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- de Flores, Robin, et al.
(författare)
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Characterization of hippocampal subfields using ex vivo MRI and histology data : Lessons for in vivo segmentation
- 2020
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Ingår i: Hippocampus. - : Wiley. - 1050-9631 .- 1098-1063. ; 30:6, s. 545-564
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Tidskriftsartikel (refereegranskat)abstract
- Hippocampal subfield segmentation on in vivo MRI is of great interest for cognition, aging, and disease research. Extant subfield segmentation protocols have been based on neuroanatomical references, but these references often give limited information on anatomical variability. Moreover, there is generally a mismatch between the orientation of the histological sections and the often anisotropic coronal sections on in vivo MRI. To address these issues, we provide a detailed description of hippocampal anatomy using a postmortem dataset containing nine specimens of subjects with and without dementia, which underwent a 9.4 T MRI and histological processing. Postmortem MRI matched the typical orientation of in vivo images and segmentations were generated in MRI space, based on the registered annotated histological sections. We focus on the following topics: the order of appearance of subfields, the location of subfields relative to macroanatomical features, the location of subfields in the uncus and tail and the composition of the dark band, a hypointense layer visible in T2-weighted MRI. Our main findings are that: (a) there is a consistent order of appearance of subfields in the hippocampal head, (b) the composition of subfields is not consistent in the anterior uncus, but more consistent in the posterior uncus, (c) the dark band consists only of the CA-stratum lacunosum moleculare, not the strata moleculare of the dentate gyrus, (d) the subiculum/CA1 border is located at the middle of the width of the hippocampus in the body in coronal plane, but moves in a medial direction from anterior to posterior, and (e) the variable location and composition of subfields in the hippocampal tail can be brought back to a body-like appearance when reslicing the MRI scan following the curvature of the tail. Our findings and this publicly available dataset will hopefully improve anatomical accuracy of future hippocampal subfield segmentation protocols.
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| 2. |
- Coogan, Matthew A, et al.
(författare)
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Examining behavioral and attitudinal differences among groups in their traffic safety culture
- 2014
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Ingår i: Transportation Research Part F. - : Elsevier BV. - 1369-8478 .- 1873-5517. ; 26:PB, s. 303-316
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Tidskriftsartikel (refereegranskat)abstract
- The paper explores the concept that, for a given population, there is not a single "traffic safety culture," but rather a set of alternative cultures in which the individual driver might belong. There are several different cultures of dangerous driving behavior and each might need a separate strategy for intervention or amelioration.First, the paper summarizes the over-arching theory explored in the research, which applies Multi-group Structural Equation Modeling (MSEM) in a modification of the Theory of Planned Behavior (TPB) in the explanation of Risky Driving Behavior, based on ten observed explanatory factors.Second, we apply Latent Class Cluster (LCC) segmentation to the full sample, revealing four segments: one cluster reflecting a "Low Risk Driving Safety Group" and three clusters describing three different groups of problematic drivers. We first apply MSEM to two groups; the "Low Risk Driving Safety Group," and the "High Risk Driving Safety Group," defined as the members of the three problematic clusters together, revealing how a "Low Risk" culture differs from the "High Risk" culture, with the relative importance of the TPB explanatory factors varying sharply between the two groups.Finally, the three problematic clusters are profiled for demographics and their mean scores for the ten observed explanatory factors. Each of the clusters is reviewed in terms of responses to selected survey questions.Three separate and distinct dangerous traffic safety cultures emerge: first, a culture of risky driving dominated by excitement seeking and optimism bias; a second dominated by denial of societal values; and a third characterized by its propensity to find rational justifications for its speeding behavior.The paper applies two research methods together: LCC segmentation divides our sample into meaningful subgroups, while MSEM reveals both within-group analysis of variance and between-group differences in safety attitudes and outcomes. The paper concludes that the combination of the segmentation powers of the LCC and the analysis powers of the MSEM provides the analyst with an improved understanding of the attitudes and behaviors of the separate groups, all tied back to the over-arching theory underlying the research.
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