Effects of Noninvasive Brain Stimulation on Food Cravings and Consumption: A Meta-Analytic Review
Bibliographic record
Abstract
OBJECTIVE: The primary aim of this review was to evaluate the effectiveness of noninvasive brain stimulation to the dorsolateral prefrontal cortex (dlPFC) for modulating appetitive food cravings and consumption in laboratory (via meta-analysis) and therapeutic (via systematic review) contexts. METHODS: Keyword searches of electronic databases (PubMed, Scopus, Web of Science, PsychoInfo, and EMBASE) and searches of previous quantitative reviews were used to identify studies (experimental [single-session] or randomized trials [multi-session]) that examined the effects of neuromodulation to the dlPFC on food cravings (n = 9) and/or consumption (n = 7). Random-effects models were employed to estimate the overall and method-specific (repetitive transcranial magnetic stimulation [rTMS] and transcranial direct current stimulation [tDCS]) effect sizes. Age and body mass index were examined as potential moderators. Two studies involving multisession therapeutic stimulation were considered in a separate systematic review. RESULTS: Findings revealed a moderate-sized effect of modulation on cravings across studies (g, -0.516; p = .037); this effect was subject to significant heterogeneity (Q, 33.086; p < .001). Although no statistically significant moderators were identified, the stimulation effect on cravings was statistically significant for rTMS (g, -0.834; p = .008) but not tDCS (g, -0.252; p = .37). There was not sufficient evidence to support a causal effect of neuromodulation and consumption in experimental studies; therapeutic studies reported mixed findings. CONCLUSIONS: Stimulation of the dlPFC modulates cravings for appetitive foods in single-session laboratory paradigms; when estimated separately, the effect size is only significant for rTMS protocols. Effects on consumption in laboratory contexts were not reliable across studies, but this may reflect methodological variability in delivery of stimulation and assessment of eating behavior. Additional single- and multi-session studies assessing eating behavior outcomes are needed.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.023 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".