Alcohol use disorder is associated with increases in frontocentral phase-amplitude coupling strength during resting state.
paper
Primary
Public
Preprint
- Authors
- Richard, C D; Porjesz, B; Meyers, J L; Bingly, A; Chorlian, D B; Kamarajan, C; Pandey, G; Kuang, W; Pandey, A K; Kinreich, S
- Year
- 2025
- Journal
- bioRxiv : the preprint server for biology
- PMID
- 40463201
- DOI
- 10.1101/2025.05.13.653768
- PMCID
- PMC12132554
- Published as
- Alcohol use disorder is associated with altered frontomedial phase-amplitude coupling strength during resting state. →
Compromised functional connectivity in the brain seen in fMRI and EEG coherence is a key feature of alcohol use disorder (AUD). Phase-amplitude coupling (PAC) represents another mechanism by which functional connectivity is achieved, and to date, the role played by PAC in understanding the development of AUD has yet to be investigated. In the current study, we compare PAC strengths between participants with severe AUD, defined as presenting with 6 or more symptoms (DSM-5), and unaffected controls. Associations between phase-amplitude coupling and AUD status were assessed using frontal EEG signals acquired during the resting state eyes closed condition as part of the Collaborative Study on the Genetics of Alcoholism (COGA). COGA is a national project following families affected with AUD and comparison families for over 35 years with data collection in multiple domains. COGA participants between 25 and 50 years old with severe AUD were compared to an age-matched group of unaffected controls (Women: N = 360; Men: N = 406). PAC calculations were made on EEG recordings from midfrontal channel FZ to generate high resolution comodulograms covering phase frequencies between 0.1-13 Hz and amplitude frequencies between 4-50 Hz. Comodulograms were generated for each 30 second EEG segment for a given visit. Average comodulogram for a visit was calculated for the first two minutes of EEG in the resting state condition for subsequent statistical analyses. PAC differences between AUD and unaffected controls were assessed at each frequency pair using Mann-Whitney test, and the resulting effect sizes and p-values were used to generate difference comodulograms and significance comodulograms, respectively. Results showed that severe AUD was associated with greater alpha-gamma PAC in both men and women compared to the unaffected groups. Men with AUD exhibited significant increases in PAC across large parts of theta-gamma. In women with AUD, increases in theta-gamma PAC were restricted to smaller domains, and accompanied significant decreases in neighboring theta-gamma subdomains. PAC strength in theta-alpha and alpha-beta frequency pair domains were also significantly greater in AUD for both men and women. The AUD-associated changes in PAC strength within the alpha-gamma, theta-beta, alpha-beta, and to a lesser degree in theta-gamma domains indicates some form of aberrant hyperconnectivity between networks within the medial prefrontal cortex during resting state of the brain.
Differences in PAC strength between AUD and unaffected groups comodulograms by sex. (A) Effect size comodulograms depicting direction and magnitude of difference between groups for men (left) and women (right). Values reflect the mean change between AUD and unaffected groups (AUD – unaffected) with hot colors indicate greater PAC strength in AUD than in unaffected, and cool colors indicate reductions of PAC strength in AUD compared to unaffected. “Hotspots” of increased PAC strength in the AUD group can be seen across multiple PAC domains, most prominently in alpha-gamma, but also in theta-gamma, alpha-beta, and theta-alpha domains. (B) Initial set of significant PAC clusters by sex. Significant clusters appear where group differences in PAC strength at multiple, adjacent frequency pairs were found to be significant (Mann-Whitney, p < 0.05). Hot and cool colors indicate magnitude and direction of PAC differences within significant clusters. White regions indicate non-significance.
