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Contributions of Neuroscience to Our Understanding of Cognitive Development

2008· article· en· W2161067800 on OpenAlex

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

VenueCurrent Directions in Psychological Science · 2008
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersNational Institute on Drug AbuseDirectorate for Biological Sciences
KeywordsPsychologyCognitive neuroscienceDevelopmental cognitive neuroscienceCognitionNeuroscienceImitationNeuroimagingCognitive scienceMechanism (biology)Cognitive neuropsychologySocial neuroscienceIntervention (counseling)Cognitive psychologySocial cognitionNeuropsychology

Abstract

fetched live from OpenAlex

One major contribution of neuroscience to understanding cognitive development has been in demonstrating that biology is not destiny-that is, demonstrating the remarkable role of experience in shaping the mind, brain, and body. Only rarely has neuroscience provided wholly new insights into cognitive development, but often it has provided evidence of mechanisms by which observations of developmental psychologists could be explained. Behavioral findings have often remained controversial until an underlying biological mechanism for them was offered. Neuroscience has demonstrated promise for detecting cognitive problems before they are behaviorally observable-and, hence, promise for early intervention. In this article, we discuss examples drawn from imitation and mirror neurons, phenylketonuria (PKU) and prefrontal dopamine, maternal touch and stress reactivity, and non-genetic (behavioral) intergenerational transmission of biological characteristics.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
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 head0.259
GPT teacher head0.476
Teacher spread0.217 · 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