Dataset Information

Spatial probability maps of the segments of the postcentral sulcus in the human brain.

ABSTRACT: The postcentral sulcus is the posterior boundary of the postcentral gyrus where the somatosensory cortex is represented. In the human brain, the postcentral sulcus is composed of five distinct segments that are related to the somatosensory representation of different parts of the body. Segment 1 of the postcentral sulcus, located near the dorsomedial boundary of each hemisphere, is associated with toe/leg representations, segment 2 with arm/hand representations, segment 3 with blinking, and segments 4 and 5, which are near the lateral fissure and the parietal operculum, with the mouth and tongue representations. The variability in location and spatial extent of these five segments were quantified in 40 magnetic resonance imaging (MRI) anatomical brain scans registered to the stereotaxic space of the Montreal Neurological Institute (MNI space), in the form of volumetric (using MINC Toolkit) and surface (using FreeSurfer) spatial probability maps. These probability maps can be used by researchers and clinicians to improve the localization of the segments of the postcentral sulcus in MRI images of interest and also to improve the interpretation of the location of activation peaks generated in functional neuroimaging studies investigating somatosensory cortex.

SUBMITTER: Zlatkina V

PROVIDER: S-EPMC9433426 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Spatial probability maps of the segments of the postcentral sulcus in the human brain.

Zlatkina Veronika V Sprung-Much Trisanna T Petrides Michael M

Cerebral cortex (New York, N.Y. : 1991) 20220801 17

The postcentral sulcus is the posterior boundary of the postcentral gyrus where the somatosensory cortex is represented. In the human brain, the postcentral sulcus is composed of five distinct segments that are related to the somatosensory representation of different parts of the body. Segment 1 of the postcentral sulcus, located near the dorsomedial boundary of each hemisphere, is associated with toe/leg representations, segment 2 with arm/hand representations, segment 3 with blinking, and segm ...[more]

PMID: 34963136

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Project description:ObjectivesTo compare single parameter thresholding with multivariable probabilistic classification of ischemic stroke regions in the analysis of computed tomography perfusion (CTP) parameter maps.MethodsPatients were included from two multicenter trials and were divided into two groups based on their modified arterial occlusive lesion grade. CTP parameter maps were generated with three methods-a commercial method (ISP), block-circulant singular value decomposition (bSVD), and non-linear regression (NLR). Follow-up non-contrast CT defined the follow-up infarct region. Conventional thresholds for individual parameter maps were established with a receiver operating characteristic curve analysis. Probabilistic classification was carried out with a logistic regression model combining the available CTP parameters into a single probability.ResultsA total of 225 CTP data sets were included, divided into a group of 166 patients with successful recanalization and 59 with persistent occlusion. The precision and recall of the CTP parameters were lower individually than when combined into a probability. The median difference [interquartile range] in mL between the estimated and follow-up infarct volume was 29/23/23 [52/50/52] (ISP/bSVD/NLR) for conventional thresholding and was 4/6/11 [31/25/30] (ISP/bSVD/NLR) for the probabilistic classification.ConclusionsMultivariable probability maps outperform thresholded CTP parameter maps in estimating the infarct lesion as observed on follow-up non-contrast CT. A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.Key points• Combining CTP parameters with a logistic regression model increases the precision and recall in estimating ischemic stroke regions. • Volumes following from a probabilistic analysis predict follow-up infarct volumes better than volumes following from a threshold-based analysis. • A multivariable probabilistic approach may harmonize the classification of ischemic stroke regions.

Dataset Information

Spatial probability maps of the segments of the postcentral sulcus in the human brain.

Publications

Spatial probability maps of the segments of the postcentral sulcus in the human brain.

Similar Datasets

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