Cluster-bounding PAC domains where significant differences between AUD and unaffected groups were corroborated. Assessment of the initial set of significant clusters was made by comparing average PAC values from within phase-amplitude frequency pair domains framed around each of the initial set of significant clusters. Significant PAC differences were found in theta-gamma (A), alpha-gamma (B), theta-alpha (C), and alpha-beta (D) PAC domains in both men (top figures) and women (bottom figures). Bar graphs of PAC strength by group and PAC domain for each sex on right side of figure. See Table 2 for details of statistical results. Significance: p < 0.05 (*), p < 0.01 (**)
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| Citation | PMID | DOI | Status |
|---|---|---|---|
| AbernathyK., ChandlerL. J., & WoodwardJ. J. (2010). Alcohol and the Prefrontal Cortex. Functional Plasticity and Genetic Variation: Insights into the Neurobiology of Alcoholism, 91, 289–320. 10.1016/S0074-7742(10)91009-XPMC359306520813246 | — | — | — |
| AgrawalA., BrislinS. J., BucholzK. K., DickD., HartR. P., JohnsonE. C., MeyersJ., SalvatoreJ., SlesingerP., AlmasyL., ForoudT., GoateA., HesselbrockV., KramerJ., KupermanS., MerikangasA. K., NurnbergerJ. I., TischfieldJ., EdenbergH. J., & PorjeszB. (2023). The Collaborative Study on the Genetics of Alcoholism: Overview. Genes, Brain and Behavior, 22(5). 10.1111/gbb.12864PMC1055079037736010 | — | — | — |
| ArainM., HaqueM., JohalL., MathurP., NelW., RaisA., SandhuR., & SharmaS. (2013). Maturation of the adolescent brain. Neuropsychiatric Disease and Treatment, 9, 449–460. 10.2147/Ndt.S3977623579318 PMC3621648 | — | — | — |
| AriasA. J., MaL. S., BjorkJ. M., HammondC. J., ZhouY., SnyderA., & MoellerF. G. (2021). Altered effective connectivity of the reward network during an incentiveprocessing task in adults with alcohol use disorder. Alcoholism-Clinical and Experimental Research, 45(8), 1563–1577. 10.1111/acer.1465034120362 PMC8742221 | — | — | — |
| AxmacherN., HenselerM. M., JensenO., WeinreichI., ElgerC. E., & FellJ. (2010). Cross-frequency coupling supports multi-item working memory in the human hippocampus. In (Vol. 107).10.1073/pnas.0911531107PMC284028920133762 | — | — | — |
| BahramisharifA., MazaheriA., LevarN., Richard SchuurmanP., FigeeM., & DenysD. (2016). Deep Brain Stimulation Diminishes Cross-Frequency Coupling in Obsessive-Compulsive Disorder. In (Vol. 80).10.1016/j.biopsych.2015.05.02126166231 | — | — | — |
| BowlingJ. T., FristonK. J., & HopfingerJ. B. (2020). Top-down versus bottom-up attention differentially modulate frontal-parietal connectivity. Human Brain Mapping, 41(4), 928–942. 10.1002/hbm.2485031692192 PMC7267915 | — | — | — |
| BraginA., JandóG., NádasdyZ., HetkeJ., WiseK., & BuzsákiG. (1995). Gamma (40-100 Hz) oscillation in the hippocampus of the behaving rat. In (Vol. 15).10.1523/JNEUROSCI.15-01-00047.1995PMC65782737823151 | — | — | — |
| BuzsákiG. (2006). Rhythms of the Brain (1st paperback. ed.). Oxford University Press. | — | — | — |
| CamchongJ., StengerA., & FeinG. (2013a). Resting-State Synchrony in Long-Term Abstinent Alcoholics. Alcoholism-Clinical and Experimental Research, 37(1), 75–85. 10.1111/j.1530-0277.2012.01859.x22725701 PMC3493852 | — | — | — |
| CamchongJ., StengerV. A., & FeinG. (2013b). Resting-State Synchrony in Short-Term Versus Long-Term Abstinent Alcoholics. Alcoholism-Clinical and Experimental Research, 37(5), 794–803. 10.1111/acer.1203723421812 PMC3637430 | — | — | — |
