Assessing differential effects of single and accelerated low‐frequency rTMS to the visual cortex on GABA and glutamate concentrations
Bibliographic record
Abstract
BACKGROUND: The application of repetitive transcranial magnetic stimulation (rTMS) for therapeutic use in visual-related disorders and its underlying mechanisms in the visual cortex is under-investigated. Additionally, there is little examination of rTMS adverse effects particularly with regards to visual and cognitive function. Neural plasticity is key in rehabilitation and recovery of function; thus, effective therapeutic strategies must be capable of modulating plasticity. Glutamate and γ-aminobutyric acid (GABA)-mediated changes in the balance between excitation and inhibition are prominent features in visual cortical plasticity. OBJECTIVES AND METHOD: We investigated the effects of low-frequency (1 Hz) rTMS to the visual cortex on levels of neurotransmitters GABA and glutamate to determine the therapeutic potential of 1 Hz rTMS for visual-related disorders. Two rTMS regimes commonly used in clinical applications were investigated: participants received rTMS to the visual cortex either in a single 20-min session or five accelerated 20-min sessions (not previously investigated at the visual cortex). Proton (1H) magnetic resonance spectroscopy for in vivo quantification of GABA (assessed via GABA+) and glutamate (assessed via Glx) concentrations was performed pre- and post-rTMS. RESULTS: GABA+ and Glx concentrations were unaltered following a single session of rTMS to the visual cortex. One day of accelerated rTMS significantly reduced GABA+ concentration for up to 24 hr, with levels returning to baseline by 1-week post-rTMS. Basic visual and cognitive function remained largely unchanged. CONCLUSION: Accelerated 1 Hz rTMS to the visual cortex has greater potential for approaches targeting plasticity or in cases with altered GABAergic responses in visual disorders. Notably, these results provide preliminary insight into a critical window of plasticity with accelerated rTMS (e.g., 24 hr) in which adjunct therapies may offer better functional outcome. We describe detailed procedures to enable further exploration of these protocols.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".