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Neural Plasticity in Amblyopia

2021· reference-entry· en· W3216934412 on OpenAlexaff
Benjamin Thompson

Bibliographic record

VenueOxford Research Encyclopedia of Psychology · 2021
Typereference-entry
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNeuroplasticityVisual cortexNeuroscienceMonocular deprivationPsychologySensory systemPerceptionOcular dominance

Abstract

fetched live from OpenAlex

Abstract Early in life, the brain has a substantial capacity for change, often referred to as neuroplasticity. Disrupted visual input to the brain during an early “critical” or “sensitive period” of heightened neuroplasticity induces structural and functional changes within neural systems and causes amblyopia, a sensory disorder associated with abnormal development of the brain areas involved in perception. Amblyopia impairs a broad range of visual, multisensory, and motor functions, and recovery from amblyopia requires a substantial change in visual information processing within the brain. Therefore, not only is amblyopia caused by an interaction between visual experience and heightened neuroplasticity, recovery from amblyopia also requires significant neuroplastic change within the brain. A number of evidence-based treatments are available for young children with amblyopia whose brains are still rapidly developing and have a correspondingly high level of neuroplasticity. However, adults with amblyopia are often left untreated because of the idea that the adult brain no longer has sufficient neuroplasticity to relearn how to process visual information. In the early 21st century, it became clear that this idea was not correct. A number of interventions that can enhance neuroplasticity in the mature visual cortex have been identified using animal models of amblyopia and are now being translated into human studies. Other promising techniques for enhancing visual cortex neuroplasticity have emerged from studies of adult humans with amblyopia. Examples of interventions that may improve vision in adult amblyopia include refractive correction, patching of the amblyopic eye (reverse patching), monocular and binocular perceptual learning, noninvasive brain stimulation, systemic drugs, and exercise. The next important stage of research within this field will be to conduct fully controlled randomized clinical trials to assess which, if any, of these interventions can be translated into a mainstream treatment for amblyopia in adulthood.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.184
GPT teacher head0.460
Teacher spread0.276 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations7
Published2021
Admission routes1
Has abstractyes

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