| CanoltyR. T., & KnightR. T. (2010). The functional role of cross-frequency coupling. In (Vol. 14).10.1016/j.tics.2010.09.001PMC335965220932795 | — | — | — |
| CanoltyR. T., , KnightR. T., & (2010). The functional role of cross-frequency coupling. In (Vol. 14).10.1016/j.tics.2010.09.001PMC335965220932795 | — | — | — |
| CanoltyR. T., EdwardsE., DalalS. S., SoltaniM., NagarajanS. S., KirschH. E., BergerM. S., BarbareN. M., & KnightR. T. (2006). High gamma power is phase-locked to theta oscillations in human neocortex. In (Vol. 313).10.1126/science.1128115PMC262828916973878 | — | — | — |
| CardenasV. A., , PriceM., , FeinG., & (2018). EEG coherence related to fMRI resting state synchrony in long-term abstinent alcoholics. In (Vol. 17).10.1016/j.nicl.2017.11.008PMC568458129159061 | — | — | — |
| ChorlianD. B., TangY. Q., RangaswamyM., O’ConnorS., RohrbaughJ., TaylorR., & PorjeszB. (2007). Heritability of EEG coherence in a large sib-pair population. Biological psychology, 75(3), 260–266. 10.1016/j.biopsycho.2007.03.00617498861 PMC2270612 | — | — | — |
| CombrissonE., NestT., BrovelliA., InceR. A. A., SotoJ. L. P., GuillotA., & JerbiK. (2020). Tensorpac: An open-source Python toolbox for tensor-based phase-amplitude coupling measurement in electrophysiological brain signals. In (Vol. 16).10.1371/journal.pcbi.1008302PMC765476233119593 | — | — | — |
| ConstableR. T., ScheinostD., FinnE. S., ShenX., HampsonM., WinstanleyF. S., SpencerD. D., & PapademetrisX. (2013). Potential use and challenges of functional connectivity mapping in intractable epilepsy. In (Vol. 4 MAY).10.3389/fneur.2013.00039PMC366066523734143 | — | — | — |
| CorbettaM., & ShulmanG. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201–215. 10.1038/nrn75511994752 | — | — | — |
| de HemptinneC., Ryapolova-WebbE. S., AirE. L., GarciaP. A., MillerK. J., OjemannJ. G., OstremJ. L., GalifianakisN. B., & StarrP. A. (2013). Exaggerated phase-amplitude coupling in the primary motor cortex in Parkinson disease. Proceedings of the National Academy of Sciences of the United States of America, 110(12), 4780–4785. 10.1073/pnas.121454611023471992 PMC3606991 | — | — | — |
| DeshpandeG., WangY., & RobinsonJ. (2022). Resting state fMRI connectivity is sensitive to laminar connectional architecture in the human brain. Brain Informatics, 9(1). 10.1186/s40708-021-00150-4PMC876400135038072 | — | — | — |
| DickD. M., BalckeE., McCutcheonV., FrancisM., KuoS., SalvatoreJ., MeyersJ., BierutL. J., SchuckitM., HesselbrockV., EdenbergH. J., PorjeszB., KupermanS., KramerJ., & BucholzK. (2023). The collaborative study on the genetics of alcoholism: Sample and clinical data. Genes, Brain and Behavior, 22(5). 10.1111/gbb.12860PMC1055078737581339 | — | — | — |
| EhringerM. A. (2023). Collaborative study on the genetics of alcoholism: The strength of collaboration, team science, and longitudinal data. Genes Brain and Behavior, 22(5). 10.1111/gbb.12866PMC1055078537793903 | — | — | — |
| FattahiM., ModaberiS., EskandariK., & HaghparastA. (2023). A systematic review of the local field potential adaptations during conditioned place preference task in preclinical studies. Synapse-Structure Function Connectivity, 77(5). 10.1002/syn.2227737279942 | — | — | — |
| FeinG., CamchongJ., CardenasV. A., & StengerA. (2017). Resting state synchrony in long-term abstinent alcoholics: Effects of a current major depressive disorder diagnosis. Alcohol, 59, 17–25. 10.1016/j.alcohol.2016.11.00828262184 PMC5340076 | — | — | — |
