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Record W2045141677 · doi:10.1097/wno.0b013e3181a58ef8

Combined Functional MRI and Diffusion Tensor Imaging Analysis of Visual Motion Pathways

2009· article· en· W2045141677 on OpenAlexafffund
Linda Lanyon, Deborah Giaschi, Simon Au Young, Kevin M. Fitzpatrick, Lu Diao, Bruce Björnson, Jason J.S. Barton

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2009
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsTractographySuperior colliculusThalamusNeuroscienceDiffusion MRIVisual cortexVisual systemWhite matterNeuroimagingPsychologyMagnetic resonance imagingMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Motion perception may be preserved after damage to striate cortex (primary visual cortex, area V1). Awareness and normal discrimination of fast-moving stimuli have been observed even in the complete absence of V1. These facts suggest that motion-sensitive cortex (the V5/MT complex or V5/MT+) may be activated by direct thalamic or collicular inputs that bypass V1. Such projections have been identified previously in monkeys but have not been shown in humans using neuroimaging techniques. METHODS: We used diffusion tensor imaging (DTI) tractography to visualize white matter fiber tracts connecting with V5/MT+ in 10 healthy volunteers. V5/MT+ was localized for each subject using functional MRI (fMRI). Functional activity maps were overlaid on high-resolution anatomical images and registered with the diffusion-weighted images to define V5/MT+ as the region of interest (ROI) for DTI tractography analysis. Fibers connecting to V1 were excluded from the analysis. RESULTS: Using conservative tractography parameters, we found connections between the V5/MT+ region and the posterior thalamus and/or superior colliculus in 4 of 10 subjects. CONCLUSIONS: Connections between the V5/MT+ region and the posterior thalamus and/or superior colliculus may explain visual motion awareness in the absence of a functioning V1.

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 score0.498
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.052
GPT teacher head0.345
Teacher spread0.292 · 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

Citations41
Published2009
Admission routes2
Has abstractyes

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