Hemispheric Differences within the Fronto-Parietal Network Dynamics Underlying Spatial Imagery.
Hemispheric Differences within the Fronto-Parietal Network Dynamics Underlying Spatial Imagery.
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DOI:
10.3389/fpsyg.2012.00214
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发表时间:
2012
影响因子:
3.8
通讯作者:
Schuhmann T
中科院分区:
文献类型:
--
作者:
Sack AT;Schuhmann T
Spatial imagery refers to the inspection and evaluation of spatial features (e.g., distance, relative position, configuration) and/or the spatial manipulation (e.g., rotation, shifting, reorienting) of mentally generated visual images. In the past few decades, psychophysical as well as functional brain imaging studies have indicated that any such processing of spatially coded information and/or manipulation based on mental images (i) is subject to similar behavioral demands and limitations as in the case of spatial processing based on real visual images, and (ii) consistently activates several nodes of widely distributed cortical networks in the brain. These nodes include areas within both, the dorsal fronto-parietal as well as ventral occipito-temporal visual processing pathway, representing the “what” versus “where” aspects of spatial imagery. We here describe evidence from functional brain imaging and brain interference studies indicating systematic hemispheric differences within the dorsal fronto-parietal networks during the execution of spatial imagery. Importantly, such hemispheric differences and functional lateralization principles are also found in the effective brain network connectivity within and across these networks, with a direction of information flow from anterior frontal/premotor regions to posterior parietal cortices. In an attempt to integrate these findings of hemispheric lateralization and fronto-to-parietal interactions, we argue that spatial imagery constitutes a multifaceted cognitive construct that can be segregated in several distinct mental sub processes, each associated with activity within specific lateralized fronto-parietal (sub) networks, forming the basis of the here proposed dynamic network model of spatial imagery.
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