Model-based perturbational neurophysiological markers of TMS iTBS in Treatment-Resistant Depression
Bibliographic record
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive technique to modulate brain activity, often used in treating Major Depressive Disorder (MDD) by targeting fronto-limbic circuitry.Despite its clinical utility, optimizing rTMS protocols remains challenging due to the complex and variable effects of parameter changes on synaptic plasticity.Oscillatory brain activity, measurable via EEG, serves as a biomarker for functional circuits and treatment response.To better understand these mechanisms, we used computational modeling of corticothalamic circuits to explore the impact of rTMS on brain oscillations and connectivity.We integrated homeostatic calcium-dependent plasticity (CaDP) with a Bienenstock-Cooper-Munro (BCM) sliding threshold in a neural population model of resting-state EEG, simulating iTBS effects on spectral power, synaptic efficacy, and calcium volumes by varying protocol parameters.Our findings highlight a resonance between theta stimulation and restingstate alpha rhythms, enhancing incoming excitatory long-term depression (LTD) and inhibitory long-term potentiation (LTP), leading to corticothalamic feed-forward inhibition.Induced effects were encapsulated by a weakening of corticothalamic loops and enhancement of intrathalamic loops.This work offers a novel paradigm for individualizing iTBS treatments, provides insights into the neurophysiological basis of clinical responsiveness, and offers a framework with which to derive tailored protocols.
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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 | 0.006 |
| 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".