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The neuroscience of sadness: A multidisciplinary synthesis and collaborative review

2020· review· en· W3003233130 on OpenAlexaff
Juan A. Arias-López, Claire Williams, Rashmi Raghvani, Moji Aghajani, Sandra Báez, Catherine Belzung, Linda Booij, Geraldo F. Busatto, Julian Chiarella, Cynthia H.Y. Fu, Agustín Ibáñez, Belinda J. Liddell, Leroy Lowe, Brenda W.J.H. Penninx, Pedro Rosa‐Neto, Andrew H. Kemp

Bibliographic record

VenueNeuroscience & Biobehavioral Reviews · 2020
Typereview
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversité de MontréalConcordia UniversityCentre Hospitalier Universitaire Sainte-Justine
FundersFondo para la Investigación Científica y TecnológicaEngineering and Physical Sciences Research CouncilComisión Nacional de Investigación Científica y TecnológicaMedical Research CouncilConsejo Nacional de Investigaciones Científicas y TécnicasFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasAcademy of Medical Royal CollegesSwansea UniversityFundación INECO
KeywordsSadnessPrecuneusNeurosciencePsychologyDorsolateral prefrontal cortexPrefrontal cortexNeuroimagingAnterior cingulate cortexCognitive psychologyAngerCognitionClinical psychology

Abstract

fetched live from OpenAlex

Sadness is typically characterized by raised inner eyebrows, lowered corners of the mouth, reduced walking speed, and slumped posture. Ancient subcortical circuitry provides a neuroanatomical foundation, extending from dorsal periaqueductal grey to subgenual anterior cingulate, the latter of which is now a treatment target in disorders of sadness. Electrophysiological studies further emphasize a role for reduced left relative to right frontal asymmetry in sadness, underpinning interest in the transcranial stimulation of left dorsolateral prefrontal cortex as an antidepressant target. Neuroimaging studies - including meta-analyses - indicate that sadness is associated with reduced cortical activation, which may contribute to reduced parasympathetic inhibitory control over medullary cardioacceleratory circuits. Reduced cardiac control may - in part - contribute to epidemiological reports of reduced life expectancy in affective disorders, effects equivalent to heavy smoking. We suggest that the field may be moving toward a theoretical consensus, in which different models relating to basic emotion theory and psychological constructionism may be considered as complementary, working at different levels of the phylogenetic hierarchy.

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)0.002
metaresearch head score (Gemma)0.063
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.005
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.001
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 head0.191
GPT teacher head0.412
Teacher spread0.221 · 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; both teacher heads agree on what is shown here.

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

Citations113
Published2020
Admission routes1
Has abstractyes

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