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Record W4399443572 · doi:10.1101/2024.06.05.597472

Modulation of neurofluid fluctuation frequency by baseline carbon dioxide in awake humans: the role of the autonomic nervous system

2024· preprint· en· W4399443572 on OpenAlexafffund
Xiaole Zhong, Catie Chang, J. Jean Chen

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsNeuroscienceHypocapniaHypercapniaPsychologyBasal gangliaResting state fMRIRespirationCerebral blood flowDisinhibitionInternal medicineMedicineAnatomyRespiratory systemCentral nervous system

Abstract

fetched live from OpenAlex

Abstract An understanding of neurofluid dynamics has been gaining importance, in part given the link between neurofluid dynamics and glymphatic flow. Recently, CSF pulsations have been attributed to widespread changes in cerebral blood volume (CBV) driven by sleep-state slow-wave electrocortical activity (Fultz et al., 2019), by localized neuronal activity (Williams et al., 2023), by respiration-related autonomic tone (Picchioni et al., 2022) and by vigilance (Z. Yang et al., 2024). It was further suggested that the slow-wave induced CSF pulsations are in fact driven by autonomic (ANS) regulation (Picchioni et al., 2022), and that CSF dynamics are ultimately modulated by ANS mechanisms instead of by sleep per se. To further understand the role of this ANS regulation of vascular tone independently of sleep, and given the established influence of carbon dioxide (CO 2 ) on both ANS tone and vascular tone, we hypothesized that a modulation of basal CO 2 , producing altered global vascular tone and respiration, may highlight the role of ANS regulation in driving CSF flow, and more broadly, neurofluid flow. In this work, we report on observations of neurofluid dynamics at awake normocapnia as well as mild hyper- and hypocapnia steady states. We use the resting-state BOLD fMRI time courses in neurofluid regions (i.e. blood vessels, CSF compartments) as a surrogate of neurofluid dynamics. We found that 1) the manner biomechanical does not drive the variations in neurfluid dynamics across capnias; 2) besides respiration, cardiac pulsation also independently drives neurofluid flow as an indication of the ANS pathway of control; 3) changed CO 2 alters neurofluid dynamics primarily through frequency rather than amplitude of heart-rate and respiratory-volume variability. These findings suggest that hyper- and hypocapnia both represent a disruption of homeostasis that engages ANS regulation, as reflected by the deviations in CRF and RRF from normocapnia. Our work demonstrates in awake humans previously reported ANS regulation observed during sleep. As basal CO 2 can modulate this ANS regulation, it represents a new avenue for modulating neurofluid dynamics independently of sleep, attention or neuronal activation. More broadly, individuals with different basal capnic states may manifest differences in CSF dynamics, giving rise to a novel paradigm for modulating neurofluid flow in awake humans.

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)0.001
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
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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