Functional subdivisions in the anterior temporal lobes: a large scale meta-analytic investigation.


Journal

Neuroscience and biobehavioral reviews
ISSN: 1873-7528
Titre abrégé: Neurosci Biobehav Rev
Pays: United States
ID NLM: 7806090

Informations de publication

Date de publication:
08 2020
Historique:
received: 17 12 2019
revised: 11 04 2020
accepted: 15 05 2020
pubmed: 30 5 2020
medline: 22 6 2021
entrez: 30 5 2020
Statut: ppublish

Résumé

The anterior temporal lobe (ATL) is involved in a wide range of cognitive processes but its functional specialization remains unclear. In this review, we synthesize evidence from cytoarchitecture, anatomical and functional connectivity, and functional activation to elucidate how subregions in the ATL contribute to various cognitive processes. Two complementary meta-analyses were conducted. We first constructed a comprehensive functional preference profile for all subregions through large-scale neuroimaging meta-analysis, and then employed a coordinate-based activation likelihood estimation analysis to examine such functional preferences by input types. We identified two subregions in the dorsal aspect of the ATL (i.e., superior dorsal, inferior dorsal) and two other subregions (lateral, ventromedial) in the ventral aspect of the ATL, all have distinct anatomical and functional preferences. We proposed sensory, language, and socioemotion as the three dimensions that jointly capture the cognitive components cutting across the four ATL subregions: the superior dorsal ATL was associated with auditory sensory, language (phonological production aspects), and emotion; the inferior dorsal ATL with auditory sensory and language (phonological perception and production aspects); the lateral ATL with visual sensory, language (semantic and episodic aspects), and social processing; and the ventromedial ATL with visual sensory, episodic memory, and emotion. The various functions associated with the ATL can be clustered into subregions, which provides sourceful basis for testing hypothesis-driven cognitive framework.

Identifiants

pubmed: 32470478
pii: S0149-7634(20)30411-5
doi: 10.1016/j.neubiorev.2020.05.008
pii:
doi:

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

134-145

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare no competing interests.

Auteurs

Jinyi Hung (J)

State Key Laboratory of Cognitive Neuroscience and Learning & IDG, McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.

Xiaoying Wang (X)

State Key Laboratory of Cognitive Neuroscience and Learning & IDG, McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.

Xiaosha Wang (X)

State Key Laboratory of Cognitive Neuroscience and Learning & IDG, McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.

Yanchao Bi (Y)

State Key Laboratory of Cognitive Neuroscience and Learning & IDG, McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China. Electronic address: ybi@bnu.edu.cn.

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Classifications MeSH