Cortical thickness is related to working memory performance after non-invasive brain stimulation

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Tipo de produção
article
Data de publicação
2023
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Título do Volume
Editora
ASSOC BRAS DIVULG CIENTIFICA
Citação
BRAZILIAN JOURNAL OF MEDICAL AND BIOLOGICAL RESEARCH, v.56, article ID e12945, 8p, 2023
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Unidades Organizacionais
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Resumo
Non-invasive brain stimulation (NIBS) probing the dorsolateral prefrontal cortex (DLPFC) has been shown to have little effect on working memory. The variability of NIBS responses might be explained by inter-subject brain anatomical variability. We investigated whether baseline cortical brain thickness of regions of interest was associated with working memory performance after NIBS by performing a secondary analysis of previously published research. Structural magnetic resonance imaging data were analyzed from healthy subjects who received transcranial direct current stimulation (tDCS), intermittent theta-burst stimulation (iTBS), and placebo. Twenty-two participants were randomly assigned to receive all the interventions in a random order. The working memory task was conducted after the end of each NIBS session. Regions of interest were the bilateral DLPFC, medial prefrontal cortex, and posterior cingulate cortex. Overall, 66 NIBS sessions were performed. Findings revealed a negative significant association between cortical thickness of the bilateral dorsolateral prefrontal cortex and reaction time for both tDCS (left: P=0.045, right: P=0.037) and iTBS (left: P=0.007, right: P=0.007) compared to placebo. A significant positive association was found for iTBS and posterior cingulate cortex (P=0.03). No association was found for accuracy. Our findings provide the first evidence that individual cortical thickness of healthy subjects might be associated with working memory performance following different NIBS interventions. Therefore, cortical thickness could explain -to some extent -the heterogeneous effects of NIBS probing the DLPFC.
Palavras-chave
Non-invasive brain stimulation, Cortical thickness, Individualization, Working memory, Voxel-based morphometry
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