Perspective: Hippocampal theta rhythm as a potential vestibuloacoustic biomarker of anxiety
Bibliographic record
Abstract
Anxiety disorders are the most common mental illnesses - afflicting 19% of Americans every year and 31% within their lifetimes - yet diagnoses remain based on symptom checklists because existing technologies have yet to produce biomarkers sufficiently robust for clinical use. Some techniques provide superior spatial resolution of deep brain regions implicated in anxiety but have poor time resolution; while others measure signals in real time but lack spatial resolution. Often, the goal of probing deep brain regions in humans for anxiety research is to measure a putative analogue of a mammalian brain rhythm linked to behaviour that is suggestive of anxiety. This 4-12 Hz, 1-2 mV, behaviourally modulated, nearly sinusoidal "hippocampal theta rhythm" (hTheta) is one of the largest normal extracellular synchronous signals in mammals and although it has been linked to anxiety processes, its function remains unclear. This paper reviews the literature on hTheta as it relates to anxiety and sensory, in particular vestibuloacoustic, signals, concludes that hTheta can modulate sensory signals during anxiety and posits that such modulation of vestibular signals may be an anxiety biomarker that could be detected non-invasively in humans.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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.
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".