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Record W2095180054 · doi:10.1177/0956797614534267

Are Orchids Left and Dandelions Right? Frontal Brain Activation Asymmetry and Its Sensitivity to Developmental Context

2014· article· en· W2095180054 on OpenAlexaff
Paz Fortier, Ryan J. Van Lieshout, Jordana A. Waxman, Michael H. Boyle, Saroj Saigal, Louis A. Schmidt

Bibliographic record

VenuePsychological Science · 2014
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsMcMaster University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentAssociation for Psychological Science
KeywordsPsychologyContext (archaeology)Developmental psychologyAsymmetryBrain asymmetryFrontal lobeOntogenyElectroencephalographyLow birth weightNeuroscienceAudiologyLateralization of brain functionInternal medicineBiologyMedicinePregnancy

Abstract

fetched live from OpenAlex

To clarify long-standing conceptual and empirical inconsistencies in models describing the relation between frontal brain asymmetry and emotion, we tested a theory of biological sensitivity to context. We examined whether asymmetry of alpha activation in frontal brain regions, as measured by resting electroencephalography, is sensitive to early developmental contexts. Specifically, we investigated whether frontal asymmetry moderates the association between birth weight and adult outcomes. Adults with left frontal asymmetry (LFA) who were born at extremely low birth weight exhibited high levels of attention problems and withdrawn behaviors in their 30s, whereas normal-birth-weight adults with LFA had low levels of these problem behaviors. Adults with right frontal asymmetry (RFA) displayed a relatively moderate amount of problem behavior regardless of birth weight. Our findings suggest that LFA is associated with sensitivity to developmental context and may help explain why LFA is associated with both positive and negative outcomes, whereas RFA seems to be associated with a more canalized process in some contexts.

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)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.475
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.330
Teacher spread0.287 · 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.

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

Citations21
Published2014
Admission routes1
Has abstractyes

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