Heart Rate Variability and Cognition: A Narrative Systematic Review of Longitudinal Studies
Bibliographic record
Abstract
BACKGROUND: Heart rate variability (HRV) is a reliable and convenient method to assess autonomic function. Cross-sectional studies have established a link between HRV and cognition. Longitudinal studies are an emerging area of research with important clinical implications in terms of the predictive value of HRV for future cognition and in terms of the potential causal relationship between HRV and cognition. However, they have not yet been the objective of a systematic review. Therefore, the aim of this systematic review was to investigate the association between HRV and cognition in longitudinal studies. METHODS: The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Embase, PsycINFO and PubMed databases were searched from the earliest available date to 26 June 2023. Studies were included if they involved adult human subjects and evaluated the longitudinal association between HRV and cognition. The risk of bias was assessed with the Newcastle-Ottawa Scale for Cohort Studies. The results were presented narratively. RESULTS: Of 14,359 records screened, 12 studies were included in this systematic review, with a total of 24,390 participants. Two thirds of the studies were published from 2020 onwards. All studies found a longitudinal relationship between HRV and cognition. There was a consistent association between higher parasympathetic nervous system (PNS) activity and better cognition, and some association between higher sympathetic nervous system activity and worse cognition. Also, higher PNS activity persistently predicted better executive functioning, while data on episodic memory and language were more scant and/or controversial. CONCLUSIONS: Our results support the role of HRV as a biomarker of future cognition and, potentially, as a therapeutic target to improve cognition. They will need confirmation by further, more comprehensive studies also including unequivocal non-HRV sympathetic measures and meta-analyses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".