Modulating intrinsic functional connectivity with visual cortex using low‐frequency repetitive transcranial magnetic stimulation
Bibliographic record
Abstract
INTRODUCTION: Intrinsic network connectivity becomes altered in pathophysiology. Noninvasive brain stimulation can modulate pathological functional networks in an attempt to restore the inherent response. To determine its usefulness for visual-related disorders, we developed procedures investigating repetitive transcranial magnetic stimulation (rTMS) protocols targeting the visual cortex on modulating connectivity associated with the visual network and default mode network (DMN). METHODS: We compared two low-frequency (1 Hz) rTMS protocols to the visual cortex (V1)-a single 20 min session and five successive 20 min sessions (accelerated/within-session rTMS)-using multi-echo resting-state functional magnetic resonance whole-brain imaging and resting-state functional connectivity (rsFC). We also explored the relationship between rsFC and rTMS-induced changes in key inhibitory and excitatory neurotransmitters, γ-aminobutyric acid (GABA) and glutamate. GABA (GABA+) and glutamate (Glx) concentrations were measured in vivo using magnetic resonance spectroscopy. RESULTS: Acute disruption with a single rTMS session caused widespread connectivity reconfiguration with nodes of interest. Changes were not evident immediately post-rTMS but were observed at 1 h post-rTMS. Accelerated sessions resulted in weak alterations in connectivity, producing a relatively homeostatic response. Changes in GABA+ and Glx concentrations with network connectivity were dependent on the rTMS protocol. CONCLUSIONS: This proof-of-concept study offers new perspectives to assess stimulation-induced neural processes involved in intrinsic functional connectivity and the potential for rTMS to modulate nodes interconnected with the visual cortex. The differential effects of single-session and accelerated rTMS on physiological markers are crucial for furthering the advancement of treatment modalities in visual cortex related disorders.
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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 | 0.001 | 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) | 0.001 | 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".