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Developmental underpinnings of differences in rodent novelty‐seeking and emotional reactivity

2011· article· en· W1930138558 on OpenAlexaff
Sarah M. Clinton, John D. H. Stead, Sue Miller, Stanley J. Watson, Huda Akil

Bibliographic record

VenueEuropean Journal of Neuroscience · 2011
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsCarleton University
FundersNational Institute on Drug AbuseNational Institute of Mental Health
KeywordsNoveltyRodentRodent modelPsychologyReactivity (psychology)NeuroscienceNovelty seekingCognitive psychologySocial psychologyMedicineBiologyTemperamentEcology

Abstract

fetched live from OpenAlex

Innate differences in human temperament strongly influence how individuals cope with stress and also predispose towards specific types of psychopathology. The present study examines the developing brain in an animal model of temperamental differences to examine how altered neurodevelopment may engender differences in emotional reactivity that are stable throughout the animal's life. We utilize selectively-bred High Responder (bHR) and Low Responder (bLR) rats that exhibit dramatic emotional behavior differences, with bHRs exhibiting exaggerated novelty-exploration, aggression, impulsivity and drug self-administration, and bLRs showing marked behavioral inhibition and exaggerated anxiety-like and depressive-like behavior. Using Affymetrix microarrays, we assessed bLR and bHR gene expression in the developing brain on postnatal days (P)7, 14 and 21, focusing on the hippocampus and nucleus accumbens, two regions related to emotionality and known to differ in adult bLR and bHR rats. We found dramatic gene expression differences between bLR and bHR in the P7 and P14 hippocampus, with minimal differences in the nucleus accumbens. Some of the most profound differences involved genes critical for neurodevelopment and synaptogenesis. Stereological studies evaluated hippocampal structure in developing bHR and bLR pups, revealing enhanced hippocampal volume and cell proliferation in bLR animals. Finally, behavioral studies showed that the characteristic bHR and bLR behavioral phenotypes emerge very early in life, with exploratory differences apparent at P16 and anxiety differences present by P25. Together these data point to specific brain regions and critical periods when the bHR and bLR phenotypes begin to diverge, which may eventually allow us to test possible therapeutic interventions to normalize extreme phenotypes (e.g. the anxiety-prone nature of bLRs or drug addiction proclivity of bHRs).

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.116
GPT teacher head0.266
Teacher spread0.151 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations62
Published2011
Admission routes1
Has abstractyes

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