| FigeeM., LuigjesJ., SmoldersR., Valencia-AlfonsoC. E., van WingenG., de KwaastenietB., MantioneM., OomsP., de KoningP., VulinkN., LevarN., DrogeL., van den MunckhofP., SchuurmanP. R., NederveenA., van den BrinkW., MazaheriA., VinkM., & DenysD. (2013). Deep brain stimulation restores frontostriatal network activity in obsessive-compulsive disorder. Nature Neuroscience, 16(4), 386–U195. 10.1038/nn.334423434914 | — | — | — |
| GhinF., BesteC., & StockA. K. (2022). Neurobiological mechanisms of control in alcohol use disorder – Moving towards mechanism-based non-invasive brain stimulation treatments. In (Vol. 133).10.1016/j.neubiorev.2021.12.03134942268 | — | — | — |
| GongR. X., MühlbergC., WegscheiderM., FrickeC., RumpfJ. J., KnöscheT. R., & ClassenJ. (2022). Cross-frequency phase-amplitude coupling in repetitive movements in patients with Parkinson’s disease. Journal of Neurophysiology, 127(6), 1606–1621. 10.1152/jn.00541.202135544757 PMC9190732 | — | — | — |
| GonzalezS. L., Reeb-SutherlandB. C., & NelsonE. L. (2016). Quantifying Motor Experience in the Infant Brain: EEG Power, Coherence, and Mu Desynchronization. Frontiers in Psychology, 7. https://doi.org/ARTN216 10.3389/fpsyg.2016.00216PMC475768026925022 | — | — | — |
| GuoY. J., ZhaoX. M., ZhangX. Z., LiM. P., LiuX. Y., LuL., LiuJ. Y., LiY., ZhangS., YueL. R., LiJ., LiuJ. X., ZhuY. Q., ZhuY. F., ShengX. N., YuD. H., & YuanK. (2023). Effects on resting-state EEG phase-amplitude coupling in insomnia disorder patients following 1 Hz left dorsolateral prefrontal cortex rTMS. Human Brain Mapping, 44(8), 3084–3093. 10.1002/hbm.2626436919444 PMC10171521 | — | — | — |
| HarrisonB. J., Soriano-MasC., PujolJ., OrtizH., López-SolàM., Hernández-RibasR., DeusJ., AlonsoP., YücelM., PantelisC., MenchonJ. M., & CardonerN. (2009). Altered Corticostriatal Functional Connectivity in Obsessive-compulsive Disorder. Archives of General Psychiatry, 66(11), 1189–1200. 10.1001/archgenpsychiatry.2009.15219884607 | — | — | — |
| HuberL., FinnE. S., ChaiY., GoebelR., StirnbergR., StöckerT., MarrettS., UludagK., KimS.-G., HanS., BandettiniP. A., & PoserB. A. (2021). Layer-dependent functional connectivity methods. Progress in Neurobiology, 207. 10.1016/j.pneurobio.2020.101835PMC1180014132512115 | — | — | — |
| HuS. Q., SteadM., DaiQ. H., & WorrellG. A. (2010). On the Recording Reference Contribution to EEG Correlation, Phase Synchorony, and Coherence. Ieee Transactions on Systems Man and Cybernetics Part B-Cybernetics, 40(5), 1294–1304. 10.1109/Tsmcb.2009.2037237PMC289157520106746 | — | — | — |
| JohnsonE. C., SalvatoreJ. E., LaiD., MerikangasA. K., NurnbergerJ. I., TischfieldJ. A., XueiX., KamarajanC., WetherillL., RiceJ. P., KramerJ. R., KupermanS., ForoudT., SlesingerP. A., GoateA. M., PorjeszB., DickD. M., EdenbergH. J., & AgrawalA. (2023). The collaborative study on the genetics of alcoholism: Genetics. Genes, Brain and Behavior, 22(5). 10.1111/gbb.12856PMC1055078837387240 | — | — | — |
| KamarajanC., ArdekaniB. A., PandeyA. K., ChorlianD. B., KinreichS., PandeyG., MeyersJ. L., ZhangJ., KuangW., StimusA. T., & PorjeszB. (2020). Random forest classification of alcohol use disorder using EEG source functional connectivity, neuropsychological functioning, and impulsivity measures. In (Vol. 10).10.3390/bs10030062PMC713932732121585 | — | — | — |
| KhanS., GramfortA., ShettyN. R., KitzbichlerM. G., GanesanS., MoranJ. M., LeeS. M., GabrieliJ. D. E., Tager-FlusbergH. B., JosephR. M., HerbertM. R., HämäläinenM. S., & KenetT. (2013). Local and long-range functional connectivity is reduced in concert in autism spectrum disorders. Proceedings of the National Academy of Sciences of the United States of America, 110(8), 3107–3112. 10.1073/pnas.121453311023319621 PMC3581984 | — | — | — |
