Evidence map›Paper›PMID 37615057›Full record

ArticleHuman brain mapping2023

Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion MRI.

Bradley G Karat, Jordan DeKraker, Uzair Hussain, Stefan Köhler, Ali R Khan

Abstract read
In one paragraph

Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Quantitative MRI of the hippocampus reveals microstructural trajectories of aging and Alzheimer's disease pathology.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  13. Hippocampal grey matter changes across scales in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025
    Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Bradley G KaratRobarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.ORCID 0000-0002-6550-1418
Jordan DeKrakerRobarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.
Uzair HussainUniversity Health Network, Toronto, Ontario, Canada.ORCID 0000-0003-3349-058X
Stefan KöhlerDepartment of Psychology, University of Western Ontario, London, Ontario, Canada.
Ali R KhanRobarts Research Institute, Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada.

Funding

Canadian Institute for Health Research 366062
6 · The paper itself

Abstract

The hippocampus is classically divided into mesoscopic subfields which contain varying microstructure that contribute to their unique functional roles. It has been challenging to characterize this microstructure with current magnetic resonance based neuroimaging techniques. In this work, we used diffusion magnetic resonance imaging (dMRI) and a novel surface-based approach in the hippocampus which revealed distinct microstructural distributions of neurite density and dispersion, T1w/T2w ratio as a proxy for myelin content, fractional anisotropy, and mean diffusivity. We used the neurite orientation dispersion and density imaging (NODDI) model optimized for grey matter diffusivity to characterize neurite density and dispersion. We found that neurite dispersion was highest in the cornu ammonis (CA) 1 and subiculum subfields which likely captures the large heterogeneity of tangential and radial fibres, such as the Schaffer collaterals, perforant path, and pyramidal neurons. Neurite density and T1w/T2w were highest in the subiculum and CA3 and lowest in CA1, which may reflect known myeloarchitectonic differences between these subfields. Using a simple logistic regression model, we showed that neurite density, dispersion, and T1w/T2w measures were separable across the subfields, suggesting that they may be sensitive to the known variability in subfield cyto- and myeloarchitecture. We report macrostructural measures of gyrification, thickness, and curvature that were in line with ex vivo descriptions of hippocampal anatomy. We employed a multivariate orthogonal projective non-negative matrix factorization (OPNNMF) approach to capture co-varying regions of macro- and microstructure across the hippocampus. The clusters were highly variable along the medial-lateral (proximal-distal) direction, likely reflecting known differences in morphology, cytoarchitectonic profiles, and connectivity. Finally, we show that by examining the main direction of diffusion relative to canonical hippocampal axes, we could identify regions with stereotyped microstructural orientations that may map onto specific fibre pathways, such as the Schaffer collaterals, perforant path, fimbria, and alveus. These results highlight the value of combining in vivo dMRI with computational approaches for capturing hippocampal microstructure, which may provide useful features for understanding cognition and for diagnosis of disease states.

Indexed as

Diffusion Tensor ImagingWhite MatterDiffusion Magnetic Resonance ImagingGray MatterHippocampusHumansNeuritesNeuroimagingdiffusion MRIhippocampusmicrostructureneurite densityneurite dispersionsubfields

Identifiers

PMID37615057
PMCPMC10543110

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.