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Prefrontal connectomics: from anatomy to human imaging

The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from...

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Autores principales: Haber, Suzanne N., Liu, Hesheng, Seidlitz, Jakob, Bullmore, Ed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617085/
https://www.ncbi.nlm.nih.gov/pubmed/34584210
http://dx.doi.org/10.1038/s41386-021-01156-6
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author Haber, Suzanne N.
Liu, Hesheng
Seidlitz, Jakob
Bullmore, Ed
author_facet Haber, Suzanne N.
Liu, Hesheng
Seidlitz, Jakob
Bullmore, Ed
author_sort Haber, Suzanne N.
collection PubMed
description The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic “hard wiring” first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas.
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spelling pubmed-86170852021-12-10 Prefrontal connectomics: from anatomy to human imaging Haber, Suzanne N. Liu, Hesheng Seidlitz, Jakob Bullmore, Ed Neuropsychopharmacology Review Article The fundamental importance of prefrontal cortical connectivity to information processing and, therefore, disorders of cognition, emotion, and behavior has been recognized for decades. Anatomic tracing studies in animals have formed the basis for delineating the direct monosynaptic connectivity, from cells of origin, through axon trajectories, to synaptic terminals. Advances in neuroimaging combined with network science have taken the lead in developing complex wiring diagrams or connectomes of the human brain. A key question is how well these magnetic resonance imaging (MRI)-derived networks and hubs reflect the anatomic “hard wiring” first proposed to underlie the distribution of information for large-scale network interactions. In this review, we address this challenge by focusing on what is known about monosynaptic prefrontal cortical connections in non-human primates and how this compares to MRI-derived measurements of network organization in humans. First, we outline the anatomic cortical connections and pathways for each prefrontal cortex (PFC) region. We then review the available MRI-based techniques for indirectly measuring structural and functional connectivity, and introduce graph theoretical methods for analysis of hubs, modules, and topologically integrative features of the connectome. Finally, we bring these two approaches together, using specific examples, to demonstrate how monosynaptic connections, demonstrated by tract-tracing studies, can directly inform understanding of the composition of PFC nodes and hubs, and the edges or pathways that connect PFC to cortical and subcortical areas. Springer International Publishing 2021-09-28 2022-01 /pmc/articles/PMC8617085/ /pubmed/34584210 http://dx.doi.org/10.1038/s41386-021-01156-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Article
Haber, Suzanne N.
Liu, Hesheng
Seidlitz, Jakob
Bullmore, Ed
Prefrontal connectomics: from anatomy to human imaging
title Prefrontal connectomics: from anatomy to human imaging
title_full Prefrontal connectomics: from anatomy to human imaging
title_fullStr Prefrontal connectomics: from anatomy to human imaging
title_full_unstemmed Prefrontal connectomics: from anatomy to human imaging
title_short Prefrontal connectomics: from anatomy to human imaging
title_sort prefrontal connectomics: from anatomy to human imaging
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8617085/
https://www.ncbi.nlm.nih.gov/pubmed/34584210
http://dx.doi.org/10.1038/s41386-021-01156-6
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