Metraipolis › archive › dc_878fa7b75bec

Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders — Europe PMC PMID:34506492

Source: Europe PMC (en)
Original: https://europepmc.org/article/MED/34506492
DOI: 10.1371/journal.pone.0248794
License (as archived): CC0-1.0
Archived: 2026-11-02T22:26:54.703Z
SHA-256 of the archived text: 2360174df5759fedfa96643ef87671233b640be756166bf26ad0d7b3dec41e91
Stable URL of this page: https://metraipolis.com/documento/dc_878fa7b75bec

How to cite

Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders — Europe PMC PMID:34506492 — Europe PMC (en), https://europepmc.org/article/MED/34506492 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_878fa7b75bec (Metraipolis archive dc_878fa7b75bec, sha256 2360174df5759fedfa96643ef87671233b640be756166bf26ad0d7b3dec41e91)

BibTeX

@misc{dc878fa7b75bec,
  title = {Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders — Europe PMC PMID:34506492},
  howpublished = {Europe PMC (en)},
  url = {https://europepmc.org/article/MED/34506492},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_878fa7b75bec; sha256 2360174df5759fedfa96643ef87671233b640be756166bf26ad0d7b3dec41e91},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: Europe PMC (en), https://europepmc.org/article/MED/34506492. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Electroencephalography (EEG) likely reflects activity of cortical neurocircuits, making it an insightful estimation for mental health in patients with substance use disorder (SUD). EEG signals are recorded as sinusoidal waves, containing spectral amplitudes across several frequency bands with high spatio-temporal resolution. Prior work on EEG signal analysis has been made mainly at individual electrodes. These signals can be evaluated from advanced aspects, including sub-regional and hemispheric analyses. Due to limitation of computational techniques, few studies in earlier work could conduct data analyses from these aspects. Therefore, EEG in patients with SUD is not fully understood. In the present retrospective study, spectral powers from a data house containing opioid (OUD), methamphetamine/stimulants (MUD), and alcohol use disorder (AUD) were extracted, and then converted into five distinct topographic data (i.e., electrode-based, cortical subregion-based, left-right hemispheric, anterior-posterior based, and total cortex-based analyses). We found that data conversion and reorganization in the topographic way had an impact on EEG spectral powers in patients with OUD significantly different from those with MUD or AUD. Differential changes were observed from multiple perspectives, including individual electrodes, subregions, hemispheres, anterior-posterior cortices, and across the cortex as a whole. Understanding the differential changes in EEG signals may be useful for future work with machine learning and artificial intelligence (AI), not only for diagnostic but also for prognostic purposes in patients with SUD.

Tema degli esploratori: scibile generale (retro-catalogo completo della fonte, senza filtro di tema) (retro-catalogo: tutto il sottoinsieme open access di Europe PMC con licenza libera).
Pubblicazione: PloS one, 2021 (prima pubblicazione 2021-09-10).
Identificativi: PMID 34506492 · PMCID PMC8432824 · DOI 10.1371/journal.pone.0248794.
Pagina: https://europepmc.org/article/MED/34506492 — https://doi.org/10.1371/journal.pone.0248794. Autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza dell'articolo dichiarata da Europe PMC: CC0 (la versione è indicata dall'editore sulla pagina). Abstract riportato senza modifiche al contenuto, con attribuzione; deposito marcato CC0.
Letto il 2026-11-02T22:18:39.952Z tramite l'API REST ufficiale di Europe PMC (EMBL-EBI), nel rispetto del robots.txt e del crawl-delay.