| KinreichS., McCutcheonV. V., AlievF., MeyersJ. L., KamarajanC., PandeyA. K., ChorlianD. B., ZhangJ., KuangW. P., PandeyG., de ViteriS. S. S., FrancisM. W., ChanG., BourdonJ. L., DickD. M., AnokhinA. P., BauerL., HesselbrockV., SchuckitM. A.,…PorjeszB. (2021). Predicting alcohol use disorder remission: a longitudinal multimodal multi-featured machine learning approach. Translational psychiatry, 11(1). https://doi.org/ARTN166 10.1038/s41398-021-01281-2PMC796073433723218 | — | — | — |
| KinreichS., MeyersJ. L., Maron-KatzA., KamarajanC., PandeyA. K., ChorlianD. B., ZhangJ., PandeyG., de ViteriS. S. S., PittiD., AnokhinA. P., BauerL., HesselbrockV., SchuckitM. A., EdenbergH. J., & PorjeszB. (2021). Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study. Molecular Psychiatry, 26(4), 1133–1141. 10.1038/s41380-019-0534-x31595034 PMC7138692 | — | — | — |
| KlenowskiP. M. (2018). Emerging role for the medial prefrontal cortex in alcohol-seeking behaviors. In (Vol. 77).10.1016/j.addbeh.2017.09.02428992574 | — | — | — |
| KoobG. F., & VolkowN. D. (2016). Neurobiology of addiction: a neurocircuitry analysis. In (Vol. 3).10.1016/S2215-0366(16)00104-8PMC613509227475769 | — | — | — |
| KoobG. F., , VolkowN. D., & (2016). Neurobiology of addiction: a neurocircuitry analysis. In (Vol. 3).10.1016/S2215-0366(16)00104-8PMC613509227475769 | — | — | — |
| Le PelleyM. E., WatsonP., & WiersR. W. (2024). Biased Choice and Incentive Salience: Implications for Addiction. Behavioral Neuroscience, 138(4), 235–243. 10.1037/bne000058338780585 | — | — | — |
| LeeJ., & YunK. (2014). Alcohol reduces cross-frequency theta-phase gamma-amplitude coupling in resting electroencephalography. In (Vol. 38).10.1111/acer.1231024255944 | — | — | — |
| LegaB., BurkeJ., JacobsJ., & KahanaM. J. (2016). Slow-Theta-to-Gamma Phase-Amplitude Coupling in Human Hippocampus Supports the Formation of New Episodic Memories. In (Vol. 26).10.1093/cercor/bhu232PMC467797725316340 | — | — | — |
| LeocaniL., & ComiG. (1999). EEG coherence in pathological conditions. Journal of Clinical Neurophysiology, 16(6), 548–555. 10.1097/00004691-199911000-0000610600022 | — | — | — |
| LimpensJ. H. W., DamsteegtR., BroekhovenM. H., VoornP., & VanderschurenL. J. M. J. (2015). Pharmacological inactivation of the prelimbic cortex emulates compulsive reward seeking in rats. In (Vol. 1628).10.1016/j.brainres.2014.10.04525451128 | — | — | — |
| LinsenbardtD. N., TimmeN. M., & LapishC. C. (2019). Encoding of the intent to drink alcohol by the prefrontal cortex is blunted in rats with a family history of excessive drinking. In (Vol. 6).10.1523/ENEURO.0489-18.2019PMC671220431358511 | — | — | — |
| López-AzcárateJ., TaintaM., Rodríguez-OrozM. C., ValenciaM., GonzálezR., GuridiJ., IriarteJ., ObesoJ. A., ArtiedaJ., & AlegreM. (2010). Coupling between beta and high-frequency activity in the human subthalamic nucleus may be a pathophysiological mechanism in Parkinson’s disease. In (Vol. 30).10.1523/JNEUROSCI.5459-09.2010PMC663256620463229 | — | — | — |
| MarzettiL., BastiA., ChellaF., D’AndreaA., SyrjäläJ., & PizzellaV. (2019). Frontiers | Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography. Frontiers in Neuroscience, 13. 10.3389/fnins.2019.00964PMC675138231572116 | — | — | — |
