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Neuroimage. 2017 Aug 15;157:144-156. doi: 10.1016/j.neuroimage.2017.05.053. Epub 2017 May 25.

Searching for behavior relating to grey matter volume in a-priori defined right dorsal premotor regions: Lessons learned.

Author information

1
Institute of Neuroscience and Medicine, INM-1/INM-7, Research Centre Jülich, Germany; GIGA-CRC In Vivo Imaging, University of Liege, Belgium; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany. Electronic address: s.genon@fz-juelich.de.
2
Institute of Neuroscience and Medicine, INM-1/INM-7, Research Centre Jülich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Germany; JARA - Translational Brain Medicine, Aachen.
3
Department of Artificial Intelligence, Donders Centre for Cognition, Radboud University Nijmegen, The Netherlands.
4
Institute of Neuroscience and Medicine, INM-1/INM-7, Research Centre Jülich, Germany.
5
Institute of Neuroscience and Medicine, INM-1/INM-7, Research Centre Jülich, Germany; C. u. O. Vogt-Institute for Brain Research, Heinrich-Heine-University Düsseldorf, Germany.
6
Department of Neurology, University of Cologne, Germany; Institute of Neuroscience and Medicine, INM-3, Research Centre Jülich, Germany.
7
Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Germany; JARA - Translational Brain Medicine, Aachen.
8
Institute of Neuroscience and Medicine, INM-1/INM-7, Research Centre Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany.

Abstract

Recently, we showed that the functional heterogeneity of the right dorsal premotor (PMd) cortex could be better understood by dividing it into five subregions that showed different behavioral associations according to task-based activations studies. The present study investigated whether the revealed behavioral profile could be corroborated and complemented by a structural brain behavior correlation approach in two healthy adults cohorts. Grey matter volume within the five volumes of interest (VOI-GM) was computed using voxel-based morphometry. Associations between the inter-individual differences in VOI-GM and performance across a range of neuropsychological tests were assessed in the two cohorts with and without correction for demographical variables. Additional analyses were performed in random smaller subsamples drawn from each of the two cohorts. In both cohorts, correlation coefficients were low; only few were significant and a considerable number of correlations were counterintuitive in their directions (i.e., higher performance related to lower grey matter volume). Furthermore, correlation patterns were inconsistent between the two cohorts. Subsampling revealed that correlation patterns could vary widely across small samples and that negative correlations were as likely as positive correlations. Thus, the structural brain-behavior approach did not corroborate the functional profiles of the PMd subregions inferred from activation studies, suggesting that local recruitment by fMRI studies does not necessarily imply covariance of local structure with behavioral performance in healthy adults. We discuss the limitations of such studies and related recommendations for future studies.

KEYWORDS:

Functional characterization; Replication; Structural brain behavior; Type S error; Voxel-based morphometry

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