An EEG-based marker of functional connectivity: detection of major depressive disorder

Afshani F, Shalbaf A, Shalbaf R, Sleigh J (2019) Frontal-temporal functional connectivity of EEG signal by standardized permutation mutual information during anesthesia. Cogn Neurodyn 13:531–540. https://doi.org/10.1007/s11571-019-09553-w

Article  PubMed  PubMed Central  Google Scholar 

Ahmadi A, Davoudi S, Daliri MR (2019) Computer aided diagnosis system for multiple sclerosis disease based on phase to amplitude coupling in covert visual attention. Comput Methods Programs Biomed 169:9–18. https://doi.org/10.1016/j.cmpb.2018.11.006

Article  PubMed  Google Scholar 

Ahn J, Han DH, Hong JS, Min KJ, Lee YS, Hahm BJ, Kim SM (2017) Features of resting-state electroencephalogram theta coherence in somatic symptom disorder compared with major depressive disorder: a pilot study. Psychosom Med 79:982–987. https://doi.org/10.1097/PSY.0000000000000490

Article  PubMed  Google Scholar 

Akbari H, Sadiq MT, Rehman AU, Ghazvini M, Naqvi RA, Payan M, Bagheri H, Bagheri H (2021) Depression recognition based on the reconstruction of phase space of EEG signals and geometrical features. Appl Acoust. https://doi.org/10.1016/j.apacoust.2021.108078

Article  Google Scholar 

Allen EA, Damaraju E, Plis SM, Erhardt EB, Eichele T, Calhoun VD (2014) Tracking whole-brain connectivity dynamics in the resting state. Cereb Cortex 24:663–676. https://doi.org/10.1093/cercor/bhs352

Article  PubMed  Google Scholar 

Aubert-Broche B, Evans AC, Collins L (2006) A new improved version of the realistic digital brain phantom. Neuroimage 32:138–145. https://doi.org/10.1016/j.neuroimage.2006.03.052

Article  PubMed  Google Scholar 

Axer M, Amunts K (2022) Scale matters: the nested human connectome. Science 378:500–504. https://doi.org/10.1126/science.abq2599

Article  CAS  PubMed  Google Scholar 

Aydemir E, Tuncer T, Dogan S, Gururajan R, Acharya UR (2021) Automated major depressive disorder detection using melamine pattern with EEG signals. Appl Intell 51:6449–6466. https://doi.org/10.1007/s10489-021-02426-y

Article  Google Scholar 

Aydin S, Cetin FH, Uytun MC, Babadagi Z, Gueven AS, Isik Y (2022) Comparison of domain specific connectivity metrics for estimation brain network indices in boys with ADHD-C. Biomed Signal Process Control. https://doi.org/10.1016/j.bspc.2022.103626

Article  Google Scholar 

Babiloni F, Cincotti F, Babiloni C, Carducci F, Mattia D, Astolfi L, Basilisco A, Rossini PM, Ding L, Ni Y, Cheng J, Christine K, Sweeney J, He B (2005) Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function. Neuroimage 24:118–131. https://doi.org/10.1016/j.neuroimage.2004.09.036

Article  CAS  PubMed  Google Scholar 

Cao J, Zhao YF, Shan XC, Wei HL, Guo YZ, Chen LY, Erkoyuncu JA, Sarrigiannis PG (2022) Brain functional and effective connectivity based on electroencephalography recordings: a review. Hum Brain Mapp 43:860–879. https://doi.org/10.1002/hbm.25683

Article  PubMed  Google Scholar 

Cavanagh JF, Bismark AW, Frank MJ, Allen JJB (2019) Multiple dissociations between comorbid depression and anxiety on reward and punishment processing: evidence from computationally informed EEG. Comput Psychiatr 3:1–17. https://doi.org/10.1162/cpsy_a_00024

Article  PubMed  PubMed Central  Google Scholar 

Chang CY, Hsu SH, Pion-Tonachini L, Jung TP (2018) Evaluation of artifact subspace reconstruction for automatic EEG artifact removal. Annu Int Conf IEEE Eng Med Biol Soc 2018:1242–1245. https://doi.org/10.1109/EMBC.2018.8512547

Article  PubMed  Google Scholar 

Cooper J (2001) Diagnostic and Statistical Manual of Mental Disorders (4th edn, text revision) (DsM-IV-TR). British Journal of Psychiatry. 179: 85–85. https://doi.org/10.1192/bjp.179.1.85-a

Daubechies I, Lu JF, Wu HT (2011) Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool. Appl Comput Harmon Anal 30:243–261. https://doi.org/10.1016/j.acha.2010.08.002

Article  Google Scholar 

Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Liston C (2017) Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med 23:28–38. https://doi.org/10.1038/nm.4246

Article  CAS  PubMed  Google Scholar 

Duan L, Duan H, Qiao Y, Sha S, Qi S, Zhang X, Huang J, Huang X, Wang C (2020) Machine learning approaches for MDD detection and emotion decoding using EEG signals. Front Hum Neurosci 14:284. https://doi.org/10.3389/fnhum.2020.00284

Article  PubMed  PubMed Central  Google Scholar 

Evans-Lacko S, Aguilar-Gaxiola S, Al-Hamzawi A, Alonso J, Benjet C, Bruffaerts R, Chiu WT, Florescu S, de Girolamo G, Gureje O, Haro JM, He Y, Hu C, Karam EG, Kawakami N, Lee S, Lund C, Kovess-Masfety V, Levinson D, Thornicroft G (2018) Socio-economic variations in the mental health treatment gap for people with anxiety, mood, and substance use disorders: results from the WHO World Mental Health (WMH) surveys. Psychol Med 48:1560–1571. https://doi.org/10.1017/S0033291717003336

