The study of noninvasive brain stimulation using molecular brain imaging: A systematic review
Bibliographic record
Abstract
Electromagnetic noninvasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation and transcranial electrical stimulation, are widely used in research and represent emerging clinical treatment options for many brain disorders. The brain-wide neurobiological effects of electromagnetic NIBS, however, are not yet fully characterized. The combination of NIBS with molecular brain imaging is a powerful tool for the investigation of these effects. Here, we conducted a systematic review of all published studies investigating the effects of all forms of electromagnetic NIBS using molecular imaging (positron emission tomography, single photon emission computed tomography). A meta-analysis was also conducted when sufficient studies employed similar methodologies. A total of 239 articles were identified, of which 71 were included in the review. Information was extracted about the study design, NIBS parameters, imaging parameters, and observed local and remote effects caused by the stimulation. Regional cerebral blood flow and glucose metabolism were the most common outcome measures, followed by dopamine neurotransmission. While the vast majority of studies obtained remote effects of stimulation in interconnected regions, approximately half of the studies showed local effects at the stimulation site. Our meta-analysis on motor cortex stimulation also showed consistent remote effects. The literature review demonstrates that although the local effects of NIBS as captured by molecular imaging are sometimes modest, there are robust remote changes in brain activity and neurotransmitter function. Finally, we discuss the potential pitfalls and methodological issues and identify gaps in the current knowledge that could be addressed using these techniques.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".