Imagery for shapes activates position-invariant representations in human visual cortex.

In this study, we show that top-down control mechanisms engaged during visual imagery of simple shapes (letters X and O) can selectively activate position-invariant perceptual codes in visual areas specialised for shape processing, including lateral occipital complex (LOC). First, we used multivoxel...

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Main Authors: Stokes, M, Saraiva, A, Rohenkohl, G, Nobre, A
Format: Journal article
Language:English
Published: 2011
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author Stokes, M
Saraiva, A
Rohenkohl, G
Nobre, A
author_facet Stokes, M
Saraiva, A
Rohenkohl, G
Nobre, A
author_sort Stokes, M
collection OXFORD
description In this study, we show that top-down control mechanisms engaged during visual imagery of simple shapes (letters X and O) can selectively activate position-invariant perceptual codes in visual areas specialised for shape processing, including lateral occipital complex (LOC). First, we used multivoxel pattern analysis (MVPA) to identify visual cortical areas that code for shape within a position-invariant reference frame. Next, we examined the similarity between these high-level visual codes and patterns elicited while participants imagined the corresponding stimulus at central fixation. Our results demonstrate that imagery engages object-centred codes in higher-level visual areas. More generally, our results also demonstrate that top-down control mechanisms are able to generate highly specific patterns of visual activity in the absence of corresponding sensory input. We argue that a general model of top-down control must account for dynamic modulation of functional connectivity between high-level control centres and overlapping neural codes in visual cortex.
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spelling oxford-uuid:ea47d34b-3fec-442a-8f8c-a8cb137a36f32022-03-27T11:00:49ZImagery for shapes activates position-invariant representations in human visual cortex.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:ea47d34b-3fec-442a-8f8c-a8cb137a36f3EnglishSymplectic Elements at Oxford2011Stokes, MSaraiva, ARohenkohl, GNobre, AIn this study, we show that top-down control mechanisms engaged during visual imagery of simple shapes (letters X and O) can selectively activate position-invariant perceptual codes in visual areas specialised for shape processing, including lateral occipital complex (LOC). First, we used multivoxel pattern analysis (MVPA) to identify visual cortical areas that code for shape within a position-invariant reference frame. Next, we examined the similarity between these high-level visual codes and patterns elicited while participants imagined the corresponding stimulus at central fixation. Our results demonstrate that imagery engages object-centred codes in higher-level visual areas. More generally, our results also demonstrate that top-down control mechanisms are able to generate highly specific patterns of visual activity in the absence of corresponding sensory input. We argue that a general model of top-down control must account for dynamic modulation of functional connectivity between high-level control centres and overlapping neural codes in visual cortex.
spellingShingle Stokes, M
Saraiva, A
Rohenkohl, G
Nobre, A
Imagery for shapes activates position-invariant representations in human visual cortex.
title Imagery for shapes activates position-invariant representations in human visual cortex.
title_full Imagery for shapes activates position-invariant representations in human visual cortex.
title_fullStr Imagery for shapes activates position-invariant representations in human visual cortex.
title_full_unstemmed Imagery for shapes activates position-invariant representations in human visual cortex.
title_short Imagery for shapes activates position-invariant representations in human visual cortex.
title_sort imagery for shapes activates position invariant representations in human visual cortex
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AT saraivaa imageryforshapesactivatespositioninvariantrepresentationsinhumanvisualcortex
AT rohenkohlg imageryforshapesactivatespositioninvariantrepresentationsinhumanvisualcortex
AT nobrea imageryforshapesactivatespositioninvariantrepresentationsinhumanvisualcortex