Your browser doesn't support javascript.
loading
Do intrinsic brain functional networks predict working memory from childhood to adulthood?
Zhang, Han; Hao, Shuji; Lee, Annie; Eickhoff, Simon B; Pecheva, Diliana; Cai, Shirong; Meaney, Michael; Chong, Yap-Seng; Broekman, Birit F P; Fortier, Marielle V; Qiu, Anqi.
Afiliação
  • Zhang H; Department of Biomedical Engineering and Clinical Imaging Research Center, National University of Singapore, Singapore, Singapore.
  • Hao S; School of Computer Engineering and Science, Shanghai University, Shanghai, China.
  • Lee A; School of Computer Engineering and Science, Shanghai University, Shanghai, China.
  • Eickhoff SB; Department of Biomedical Engineering and Clinical Imaging Research Center, National University of Singapore, Singapore, Singapore.
  • Pecheva D; Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany.
  • Cai S; Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany.
  • Meaney M; Department of Biomedical Engineering and Clinical Imaging Research Center, National University of Singapore, Singapore, Singapore.
  • Chong YS; Singapore Institute for Clinical Sciences, Singapore, Singapore.
  • Broekman BFP; Singapore Institute for Clinical Sciences, Singapore, Singapore.
  • Fortier MV; Singapore Institute for Clinical Sciences, Singapore, Singapore.
  • Qiu A; Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Hum Brain Mapp ; 41(16): 4574-4586, 2020 11.
Article em En | MEDLINE | ID: mdl-33463860
ABSTRACT
Working memory (WM) is defined as the ability to maintain a representation online to guide goal-directed behavior. Its capacity in early childhood predicts academic achievements in late childhood and its deficits are found in various neurodevelopmental disorders. We employed resting-state fMRI (rs-fMRI) of 468 participants aged from 4 to 55 years and connectome-based predictive modeling (CPM) to explore the potential predictive power of intrinsic functional networks to WM in preschoolers, early and late school-age children, adolescents, and adults. We defined intrinsic functional networks among brain regions identified by activation likelihood estimation (ALE) meta-analysis on existing WM functional studies (ALE-based intrinsic functional networks) and intrinsic functional networks generated based on the whole brain (whole-brain intrinsic functional networks). We employed the CPM on these networks to predict WM in each age group. The CPM using the ALE-based and whole-brain intrinsic functional networks predicted WM of individual adults, while the prediction power of the ALE-based intrinsic functional networks was superior to that of the whole-brain intrinsic functional networks. Nevertheless, the CPM using the whole-brain but not the ALE-based intrinsic functional networks predicted WM in adolescents. And, the CPM using neither the ALE-based nor whole-brain networks predicted WM in any of the children groups. Our findings showed the trend of the prediction power of the intrinsic functional networks to cognition in individuals from early childhood to adulthood.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Conectoma / Desenvolvimento Humano / Memória de Curto Prazo / Rede Nervosa Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Singapura

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Conectoma / Desenvolvimento Humano / Memória de Curto Prazo / Rede Nervosa Idioma: En Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Singapura