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1.
Cereb Cortex ; 31(6): 3122-3135, 2021 05 10.
Artigo em Inglês | MEDLINE | ID: mdl-33585902

RESUMO

Human learning can be understood as a network phenomenon, underpinned by the adaptive reconfiguration of modular organization. However, the plasticity of community structure (CS) in resting-state network induced by cognitive intervention has never been investigated. Here, we explored the individual difference of intrinsic CS between children with 5-year abacus-based mental calculation (AMC) training (35 subjects) and their peers without prior experience in AMC (31 subjects). Using permutation-based analysis between subjects in the two groups, we found the significant alteration of intrinsic CS, with training-attenuated individual difference. The alteration of CS focused on selective subsets of cortical regions ("core areas"), predominantly affiliated to the visual, somatomotor, and default-mode subsystems. These subsystems exhibited training-promoted cohesion with attenuated interaction between them, from the perspective of individuals' CS. Moreover, the cohesion of visual network could predict training-improved math ability in the AMC group, but not in the control group. Finally, the whole network displayed enhanced segregation in the AMC group, including higher modularity index, more provincial hubs, lower participation coefficient, and fewer between-module links, largely due to the segregation of "core areas." Collectively, our findings suggested that the intrinsic CS could get reconfigured toward more localized processing and segregated architecture after long-term cognitive training.


Assuntos
Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Cognição/fisiologia , Rede Nervosa/diagnóstico por imagem , Rede Nervosa/fisiologia , Resolução de Problemas/fisiologia , Adaptação Fisiológica/fisiologia , Criança , Feminino , Humanos , Aprendizagem/fisiologia , Imageamento por Ressonância Magnética/métodos , Masculino , Conceitos Matemáticos , Fatores de Tempo
2.
Psych J ; 10(4): 566-573, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-33709543

RESUMO

Abacus-based mental calculation (AMC) training may improve mathematics-related abilities and transfer to other cognitive domains. Thus, it was hypothesized that inductive reasoning abilities can be improved by AMC training given the overlapping cognitive processes and neural correlates between AMC and inductive reasoning. The aim of the current study was to examine the underlying neurobiological mechanisms of this possible adaption by resting-state functional magnetic resonance imaging (rs-fMRI). Sixty-three children were randomly assigned to either the AMC-trained or the nontrained group. The AMC-trained group was required to perform abacus training for 2 hours per week for 5 years whereas the nontrained group was not required to perform any abacus training. Each participant's rs-fMRI data were collected after abacus training, and regional homogeneity (ReHo) analysis was performed to determine the neural activity differences between groups. The participants' posttraining mathematical ability, intelligence quotients, and inductive reasoning ability were recorded and evaluated. The results revealed that AMC-trained children exhibited a significantly higher mathematical ability and inductive reasoning performance and higher ReHo in the rostrolateral prefrontal cortex (RLPFC) compared to the nontrained group. In particular, the increased ReHo in the RLPFC was found to be positively correlated with improved inductive reasoning performance. Our findings suggest that rs-fMRI may reflect the modulation of training in task-related networks.


Assuntos
Encéfalo , Imageamento por Ressonância Magnética , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Criança , Humanos , Resolução de Problemas
3.
Front Hum Neurosci ; 14: 566675, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33424561

RESUMO

Numerical inductive reasoning has been considered as one of the most important higher cognitive functions of the human brain. Importantly, previous behavioral studies have consistently reported that one critical component of numerical inductive reasoning is checking, which often occurs when a discrepant element is discovered, and reprocessing is needed to determine whether the discrepancy is an error of the original series. However, less is known about the neural mechanism underlying the checking process. Given that the checking effect involves cognitive control processes, such as the incongruent resolution, that are linked to the right dorsolateral prefrontal cortex (DLPFC), this study hypothesizes that the right DLPFC may play a specific role in the checking process. To test the hypothesis, this study utilized the transcranial direct current stimulation (tDCS), a non-invasive brain stimulation method that could modulate cortical excitability, and examined whether and how the stimulation of the right DLPFC via tDCS could modulate the checking effect during a number-series completion problem task. Ninety healthy participants were allocated to one of the anodal, cathodal, and sham groups. Subjects were required to verify whether number sequences formed rule-based series, and checking effect was assessed by the difference in performance between invalid and valid conditions. It was found that significantly longer response times (RTs) were exhibited in invalid condition compared with valid condition in groups of anodal, cathodal, and sham tDCS. Furthermore, the anodal tDCS significantly shortened the checking effect than those of the cathodal and sham groups, whereas no significantly prolonged checking effect was detected in the cathodal group. The current findings indicated that anodal tDCS affected the process of checking, which suggested that the right DLPFC might play a critical role in the checking process of numerical inductive reasoning by inhibiting incongruent response.

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