Associations of the P300 Event-Related Potentials and Self-Reported Craving in Substance Use Disorders: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: The phenomenon of craving and attention bias towards drug cues is theorized to operate cooperatively, owing to the principles of associative learning. In this context, the conditioned response to drug-related stimuli activates reward mechanisms within the brain, consequently inducing craving and fostering the underlying mechanisms that contribute to relapse in individuals with substance use disorders. Multiple studies have assessed the relationship between attention to substance-related cues and subjective craving through electroencephalography (EEG), but their findings have yet to be synthesized and examined. This review summarizes the association between the amplitude of the P300 event-related potential (ERP) and substance use craving, compares discrepancies in results by type of substance, and discusses gaps in the literature to inform future research. METHODS: A systematic search was conducted on Embase, Web of Science, CINAHL, and PsychINFO databases. Studies were published in English and included peer-reviewed human research investigating the relationship between EEG P300 ERP and self-reported substance use craving. The included study samples comprised of in treatment or non-treatment-seeking participants who use substances. The primary outcomes of interest were those derived from inferential statistics assessing P300 amplitude and substance use craving. RESULTS: Ten studies were included in the final search and were organized by substance type: three alcohol, three cocaine, two tobacco, one heroin, and one cannabis. Results were mixed for alcohol and cocaine. Studies on tobacco, heroin, and cannabis use were congruent for associations between the P300 amplitude and craving. CONCLUSIONS: Overall findings are mixed between studies addressing the association of the EEG P300 amplitude and craving. These results should be considered in the context of the limited sample size, underpowered analyses, and methodological differences that potentially contribute to discrepancies in outcomes. Further research is required to assess the role of craving assessment, EEG methodology, and substance-related factors on the association between P300 amplitude and self-reported craving.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.014 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".