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Record W4390198182 · doi:10.1002/alz.081707

Comparison of histological delineation of the entorhinal, perirhinal, ectorhinal, and parahippocampal cortices by different neuroanatomy laboratories

2023· article· en· W4390198182 on OpenAlexaff
Hannah Baumeister, Anika Wuestefeld, Jenna N. Adams, Arnold Bakker, Ana M. Daugherty, Robin de Florès, Carl J. Hodgetts, Renaud La Joie, Negar Mazloum‐Farzaghi, Rosanna K. Olsen, Vyash Puliyadi, Craig E.L. Stark, Tammy Tran, Lei Wang, Paul A. Yushkevich, Katrin Amunts, Jean C. Augustinack, Song‐Lin Ding, Ricardo Insausti, Olga Kedo, David Berron, Laura E.M. Wisse

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsCytoarchitecturePerirhinal cortexEntorhinal cortexNeuroscienceParahippocampal gyrusCortex (anatomy)Posterior commissureTemporal cortexNeuroanatomyTemporal lobeCommissureAnatomyBiologyHippocampus

Abstract

fetched live from OpenAlex

Abstract Background The medial temporal lobe (MTL) cortex, located adjacent to the hippocampus, is crucial for memory and a hotspot of neurodegenerative processes (e.g., accumulation of tau tangles or TDP‐43). Importantly, the MTL cortex comprises several subregions with distinct functional, cytoarchitectonic, and macro‐anatomical features (Fig. 1). In vivo imaging studies measuring atrophy or aggregates of pathologies in these subregions rely on various segmentation protocols. Comparability of these imaging studies is limited as segmentation protocols differ, which results from different macro‐anatomical parcellations and cytoarchitectonic definitions of MTL subregions. Thus, it must be clarified to which extent definitions of MTL subregions overlap between neuroanatomists, to establish a harmonized MTL magnetic resonance imaging (MRI) segmentation protocol. We give an overview of cytoarchitectonic definitions of MTL cortex subregions provided by four neuroanatomists from independent laboratories. Method Four neuroanatomists performed annotations of the entorhinal cortex, Brodmann area (BA) 35, BA36, and the parahippocampal cortex on digital histology images. Nissl‐stained series were acquired in three specimens (Fig. 2). Slices (50µm thick) were prepared perpendicular to the anterior commissure‐posterior comimssure line spanning the entire longitudinal extent of the MTL cortex. Neuroanatomists annotated MTL cortex subdivisions on digitized (20X resolution) slices with 5mm spacing. Parcellations, terminology, and delineations were compared between neuroanatomists. Result Cytoarchitectonic features of the MTL cortex subregions are described in detail. Overall, we observed higher agreement in the definition of the entorhinal cortex and BA35, while definitions of BA36 and the parahippocampal cortex exhibited less overlap between neuroanatomists (Fig. 2). The degree of overlap of cytoarchitectonic definitions was reflected in the neuroanatomists’ agreement on the respective delineations. Lower agreement on annotations was observed for transitional zones where gradual changes from one subregion to another occur (Fig. 3). Due to the gradual transition of features from, for example, proisocortex to periallocortex, border placement is difficult to determine according to the neuroanatomists. Conclusion The results highlight that definitions and parcellations of the MTL cortex are variable but increase understanding of why these differences arise. This sets a crucial foundation for a harmonized in vivo MRI segmentation protocol for cortical MTL subregions and the study of these regions in the context of dementia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.103
GPT teacher head0.352
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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