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Record W2782208459 · doi:10.1073/pnas.1717016115

Transient visual pathway critical for normal development of primate grasping behavior

2018· article· en· W2782208459 on OpenAlexaff
Iñaki-Carril Mundiñano, Dylan M. Fox, William C. Kwan, Diego Vidaurre, Leon Teo, Jihane Homman‐Ludiye, Melvyn A. Goodale, David A. Leopold, James A. Bourne

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsWestern University
FundersState Government of VictoriaNational Health and Medical Research CouncilNational Institutes of HealthNational Institute of Mental HealthMedical Research CouncilAustralian Government
KeywordsNeuroscienceThalamusGRASPVisual systemVisual cortexPrimateDorsumBiologyPsychologyComputer scienceAnatomy

Abstract

fetched live from OpenAlex

An evolutionary hallmark of anthropoid primates, including humans, is the use of vision to guide precise manual movements. These behaviors are reliant on a specialized visual input to the posterior parietal cortex. Here, we show that normal primate reaching-and-grasping behavior depends critically on a visual pathway through the thalamic pulvinar, which is thought to relay information to the middle temporal (MT) area during early life and then swiftly withdraws. Small MRI-guided lesions to a subdivision of the inferior pulvinar subnucleus (PIm) in the infant marmoset monkey led to permanent deficits in reaching-and-grasping behavior in the adult. This functional loss coincided with the abnormal anatomical development of multiple cortical areas responsible for the guidance of actions. Our study reveals that the transient retino-pulvinar-MT pathway underpins the development of visually guided manual behaviors in primates that are crucial for interacting with complex features in the environment.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.077
GPT teacher head0.360
Teacher spread0.283 · 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 designBench or experimental
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

Citations67
Published2018
Admission routes1
Has abstractyes

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