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Record W3178398029 · doi:10.1152/jn.00062.2021

Neuron-astrocyte networking: astrocytes orchestrate and respond to changes in neuronal network activity across brain states and behaviors

2021· review· en· W3178398029 on OpenAlexaff
Marion R. Van Horn, Nicholas J. Benfey, Colleen Shikany, Liza J. Severs, Tara Deemyad

Bibliographic record

VenueJournal of Neurophysiology · 2021
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsNeuroscienceAstrocytePremovement neuronal activityArousalNeuronBrain functionBiologyPsychologyCentral nervous system

Abstract

fetched live from OpenAlex

Astrocytes are known to play many important roles in brain function. However, research underscoring the extent to which astrocytes modulate neuronal activity is still underway. Here we review the latest evidence regarding the contribution of astrocytes to neuronal oscillations across the brain, with a specific focus on how astrocytes respond to changes in brain state (e.g., sleep, arousal, stress). We then discuss the general mechanisms by which astrocytes signal to neurons to modulate neuronal activity, ultimately driving changes in behavior, followed by a discussion of how astrocytes contribute to respiratory rhythms in the medulla. Finally, we contemplate the possibility that brain stem astrocytes could modulate brainwide oscillations by communicating the status of oxygenation to higher cortical areas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.079
GPT teacher head0.368
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations19
Published2021
Admission routes1
Has abstractyes

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