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Record W2788289493 · doi:10.3389/fnbeh.2018.00004

Biological Clocks and Rhythms of Anger and Aggression

2018· review· en· W2788289493 on OpenAlexafffund
Suzanne Hood, Shimon Amir

Bibliographic record

VenueFrontiers in Behavioral Neuroscience · 2018
Typereview
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsConcordia UniversityBishop's University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsCircadian rhythmAngerAggressionRhythmPsychologyInfradian rhythmCircadian clockNeuroscienceChronobiologyDevelopmental psychologyMedicineClinical psychologyInternal medicineUltradian rhythm

Abstract

fetched live from OpenAlex

The body’s internal timekeeping system is an under-recognized but highly influential force in behaviors and emotions including anger and reactive aggression. Predictable cycles or rhythms in behavior are expressed on several different time scales such as circadian (circa diem, or approximately 24-hour rhythms) and infradian (exceeding 24 hours, such as monthly or seasonal cycles). The circadian timekeeping system underlying rhythmic behaviors in mammals is constituted by a network of clocks distributed throughout the brain and body, the activity of which synchronizes to a central pacemaker, or master clock. Our daily experiences with the external environment including social activity strongly influence the clock mechanism operates at the level of our genes, but its exact timing of this network is synchronized by our experiences with the external environment including social activity. In the present review, we examine evidence from a number of species and propose that anger and reactive aggression interact in multiple ways with circadian clocks. Specifically, we argue that i) there are predictable rhythms in the expression of aggression and anger, ii) disruptions of the normal functioning of the body clock circadian system increase the likelihood of aggressive behaviors, and iii) conversely, chronic expression of anger can disrupt normal rhythmic cycles of physiological activities and create conditions for pathologies such as cardiovascular disease to develop. Taken together, these observations suggest that a comprehensive perspective on anger and reactive aggression must incorporate an understanding of the role of the body circadian timing system in these intense affective states.

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)0.000
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 score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.131
GPT teacher head0.364
Teacher spread0.233 · 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 designOther design
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

Citations25
Published2018
Admission routes2
Has abstractyes

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