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Category-specific activations depend on imaging mode, task demand, and stimuli modality: An ALE meta-analysis.
Derderian, Kimberly D; Zhou, Xiaojue; Chen, Lang.
Afiliação
  • Derderian KD; Neuroscience Program, Santa Clara University, United States.
  • Zhou X; Department of Cognitive Sciences, University of California at Irvine, United States.
  • Chen L; Neuroscience Program, Santa Clara University, United States; Department of Psychology, Santa Clara University, United States. Electronic address: lchen4@scu.edu.
Neuropsychologia ; 161: 108002, 2021 10 15.
Article em En | MEDLINE | ID: mdl-34450136
ABSTRACT
The cortical organization of the semantic network has been examined extensively in neuropsychological and neuroimaging studies; however, after decades of research, several issues remain controversial. A comprehensive and systematic investigation is needed to characterize the consistent patterns of category-specific activations as well as to examine factors that contribute to the varying findings across numerous neuroimaging studies. In this study, we reviewed 113 published papers that reported category-specific activations for living or nonliving concepts from the past two decades. Using the Activation Likelihood Estimate (ALE) method, we characterized the brain regions associated with living and nonliving concepts and revealed how the observed patterns were heavily influenced by methodological factors including imaging mode, task demand, and stimuli modality. Our findings provided the most comprehensive summary of category-specific activations for living and nonliving concepts and critically revealed that these activation patterns are highly contextually dependent. This work advanced our knowledge about the organization of the cortical semantic network and provided important insights into theoretical accounts and future research directions.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Conhecimento / Neuroimagem Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Conhecimento / Neuroimagem Idioma: En Ano de publicação: 2021 Tipo de documento: Article