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Record W4411009153 · doi:10.1002/hbm.70245

Mapping Caudolenticular Gray Matter Bridges in the Human Brain Striatum Through Diffusion Magnetic Resonance Imaging and Tractography

2025· article· en· W4411009153 on OpenAlexafffund
Graham Little, Charles Poirier, Arnaud Boré, Martin Parent, Laurent Petit, Maxime Descoteaux

Bibliographic record

VenueHuman Brain Mapping · 2025
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversité LavalUniversité de Sherbrooke
FundersNational Institute of Mental HealthNatural Sciences and Engineering Research Council of CanadaUniversité de Sherbrooke
KeywordsTractographyHuman Connectome ProjectDiffusion MRIPutamenWhite matterMagnetic resonance imagingHuman brainConnectomeStriatumNuclear magnetic resonanceCaudate nucleusArtificial intelligencePhysicsNeuroscienceComputer sciencePsychologyRadiologyMedicine

Abstract

fetched live from OpenAlex

In primates, the putamen and the caudate nucleus are connected by ~1 mm-thick caudolenticular gray matter bridges (CLGBs) interspersed between the white matter bundles of the internal capsule. Little is understood about the functional or microstructural properties of the CLGBs. In studies proposing high resolution diffusion magnetic resonance imaging (dMRI) techniques, CLGBs have been qualitatively identified as an example of superior imaging quality; however, the microstructural properties of these structures have yet to be examined. In this study, it is demonstrated for the first time that dMRI is sensitive to an organized anisotropic signal oriented in the direction parallel to the CLGBs, suggesting that dMRI could be a useful imaging method for probing the microstructure of the CLGBs. To demonstrate the anisotropic diffusion signal is coherently organized along the extent of the CLGBs and to enable a subsequent CLGB microstructural measurement, a customized tractography seeding and filtering method is proposed that utilizes the shape of the human striatum (putamen + caudate nucleus) to reconstruct the CLGBs in 3D. The proposed seeding strategy seeds tractography streamlines outward and normal to the surface of a 3D model of the striatum such that reconstructed streamlines are more likely to follow the diffusion signal peaks aligned parallel to the CLGBs. The method is applied to three different diffusion datasets, namely a high resolution 760 μm isotropic diffusion dataset acquired on a single subject, the test-retest cohort included as part of the human connectome project (N = 44) with diffusion data acquired at 1.25 mm isotropic, and a locally acquired "clinical" test-retest dataset acquired at 2.0 mm isotropic (N = 24). Reconstructed CLGBs directly overlap expected gray matter regions in the human brain for all three datasets. In addition, the method is shown to accurately reconstruct CLGBs repeatedly across multiple test-retest cohorts. The tractography CLGB reconstructions are then used to extract a quantitative measurement of microstructure from a local model of the diffusion signal along the CLGBs themselves. This is the first work to comprehensively study the CLGBs in vivo using dMRI and presents techniques suitable for future human neuroscience studies targeting these structures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.495
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.326
Teacher spread0.291 · 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 teacher head, 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

Citations1
Published2025
Admission routes2
Has abstractyes

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