| MeyersJ. L., BrislinS. J., KamarajanC., PlaweckiM. H., ChorlianD., AnohkinA., KupermanS., MerikangasA., PandeyG., KinreichS., PandeyA., EdenbergH. J., BucholzK. K., AlmasyL., & PorjeszB. (2023). The collaborative study on the genetics of alcoholism: Brain function. Genes, Brain and Behavior, 22(5). 10.1111/gbb.12862PMC1055079137587903 | — | — | — |
| MeyersJ. L., ZhangJ., ChorlianD. B., PandeyA. K., KamarajanC., WangJ. C., WetherillL., LaiD., ChaoM., ChanG., KinreichS., KapoorM., BertelsenS., McClintickJ., BauerL., HesselbrockV., KupermanS., KramerJ., SalvatoreJ. E.,…PorjeszB. (2021). A genome-wide association study of interhemispheric theta EEG coherence: implications for neural connectivity and alcohol use behavior. In (Vol. 26).10.1038/s41380-020-0777-6PMC850386032433515 | — | — | — |
| MusaeusC. S., NielsenM. S., MusaeusJ. S., & HoghP. (2020). Electroencephalographic Cross-Frequency Coupling as a Sign of Disease Progression in Patients With Mild Cognitive Impairment: A Pilot Study. Frontiers in Neuroscience, 14. https://doi.org/ARTN790 10.3389/fnins.2020.00790PMC743163432848563 | — | — | — |
| NestorL., McCabeE., JonesJ., ClancyL., & GaravanH. (2011). Differences in “bottom-up” and “top-down” neural activity in current and former cigarette smokers: Evidence for neural substrates which may promote nicotine abstinence through increased cognitive control. Neuroimage, 56(4), 2258–2275. 10.1016/j.neuroimage.2011.03.05421440645 | — | — | — |
| NukitramJ., CheahaD., & KumarnsitE. (2021). Spectral power and theta-gamma coupling in the basolateral amygdala related with methamphetamine conditioned place preference in mice. In (Vol. 756).10.1016/j.neulet.2021.13593933945805 | — | — | — |
| PorjeszB., & RangaswamyM. (2007). Neurophysiological Endophenotypes, CNS Disinhibition, and Risk for Alcohol Dependence and Related Disorders. The Scientific World Journal, 7(1). 10.1100/tsw.2007.203PMC590135017982586 | — | — | — |
| RangaswamyM., PorjeszB., ChorlianD. B., WangK. M., JonesK. A., BauerL. O., RohrbaughJ., O’ConnorS. J., KupermanS., ReichT., & BegleiterH. (2002). Beta power in the EEG of alcoholics. Biological Psychiatry, 52(8), 831–842. https://doi.org/PiiS0006-3223(02)010362-8 Doi 10.1016/S0006-3223(02)01362-812372655 | — | — | — |
| RangaswamyM., PorjeszB., ChorlianD. B., WangK. M., JonesK. A., KupermanS., RohrbaughJ., O’ConnorS. J., BauerL. O., ReichT., & BegleiterH. (2004). Resting EEG in offspring of male alcoholics: beta frequencies. International Journal of Psychophysiology, 51(3), 239–251. 10.1016/j.ijpsycho.2003.09.00314962576 | — | — | — |
| RaussK., & PourtoisG. (2013). What is bottom-up and what is top-down in predictive coding? Frontiers in Psychology, 4. https://doi.org/ARTN276 10.3389/fpsyg.2013.00276PMC365634223730295 | — | — | — |
| SamerphobN., CheahaD., ChatpunS., & KumarnsitE. (2017). Hippocampal CAl local field potential oscillations induced by olfactory cue of liked food. Neurobiology of Learning and Memory, 142, 173–181. 10.1016/j.nlm.2017.05.01128532653 | — | — | — |
| SongH. W., YangP., ZhangX. Y., TaoR., ZuoL., LiuW. L., FuJ. X., KongZ., TangR., WuS. Y., PangL. J., & ZhangX. C. (2024). Atypical effective connectivity from the frontal cortex to striatum in alcohol use disorder. Translational psychiatry, 14(1). https://doi.org/ARTN381 10.1038/s41398-024-03083-8PMC1141113739294121 | — | — | — |
| SpaakE., BonnefondM., MaierA., LeopoldD. A., & JensenO. (2012). Layer-specific entrainment of gamma-band neural activity by the alpha rhythm in monkey visual cortex. In (Vol. 22).10.1016/j.cub.2012.10.020PMC352883423159599 | — | — | — |
