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The Salience Network: A Neural System for Perceiving and Responding to Homeostatic Demands

2019· article· en· W2984087519 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

VenueJournal of Neuroscience · 2019
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsSalience (neuroscience)NeurosciencePsychologyConceptualizationCognitive psychologyBrainstemAmygdalaThalamusVentral striatumAnterior cingulate cortexCognitive scienceCognitionStriatumComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The term "salience network" refers to a suite of brain regions whose cortical hubs are the anterior cingulate and ventral anterior insular (i.e., frontoinsular) cortices. This network, which also includes nodes in the amygdala, hypothalamus, ventral striatum, thalamus, and specific brainstem nuclei, coactivates in response to diverse experimental tasks and conditions, suggesting a domain-general function. In the 12 years since its initial description, the salience network has been extensively studied, using diverse methods, concepts, and mammalian species, including healthy and diseased humans across the lifespan. Despite this large and growing body of research, the essential functions of the salience network remain uncertain. In this paper, which makes no attempt to comprehensively review this literature, I describe the circumstances surrounding the initial discovery, conceptualization, and naming of the salience network, highlighting aspects that may be unfamiliar to many readers. I then discuss some of the key advances provided by subsequent research and conclude by posing a few of the questions that remain to be explored.

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)0.002
metaresearch head score (Gemma)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.945
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.036
GPT teacher head0.288
Teacher spread0.251 · 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