A novel interleaved TMS-MRS approach with standard MRI hardware
Bibliographic record
Abstract
OBJECTIVE: Interleaved TMS-fMRI has advanced understanding of network modulation but is limited to hemodynamic measures. We introduce a novel interleaved TMS-MRS platform, using standard MRI hardware, to assess real-time neurochemical changes and demonstrate feasibility in a clinical sample of patients with treatment-resistant depression (TRD). METHODS: H-MRS spectra were acquired at baseline and during 10 Hz burst stimulation. Spectral quality and metabolite concentrations were compared across conditions. RESULTS: Spectral quality was preserved across conditions (FWHM baseline: 0.041 ± 0.005; active: 0.040 ± 0.005; p = 0.699) and signal-to-noise remained stable (baseline: 38.29 ± 5.38; active: 34.67 ± 9.12; p = 0.790). Two metabolites differed significantly: alanine increased during stimulation (0.58 ± 0.16 vs. 0.46 ± 0.14; p = 0.031), while NAA + NAAG decreased (9.07 ± 2.02 vs. 8.83 ± 0.99; p = 0.031). Exploratory analyses suggested associations between baseline and stimulation-induced metabolites (e.g., GSH, GABA, lactate) and clinical improvement following accelerated iTBS. CONCLUSION: Interleaved TMS-MRS is feasible with standard MRI hardware in TRD patients, enabling in-vivo detection of acute neurochemical changes during stimulation. This method offers a new avenue for probing excitatory/inhibitory balance, neuronal metabolism, and treatment mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".