Corcoles-Parada, M., Muller, N. C. J., Ubero, M., Serrano-dol-Pueblo, V.M., Mansilla, F., Marcos-Rabal, P., Artacho-Perula, E., Dresler, M., Insausti, R., Fernandez, G. and Munoz-Lopez, M. (2017) Anatomical segmentation of the human medial prefrontal cortex. [Data Collection]
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The medial prefrontal areas 32, 24, 14, and 25 (mPFC) form part of the limbic memory system, but little is known about their functional specialization in humans. To add anatomical precision to structural and functional magnetic resonance imaging (MRI) data, we aimed to identify these mPFC subareas in histological preparations of human brain tissue, determine sulci most consistently related with mPFC areal boundaries, and use these sulci to delineate mPFC areas in MRIs. To achieve this, we obtained three-dimensional MRI data from 11 ex vivo hemispheres and processed them for cyto- and myelo-architectonic analysis. The architectonic boundaries of mPFC areas were identified in histology and cortical surface length and volumes were measured. Unfolded maps of histologically determined boundaries were generated to identify the association of mPFC areal boundaries with sulci across cases. This analysis showed that cingulate and superior rostral were the sulci most consistently related to mPFC areal boundaries. Based on presence/absence and anastomosis between such sulci, 6 sulci patterns in the 11 hemispheres were found. A further analysis of 102 hemispheres of in vivo MRI scans (N = 51 males, mean ± SD 24.1 ± 3.1 years of age) showed similar sulci patterns, which allowed us to delineate the mFPC areas in them. The volumes of mPFC areas across histological, ex vivo and in vivo MRI delineations were comparable and probabilistic maps generated from the MRIs of the102 hemispheres. Probabilistic maps of mPFC areas were registered to MNI space and are available for regional analysis of functional magnetic resonance imaging data.
| College / School: | College of Medical Veterinary and Life Sciences > School of Life Sciences |
|---|---|
| Date Deposited: | 14 Jun 2017 12:03 |
| Enlighten Publications URL: | http://eprints.gla.ac.uk/139316/ |
| URI: | https://researchdata.gla.ac.uk/id/eprint/403 |
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