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Record W2264009892 · doi:10.1017/s095457941500019x

Dysplasticity, metaplasticity, and schizophrenia: Implications for risk, illness, and novel interventions

2015· review· en· W2264009892 on OpenAlex
Matcheri S. Keshavan, Urvakhsh Meherwan Mehta, Jaya Padmanabhan, Jai Shah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDevelopment and Psychopathology · 2015
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
FundersNational Institute of Mental HealthU.S. Public Health Service
KeywordsSchizophrenia (object-oriented programming)NeuroplasticityPsychologyMetaplasticityNeurosciencePsychological interventionPsychosisCognitionSchizophrenia researchPsychiatrySynaptic plasticityMedicine

Abstract

fetched live from OpenAlex

In this paper, we review the history of the concept of neuroplasticity as it relates to the understanding of neuropsychiatric disorders, using schizophrenia as a case in point. We briefly review the myriad meanings of the term neuroplasticity, and its neuroscientific basis. We then review the evidence for aberrant neuroplasticity and metaplasticity associated with schizophrenia as well as the risk for developing this illness, and discuss the implications of such understanding for prevention and therapeutic interventions. We argue that the failure and/or altered timing of plasticity of critical brain circuits might underlie cognitive and deficit symptoms, and may also lead to aberrant plastic reorganization in other circuits, leading to affective dysregulation and eventually psychosis. This "dysplastic" model of schizophrenia can suggest testable etiology and treatment-relevant questions for the future.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.210
GPT teacher head0.408
Teacher spread0.198 · 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