstract categories (faces and scenes), with a spatial organization similar to adults. However, precise response profiles and patterns of activity across multiple visual categories differ between infants and adults. These results demonstrate that the large-scale organization of category preferences in visual cortex is adult-like within a few months after birth, but is subsequently refined through development.

          Abstract

          Adult visual cortex is organized into regions that respond to categories such as faces and scenes, but it is unclear if this depends on experience. Here, authors measured brain activity in 4–6 month old infants looking at faces and scenes and find that their visual cortex is organized similarly to adults.

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          Most cited references30

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          A cortical representation of the local visual environment.

          Medial temporal brain regions such as the hippocampal formation and parahippocampal cortex have been generally implicated in navigation and visual memory. However, the specific function of each of these regions is not yet clear. Here we present evidence that a particular area within human parahippocampal cortex is involved in a critical component of navigation: perceiving the local visual environment. This region, which we name the 'parahippocampal place area' (PPA), responds selectively and automatically in functional magnetic resonance imaging (fMRI) to passively viewed scenes, but only weakly to single objects and not at all to faces. The critical factor for this activation appears to be the presence in the stimulus of information about the layout of local space. The response in the PPA to scenes with spatial layout but no discrete objects (empty rooms) is as strong as the response to complex meaningful scenes containing multiple objects (the same rooms furnished) and over twice as strong as the response to arrays of multiple objects without three-dimensional spatial context (the furniture from these rooms on a blank background). This response is reduced if the surfaces in the scene are rearranged so that they no longer define a coherent space. We propose that the PPA represents places by encoding the geometry of the local environment.
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            A cortical area selective for visual processing of the human body.

            Despite extensive evidence for regions of human visual cortex that respond selectively to faces, few studies have considered the cortical representation of the appearance of the rest of the human body. We present a series of functional magnetic resonance imaging (fMRI) studies revealing substantial evidence for a distinct cortical region in humans that responds selectively to images of the human body, as compared with a wide range of control stimuli. This region was found in the lateral occipitotemporal cortex in all subjects tested and apparently reflects a specialized neural system for the visual perception of the human body.
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              Matching categorical object representations in inferior temporal cortex of man and monkey.

              Inferior temporal (IT) object representations have been intensively studied in monkeys and humans, but representations of the same particular objects have never been compared between the species. Moreover, IT's role in categorization is not well understood. Here, we presented monkeys and humans with the same images of real-world objects and measured the IT response pattern elicited by each image. In order to relate the representations between the species and to computational models, we compare response-pattern dissimilarity matrices. IT response patterns form category clusters, which match between man and monkey. The clusters correspond to animate and inanimate objects; within the animate objects, faces and bodies form subclusters. Within each category, IT distinguishes individual exemplars, and the within-category exemplar similarities also match between the species. Our findings suggest that primate IT across species may host a common code, which combines a categorical and a continuous representation of objects.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group
                2041-1723
                10 January 2017
                2017
                : 8
                : 13995
                Affiliations
                [1 ]Department of Brain and Cognitive Sciences and McGovern Institute, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, USA
                [2 ]Department of Psychology, Emory University , Atlanta, Georgia 30322, USA
                [3 ]Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital , Charlestown, Massachusetts 02129, USA
                [4 ]Institute of Medical Physics and Radiation Protection, Department of Life Science Engineering, Mittelhessen University of Applied Science , Giessen 35390, Germany
                [5 ]Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, USA
                Author notes
                Article
                ncomms13995
                10.1038/ncomms13995
                5234071
                28072399
                7121b4e5-1a34-4ffd-b94f-4170f15b697b
                Copyright © 2017, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 02 August 2016
                : 18 November 2016
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