| SrinivasanR., WinterW. R., DingJ., & NunezP. L. (2007). EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics. Journal of Neuroscience Methods, 166(1), 41–52. 10.1016/j.jneumeth.2007.06.02617698205 PMC2151962 | — | — | — |
| SukJ. W., HwangS., & CheongC. (2021). Functional and Structural Alteration of Default Mode, Executive Control, and Salience Networks in Alcohol Use Disorder. In (Vol. 12).10.3389/fpsyt.2021.742228PMC856449534744834 | — | — | — |
| SunN., ChiN., LauzonN., BishopS., TanH., & LavioletteS. R. (2011). Acquisition, extinction, and recall of opiate reward memory are signaled by dynamic neuronal activity patterns in the prefrontal cortex. In (Vol. 21).10.1093/cercor/bhr03121531781 | — | — | — |
| TreuS., Gonzalez-RosaJ. J., Soto-LeonV., Lozano-SoldevillaD., OlivieroA., Lopez-SosaF., Reneses-PrietoB., BarciaJ. A., & StrangeB. A. (2021). A ventromedial prefrontal dysrhythmia in obsessive-compulsive disorder is attenuated by nucleus accumbens deep brain stimulation. In (Vol. 14).10.1016/j.brs.2021.04.02833984535 | — | — | — |
| van BeijsterveldtC. E., MolenaarP. C., de GeusE. J., & BoomsmaD. I. (1996). Heritability of human brain functioning as assessed by electroencephalography. Am J Hum Genet, 58(3), 562–573. https://www.ncbi.nlm.nih.gov/pubmed/86447168644716 PMC1914558 | — | — | — |
| van BreeS., LevensteinD., KrauseM. R., VoytekB., & GaoR. (2025). Processes and measurements: a framework for understanding neural oscillations in field potentials. Trends in Cognitive Sciences. 10.1016/j.tics.2024.12.00339753446 | — | — | — |
| van WijkB. C. M., BeudelM., JhaA., OswalA., FoltynieT., HarizM. I., LimousinP., ZrinzoL., AzizT. Z., GreenA. L., BrownP., & LitvakV. (2016). Subthalamic nucleus phase-amplitude coupling correlates with motor impairment in Parkinson’s disease. In (Vol. 127).10.1016/j.clinph.2016.01.015PMC480302226971483 | — | — | — |
| WangH. E., BénarC. G., QuilichiniP. P., FristonK. J., JirsaV. K., & BernardC. (2014). A systematic framework for functional connectivity measures. In (Vol. 8, pp. 111632): Frontiers Research Foundation.10.3389/fnins.2014.00405PMC426048325538556 | — | — | — |
| WoisardK., SteinbergJ. L., MaL., ZunigaE., RameyT., LennonM., Keyser-MarcusL., & MoellerF. G. (2021). Preliminary Findings of Weaker Executive Control Network Resting State fMRI Functional Connectivity in Opioid Use Disorder compared to Healthy Controls HHS Public Access. In (Vol. 12).PMC983604336643376 | — | — | — |
| WulffP., PonomarenkoA. A., BartosM., KorotkovaT. M., FuchsE. C., BähnerF., BothM., TortA. B. L., KopellN. J., WisdenW., & MonyerH. (2009). Hippocampal theta rhythm and its coupling with gamma oscillations require fast inhibition onto parvalbumin-positive interneurons. In (Vol. 106).10.1073/pnas.0813176106PMC263790719204281 | — | — | — |
| YakubovB., DasS., ZomorrodiR., BlumbergerD. M., EnticottP. G., KirkovskiM., RajjiT. K., & DesarkarP. (2022). Cross-frequency coupling in psychiatric disorders: A systematic review. In (Vol. 138).10.1016/j.neubiorev.2022.10469035569580 | — | — | — |
| YinZ. X., ZhuG. Y., LiuY. Y., ZhaoB. T., LiuD. F., BaiY. T., ZhangQ., ShiL., FengT., YangA. C., LiuH. G., MengF. G., NeumannW. J., KühnA. A., JiangY., & ZhangJ. G. (2022). Cortical phase-amplitude coupling is key to the occurrence and treatment of freezing of gait. Brain, 145(7), 2407–2421. 10.1093/brain/awac12135441231 PMC9337810 | — | — | — |
| ZhuZ., YeZ., WangH., HuaT., WenQ., & ZhangC. (2019). Theta–gamma coupling in the prelimbic area is associated with heroin addiction. In (Vol. 701).10.1016/j.neulet.2019.02.02030769004 | — | — | — |
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