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Record W1516609261 · doi:10.1113/jphysiol.2012.227462

Interneuron‐mediated inhibition synchronizes neuronal activity during slow oscillation

2012· article· en· W1516609261 on OpenAlexafffund
Jen‐Yung Chen, Sylvain Chauvette, Steven W. Skorheim, Igor Timofeev, Maxim Bazhenov

Bibliographic record

VenueThe Journal of Physiology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité Laval
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsNeuroscienceInhibitory postsynaptic potentialLocal field potentialInterneuronElectrophysiologyPremovement neuronal activitySlow-wave sleepOscillation (cell signaling)ElectroencephalographySleep spindleSleep (system call)BiologyPhysicsComputer science

Abstract

fetched live from OpenAlex

Key points A signature of deep sleep in the EEG is large‐amplitude fluctuation of field potential, which reflects alternating periods of activity and silence in the thalamocortical network. Transitions between active and silent states of sleep slow oscillation are well synchronous between remote populations of neurons with the onsets of silent states synchronized better than the onsets of activity. We found that synaptic inhibition plays a major role in terminating active cortical states; strong synaptic inhibition is necessary to synchronize onsets of silent states during normal sleep slow oscillation. We further show that when synaptic inhibition is significantly reduced, active state termination is mediated by intrinsic hyperpolarizing conductances. Our study suggests that inhibitory interaction in the cortical network actively mediates the patterns of neural activity during slow‐wave sleep and may, therefore, contribute to various brain functions developed during deep sleep. Abstract The signature of slow‐wave sleep in the electroencephalogram (EEG) is large‐amplitude fluctuation of the field potential, which reflects synchronous alternation of activity and silence across cortical neurons. While initiation of the active cortical states during sleep slow oscillation has been intensively studied, the biological mechanisms which drive the network transition from an active state to silence remain poorly understood. In the current study, using a combination of in vivo electrophysiology and thalamocortical network simulation, we explored the impact of intrinsic and synaptic inhibition on state transition during sleep slow oscillation. We found that in normal physiological conditions, synaptic inhibition controls the duration and the synchrony of active state termination. The decline of interneuron‐mediated inhibition led to asynchronous downward transition across the cortical network and broke the regular slow oscillation pattern. Furthermore, in both in vivo experiment and computational modelling, we revealed that when the level of synaptic inhibition was reduced significantly, it led to a recovery of synchronized oscillations in the form of seizure‐like bursting activity. In this condition, the fast active state termination was mediated by intrinsic hyperpolarizing conductances. Our study highlights the significance of both intrinsic and synaptic inhibition in manipulating sleep slow rhythms.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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 designBench or experimental
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

Citations108
Published2012
Admission routes2
Has abstractyes

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