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Record W3093083946 · doi:10.1523/eneuro.0534-19.2020

Biological Action Identification Does Not Require Early Visual Input for Development

2020· article· en· W3093083946 on OpenAlexaff
Siddhart S. Rajendran, Davide Bottari, Idris Shareef, Kabilan Pitchaimuthu, Suddha Sourav, Nikolaus F. Troje, Ramesh Kekunnaya, Brigitte Röder

Bibliographic record

VenueeNeuro · 2020
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
FundersEuropean Research CouncilHyderabad Eye Research FoundationDeutsche Forschungsgemeinschaft
KeywordsBiological motionVisual processingAudiologyPsychologyVisual perceptionIdentification (biology)PerceptionTask (project management)MedicineNeuroscienceBiology

Abstract

fetched live from OpenAlex

Visual input during the first years of life is vital for the development of numerous visual functions. While normal development of global motion perception seems to require visual input during an early sensitive period, the detection of biological motion (BM) does not seem to do so. A more complex form of BM processing is the identification of human actions. Here, we tested whether identification rather than detection of BM is experience dependent. A group of human participants who had been treated for congenital cataracts (CC; of up to 18 years in duration, CC group) had to identify ten actions performed by human line figures. In addition, they performed a coherent motion (CM) detection task, which required identifying the direction of CM amid the movement of random dots. As controls, developmental cataract (DC) reversal individuals (DC group) who had undergone the same surgical treatment as CC group were included. Moreover, normally sighted controls were tested both with vision blurred to match the visual acuity (VA) of CC individuals [vision matched (VM) group] and with full sight [sighted control (SC) group]. The CC group identified biological actions with an extraordinary high accuracy (on average ∼85% correct) and was indistinguishable from the VM control group. By contrast, CM processing impairments of the CC group persisted even after controlling for VA. These results in the same individuals demonstrate an impressive resilience of BM processing to aberrant early visual experience and at the same time a sensitive period for the development of CM processing.

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)0.001
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 score0.034
Threshold uncertainty score0.296

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.236
GPT teacher head0.387
Teacher spread0.151 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

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