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Record W2091642132 · doi:10.1002/dev.20515

Age, experience, injury, and the changing brain

2010· review· en· W2091642132 on OpenAlexaff
Bryan Kolb, G. Campbell Teskey

Bibliographic record

VenueDevelopmental Psychobiology · 2010
Typereview
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsNeuroplasticityNeurosciencePsychologyHuman brainBrain functionBrain Structure and FunctionDiversity (politics)Stroke (engine)Cognitive psychologyNeuroimaging

Abstract

fetched live from OpenAlex

The fundamental concept in the emerging field of rehabilitation and brain plasticity is that although there is much constancy in brain function and organization across our lifetime, there is remarkable variability as well. This variability reflects the brain's capacity to alter its structure and function in reaction to environmental diversity as well as to perturbations including injury throughout the lifespan. Although the term brain plasticity is now widely used, it is not easily defined and is used to refer to changes at many levels in the nervous system ranging from molecular events, such as changes in gene expression, to behavior (e.g., Shaw & McEachern (Eds.) [2001]. Toward a Theory of Neuroplasticity. Philadelphia, USA: Psychology Press). The focus of our work has been to correlate changes in behavior, neuronal morphology, and the organization of motor maps after cortical injury throughout the lifespan. In this article, we review evidence we have collected from a rat model of normal development and the effects of brain injury, and comment on the general principals that may apply to human stroke and amblyopia.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.049
GPT teacher head0.360
Teacher spread0.311 · 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 designNot applicable
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

Citations85
Published2010
Admission routes1
Has abstractyes

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