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Ensemble Dynamics of Stellate Ganglion Neurons Reveal Differential Transduction of Cardiac and Pulmonary Inputs ‐ SPARC

2020· article· en· W3016918892 on OpenAlexaff
Kostubh B. Sudarshan, Yuichi Hori, Mohammed Amer Swid, Alexander B. Karavos, Christian Wooten, Gohar Mirhanian, William Narinyan, J. Andrew Armour, G. Kember, Olujimi A. Ajijola

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsStellate ganglionNeurosciencePopulationCardiologyInternal medicineBiologyMedicinePathology

Abstract

fetched live from OpenAlex

Background The sympathetic nervous system exerts closed‐loop hierarchical control of cardiac function partially through peripheral sympathetic ganglia (PSGs). To what extent PSGs possess network processing capabilities useful for local cardiopulmonary integration outside the central nervous system is unknown. Methods To understand whether neurons within PSGs process cardiopulmonary inputs, and to gain insights into the modes and properties of such transduction, we performed extracellular recordings (via a linear 16‐electrode array) to determine intrinsic activity of left stellate ganglion (LSG) neurons in chloralose‐anesthetized pigs (n=8). Continuous respiratory and left ventricular pressures (RP and LVP) were recorded along with the ECG. Neuronal activity was examined during resting states and under various cardiopulmonary stressors. Linkages between neural activity and LVP and RP were examined at the local neural ensemble and global population levels such that ensemble behavior could be examined over short time scales (minutes) versus evolution of population level processing over hours, using a sliding window. Results Neural ensembles show a wide range of regional behaviors with activity that may cease or commence during the cardiorespiratory cycle such that no neuron is either purely cardiac or pulmonary, rather neurons exhibit cardiopulmonary integration. Global level processing was examined, over a sliding window, for: (i) the presence or absence of cardiac and respiratory periodicities, and (ii) the evolution of the degree to which greater or lesser ‘attention’ is globally paid to LVP and RP relative to random sampling. The results of (ii) show that the greatest attention is paid to diastole and near‐peak LVP. Regarding RP, little attention is paid to the respiratory pressure while the breathing rate from (i) is generally strongly evident. Interestingly, spiking density did not correlate with level of attention i.e. increased spiking levels does not imply that random sampling has ceased and attention has become focused on LVP or RP. Conclusions Activity of stellate ganglion neurons recorded in situ reveal complex local neuronal and global population properties that are dynamically phase‐ and rate‐locked with cardiac and pulmonary function respectively. The combination of (i) and (ii) are useful in finding consistency in neuronal attention across animals since this combination gives insight into the degree to which a population of neurons is processing information at the local and global levels within PSGs. Support or Funding Information NIH: DP2OD024323‐01 and OT2OD023848

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.018
GPT teacher head0.230
Teacher spread0.212 · 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 designObservational
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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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