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A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network

Goal-directed behavior often involves temporal separation and flexible context-dependent association between sensory input and motor output. The control of goal-directed behavior is proposed to lie in the frontoparietal network, but the computational architecture of this network remains elusive. Bas...

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Autores principales: Hwang, Eun Jung, Sato, Takashi R., Sato, Tatsuo K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8406690/
https://www.ncbi.nlm.nih.gov/pubmed/34475815
http://dx.doi.org/10.3389/fncir.2021.691314
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author Hwang, Eun Jung
Sato, Takashi R.
Sato, Tatsuo K.
author_facet Hwang, Eun Jung
Sato, Takashi R.
Sato, Tatsuo K.
author_sort Hwang, Eun Jung
collection PubMed
description Goal-directed behavior often involves temporal separation and flexible context-dependent association between sensory input and motor output. The control of goal-directed behavior is proposed to lie in the frontoparietal network, but the computational architecture of this network remains elusive. Based on recent rodent studies that measured and manipulated projection neurons in the frontoparietal network together with findings from earlier primate studies, we propose a canonical scheme of information flows in this network. The parietofrontal pathway transmits the spatial information of a sensory stimulus or internal motor bias to drive motor programs in the frontal areas. This pathway might consist of multiple parallel connections, each controlling distinct motor effectors. The frontoparietal pathway sends the spatial information of cognitively processed motor plans through multiple parallel connections. Each of these connections could support distinct spatial functions that use the motor target information, including attention allocation, multi-body part coordination, and forward estimation of movement state (i.e., forward models). The parallel pathways in the frontoparietal network enable dynamic interactions between regions that are tuned for specific goal-directed behaviors. This scheme offers a promising framework within which the computational architecture of the frontoparietal network and the underlying circuit mechanisms can be delineated in a systematic way, providing a holistic understanding of information processing in this network. Clarifying this network may also improve the diagnosis and treatment of behavioral deficits associated with dysfunctional frontoparietal connectivity in various neurological disorders including Alzheimer’s disease.
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spelling pubmed-84066902021-09-01 A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network Hwang, Eun Jung Sato, Takashi R. Sato, Tatsuo K. Front Neural Circuits Neural Circuits Goal-directed behavior often involves temporal separation and flexible context-dependent association between sensory input and motor output. The control of goal-directed behavior is proposed to lie in the frontoparietal network, but the computational architecture of this network remains elusive. Based on recent rodent studies that measured and manipulated projection neurons in the frontoparietal network together with findings from earlier primate studies, we propose a canonical scheme of information flows in this network. The parietofrontal pathway transmits the spatial information of a sensory stimulus or internal motor bias to drive motor programs in the frontal areas. This pathway might consist of multiple parallel connections, each controlling distinct motor effectors. The frontoparietal pathway sends the spatial information of cognitively processed motor plans through multiple parallel connections. Each of these connections could support distinct spatial functions that use the motor target information, including attention allocation, multi-body part coordination, and forward estimation of movement state (i.e., forward models). The parallel pathways in the frontoparietal network enable dynamic interactions between regions that are tuned for specific goal-directed behaviors. This scheme offers a promising framework within which the computational architecture of the frontoparietal network and the underlying circuit mechanisms can be delineated in a systematic way, providing a holistic understanding of information processing in this network. Clarifying this network may also improve the diagnosis and treatment of behavioral deficits associated with dysfunctional frontoparietal connectivity in various neurological disorders including Alzheimer’s disease. Frontiers Media S.A. 2021-08-12 /pmc/articles/PMC8406690/ /pubmed/34475815 http://dx.doi.org/10.3389/fncir.2021.691314 Text en Copyright © 2021 Hwang, Sato and Sato. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neural Circuits
Hwang, Eun Jung
Sato, Takashi R.
Sato, Tatsuo K.
A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network
title A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network
title_full A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network
title_fullStr A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network
title_full_unstemmed A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network
title_short A Canonical Scheme of Bottom-Up and Top-Down Information Flows in the Frontoparietal Network
title_sort canonical scheme of bottom-up and top-down information flows in the frontoparietal network
topic Neural Circuits
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8406690/
https://www.ncbi.nlm.nih.gov/pubmed/34475815
http://dx.doi.org/10.3389/fncir.2021.691314
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