Neural Noise

Cognition-guided EEG neurofeedback for response inhibition in clinical populations

2 min read

  • Response inhibition was improved through cognition-guided EEG neurofeedback in men with methamphetamine use disorder (peer-reviewed study).1
  • The approach is relevant to EEG-BCI methods and neurofeedback; methods are transferable to other populations.1 1

Gardner updates

  • Cognition-guided EEG neurofeedback improved response inhibition in men with methamphetamine use disorder in a peer-reviewed study. 1

Weekly enrichment (2026-07-20)

  • The study was published in the American Journal of Psychiatry (2025, volume 182, issue 9, pages 861–877) by Gou, Bu, Zhang and colleagues; DOI 10.1176/appi.ajp.20240475.2
  • It used a cognition-guided, closed-loop EEG neurofeedback protocol: methamphetamine cue-related brain activity patterns were identified offline using multivariate pattern analysis of all-channel EEG during a cue-reactivity task, then participants were trained in real time to deactivate their own patterns.2
  • The trial included 99 men with methamphetamine use disorder across two samples; sample 1 (n=66) randomized participants to real neurofeedback based on their own patterns (n=33) or yoked feedback from randomly matched participants (n=33), each receiving 10 sessions.2
  • A per-participant support vector machine classifier learned to distinguish methamphetamine cue-reactive versus neutral brain states at above-chance accuracy, forming the core of the neurofeedback signal.3
  • Compared with yoked feedback, real neurofeedback significantly improved response inhibition on a methamphetamine go/no-go task (d-prime), with a medium effect size (Cohen’s f = 0.31).24
  • Sample 2 (real feedback n=17 versus standard rehabilitation n=16) replicated the effect, with real neurofeedback outperforming standard rehabilitation alone.2
  • Improvements in inhibitory control correlated with neurofeedback performance and were predictable from initial neurofeedback performance and baseline characteristics.2
  • The approach builds on the group’s prior cognition-guided deactivation work in nicotine addiction (Bu et al., Brain, 2019); the authors suggest applicability to other addiction interventions, relevant to EEG-BCI neuromodulation methods.23

Footnotes

  1. https://news.google.com/rss/articles/CBMib0FVX3lxTE9ZNnVRRlhsM3VoV21FclkxdDNRNXFxaGczUXR2OENSdkdldUd5ZzBZQ1RNd0doRjlYX1ZoZDJaUjIzNy01ZFkxd2swaldEeHB0VTVwbFZzMXVrWFJlOEpuTVJrZE51d1RnbHhXTTd0VQ?oc=5 ↩ ↩2 ↩3 ↩4

  2. https://doi.org/10.1176/appi.ajp.20240475 ↩ ↩2 ↩3 ↩4 ↩5 ↩6 ↩7

  3. https://www.biosourcesoftware.com/post/revitalizing-eeg-neurofeedback ↩ ↩2

  4. https://www.medxy.ai/news/cognition-guided-eeg-neurofeedback ↩

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