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Record W1975598610 · doi:10.1073/pnas.0905549106

“Real-time” obstacle avoidance in the absence of primary visual cortex

2009· article· en· W1975598610 on OpenAlexafffund
Christopher L. Striemer, Craig S. Chapman, Melvyn A. Goodale

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2009
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsCanadian Institutes of Health ResearchWestern University
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsVisual cortexVisual fieldNeurosciencePosterior parietal cortexObstacleDorsumVision for perception and vision for actionComputer scienceVisual systemTask (project management)Obstacle avoidancePsychologyCortex (anatomy)Computer visionArtificial intelligenceCognitive psychologyBiologyAnatomyRobot

Abstract

fetched live from OpenAlex

When we reach toward objects, we easily avoid potential obstacles located in the workspace. Previous studies suggest that obstacle avoidance relies on mechanisms in the dorsal visual stream in the posterior parietal cortex. One fundamental question that remains unanswered is where the visual inputs to these dorsal-stream mechanisms are coming from. Here, we provide compelling evidence that these mechanisms can operate in "real-time" without direct input from primary visual cortex (V1). In our first experiment, we used a reaching task to demonstrate that an individual with a dense left visual field hemianopia after damage to V1 remained strikingly sensitive to the position of unseen static obstacles placed in his blind field. Importantly, in a second experiment, we showed that his sensitivity to the same obstacles in his blind field was abolished when a short 2-s delay (without vision) was introduced before reach onset. These findings have far-reaching implications, not only for our understanding of the time constraints under which different visual pathways operate, but also in relation to how these seemingly "primitive" subcortical visual pathways can control complex everyday behavior without recourse to conscious vision.

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)0.002
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 score0.224
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.063
GPT teacher head0.348
Teacher spread0.285 · 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

Citations53
Published2009
Admission routes2
Has abstractyes

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