Article  CAS  PubMed  Google Scholar 

Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, Vos T, Whiteford HA (2013) Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med 10:e1001547. https://doi.org/10.1371/journal.pmed.1001547

Article  PubMed  PubMed Central  Google Scholar 

Fu Z, Iraji A, Turner JA, Sui J, Miller R, Pearlson GD, Calhoun VD (2021) Dynamic state with covarying brain activity-connectivity: on the pathophysiology of schizophrenia. Neuroimage 224:117385. https://doi.org/10.1016/j.neuroimage.2020.117385

Article  PubMed  Google Scholar 

Geng XL, Fan XW, Zhong YW, Casanova MF, Sokhadze EM, Li XL, Kang JN (2023) Abnormalities of EEG functional connectivity and effective connectivity in children with autism spectrum disorder. Brain Sci. https://doi.org/10.3390/brainsci13010130

Article  PubMed  PubMed Central  Google Scholar 

Gloss D, Varma JK, Pringsheim T, Nuwer MR (2016) Practice advisory: the utility of EEG theta/beta power ratio in ADHD diagnosis: report of the guideline development, dissemination, and implementation subcommittee of the American academy of neurology. Neurology 87:2375–2379. https://doi.org/10.1212/WNL.0000000000003265

Article  PubMed  PubMed Central  Google Scholar 

Grinsted A, Moore JC, Jevrejeva S (2004) Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys 11:561–566. https://doi.org/10.5194/npg-11-561-2004

Article  Google Scholar 

Holmes CJ, Hoge R, Collins L, Woods R, Toga AW, Evans AC (1998) Enhancement of MR images using registration for signal averaging. J Comput Assist Tomogr 22:324–333. https://doi.org/10.1097/00004728-199803000-00032

Article  CAS  PubMed  Google Scholar 

Jewell NP, Lewnard JA, Jewell BL (2020) Caution warranted: using the institute for health metrics and evaluation model for predicting the course of the COVID-19 pandemic. Ann Intern Med 173:226–227. https://doi.org/10.7326/M20-1565

Article  PubMed  Google Scholar 

Khan DM, Masroor K, Jailani MFM, Yahya N, Yusoff MZ, Khan SM (2022) Development of wavelet coherence EEG as a biomarker for diagnosis of major depressive disorder. IEEE Sens J 22:4315–4325. https://doi.org/10.1109/Jsen.2022.3143176

Article  Google Scholar 

Klem GH, Luders HO, Jasper HH, Elger C (1999) The ten-twenty electrode system of the international federation. The international federation of clinical neurophysiology. Electroencephalogr Clin Neurophysiol Suppl 52:3–6

CAS  PubMed  Google Scholar 

Lachaux JP, Rodriguez E, Martinerie J, Varela FJ (1999) Measuring phase synchrony in brain signals. Hum Brain Mapp 8:194–208. https://doi.org/10.1002/(sici)1097-0193(1999)8:4%3c194::aid-hbm4%3e3.0.co;2-c

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lee JH, Liu Q, Dadgar-Kiani E (2022) Solving brain circuit function and dysfunction with computational modeling and optogenetic fMRI. Science 378:493–499. https://doi.org/10.1126/science.abq3868

Article  CAS  PubMed  PubMed Central  Google Scholar 

Li XW, Jing Z, Hu B, Sun ST (2016) An EEG-based study on coherence and brain networks in mild depression cognitive process. Ieee Int Conf Bioinform Biomed (bibm). https://doi.org/10.1109/bibm.2016.7822702

Article  Google Scholar 

Li X, La R, Wang Y, Hu B, Zhang X (2020a) A deep learning approach for mild depression recognition based on functional connectivity using electroencephalography. Front Neurosci. https://doi.org/10.3389/fnins.2020.00192

Article  PubMed  PubMed Central  Google Scholar 

Li M, Xia L, Yang Y, Zhang L, Zhang S, Liu T, Liu Y, Kaslow NJ, Jiang F, Tang YL, Liu H (2022) Depression, anxiety, stress, and their associations with quality of life in a nationwide sample of psychiatrists in china during the COVID-19 pandemic. Front Psychol 13:881408. https://doi.org/10.3389/fpsyg.2022.881408

Article  PubMed  PubMed Central  Google Scholar 

Loh HW, Ooi CP, Aydemir E, Tuncer T, Dogan S, Acharya UR (2021) Decision support system for major depression detection using spectrogram and convolution neural network with EEG signals. Exp Syst. https://doi.org/10.1111/exsy.12773

Article  Google Scholar 

McVoy M, Aebi ME, Loparo K, Lytle S, Morris A, Woods N, Deyling E, Tatsuoka C, Kaffashi F, Lhatoo S, Sajatovic M (2019) Resting-state quantitative electroencephalography demonstrates differential connectivity in adolescents with major depressive disorder. J Child Adolesc Psychopharmacol 29:370–377. https://doi.org/10.1089/cap.2018.0166

Article  PubMed  PubMed Central  Google Scholar 

Mohammadi Y, Moradi MH (2021) Prediction of depression severity scores based on functional connectivity and complexity of the EEG signal. Clin EEG Neurosci 52:52–60. https://doi.org/10.1177/1550059420965431

Article  PubMed  Google Scholar 

留言 (0)

沒有登入
gif