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Record W2172252744 · doi:10.1002/ana.20030

Diffusion tensor fiber tracking shows distinct corticostriatal circuits in humans

2004· article· en· W2172252744 on OpenAlexaff
Stéphane Lehéricy, Mathieu Ducros, Pierre‐François Van de Moortele, Chantal François, Lionel Thivard, Cyril Poupon, Nick Swindale, Kǎmil Uǧurbil, Dae‐Shik Kim

Bibliographic record

VenueAnnals of Neurology · 2004
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNational Center for Research ResourcesW. M. Keck Foundation
KeywordsNeuroscienceDiffusion MRIStriatumTracingFunctional magnetic resonance imagingPsychologyComputer scienceMagnetic resonance imagingMedicine

Abstract

fetched live from OpenAlex

A landmark of corticostriatal connectivity in nonhuman primates is that cortical connections are organized into a set of discrete circuits. Each circuit is assumed to perform distinct behavioral functions. In animals, most connectivity studies are performed using invasive tracing methods, which are nonapplicable in humans. To test the proposal that corticostriatal connections are organized as multiple circuits in humans, we used diffusion tensor imaging axonal tracking, a new magnetic resonance technique that allows demonstration of fiber tracts in a noninvasive manner. Diffusion tensor imaging-based fiber tracking showed that the posterior (sensorimotor), anterior (associative), and ventral (limbic) compartments of the human striatum have specific connections with the cortex, and particularly the frontal lobes. These results provide the first direct demonstration of distinct corticostriatal connections in humans.

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)0.000
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.168
GPT teacher head0.395
Teacher spread0.227 · 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

Citations550
Published2004
Admission routes1
Has abstractyes

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