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A framework for identification of a resting-bold connectome associated with cognitive reserve
The concept of cognitive reserve proposes that specific life experiences result in more flexible or resilient cognitive processing allowing some people to cope better with age- or disease-related brain changes than others. Imaging studies seeking to understand the neural implementation of cognitive...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10114917/ https://www.ncbi.nlm.nih.gov/pubmed/33639257 http://dx.doi.org/10.1016/j.neuroimage.2021.117875 |
Sumario: | The concept of cognitive reserve proposes that specific life experiences result in more flexible or resilient cognitive processing allowing some people to cope better with age- or disease-related brain changes than others. Imaging studies seeking to understand the neural implementation of cognitive reserve have most often used task-related fMRI studies. Using that approach, we recently described a task-invariant cognitive-reserve network whose expression correlated with IQ and that moderated between cortical thickness and cognitive performance. Here we sought to identify a pattern of resting BOLD connectivity related to cognitive reserve. We identified a connectome pattern whose connectivity correlated with IQ in both the derivation sample and a separate replication sample. The majority of the edges showing positive relationships with IQ implicate frontal regions. In the derivation sample, connectivity either moderated the relationship between mean cortical thickness and a set of cognitive outcomes or accounted for unique variance in cognitive performance after accounting for cortical thickness. In a replication sample we found that expression of this connectome correlated significantly with the primary endpoint of IQ, and also accounted for unique variance in cognitive performance beyond cortical thickness. Our findings represent an intermediate level of replication and are unlikely to have arisen purely by type-I error. This connectivity pattern therefore meets some of our theoretical criteria for a cognitive reserve-related network and provides insight into the neural implementation of cognitive reserve. Further, expression of this connectome could potentially be used as a direct measure of cognitive reserve, and as an outcome measure for intervention studies that seek to influence cognitive reserve. Future validation of and re-derivation of the pattern in expanded data sets by our and other groups will lead to further improved estimates of cognitive reserve in resting functional connectivity. |
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