Neuroimaging techniques are now widely used to understand relationships between brain features and cognitive performance. Nevertheless, studies do not always implicate the same anatomical neural networks in intellectual function. Here we used T1-weighted brain MRI scans obtained from a sample of 82 healthy young adults to study four potential sources of variability affecting the reproducibility of brain-cognition relationships: the neuroimaging protocol used, different measures of cortical gray matter, ...
Neuroimaging techniques are now widely used to understand relationships between brain features and cognitive performance. Nevertheless, studies do not always implicate the same anatomical neural networks in intellectual function. Here we used T1-weighted brain MRI scans obtained from a sample of 82 healthy young adults to study four potential sources of variability affecting the reproducibility of brain-cognition relationships: the neuroimaging protocol used, different measures of cortical gray matter, the nature of the cognitive measurement, and sample characteristics. We found that brain networks implicated in individual differences in cognition were not consistent when derived from different gray matter measures, or from different surface-based processing pipelines, even in equivalent samples of participants. Differences in the networks associated with cognition may reflect differences in the methods used to analyze them; in addition, different individuals may reach equivalent psychological goals through disparate brain networks.
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