Abstract:Depression is a common and acute mental disease and cognitive impairment is one of the core symptoms of depression, which greatly affects the daily life of patients and imposes a heavy burden on the family and the society. However, effective rehabilitation methods for cognitive impairment in depression are still lacking, the relevant neural mechanism remains unclear, and therapeutic effects vary greatly from individual to individual. Electroencephalogram (EEG) neurofeedback has attracted more and more attention because it is safe, non-invasive, and without side effects. This paper reviewed the EEG features of cognitive impairment in depression, introduced existing EEG neurofeedback training studies based on these features, and discussed the current problems and future development. With the rapid development of neurofeedback techniques and a deep understanding of the underlying mechanisms, EEG neurofeedback has the potential to be a useful tool in cognitive rehabilitation of depression.
[1] Miret M, Ayuso-Mateos JL, Sanchez-Moreno J, et al. Depressive disorders and suicide: Epidemiology, risk factors, and burden [J]. Neurosci Biobehav Rev, 2013, 37(10): 2372-2374. [2] World Health Organization. Depression and other common mental disorders: Global estimates [R]. 2017. [3] GBD 2015 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: A systematic analysis for the Global Burden of Disease Study 2015 [J]. Lancet, 2016, 388(10053): 1545-1602. [4] American Psychological Association. Diagnostic and statistical manual for mental disorders: DSM-5 [R]. 2013. [5] Rock PL, Roiser JP, Riedel WJ, et al. Cognitive impairment in depression: A systematic review and meta-analysis[J]. Psychol Med, 2014, 44(10): 2029-2040. [6] American Psychological Association. Diagnostic and statistical manual of mental disorders [R]. 2000. [7] Bhalla RK, Butters MA, Mulsant BH, et al. Persistence of neuropsychologic deficits in the remitted state of late-life depression [J]. Am J Geriatr Psychiatry, 2006, 14(5): 419-427. [8] Lundbeck H. FDA updates trintellix (vortioxetine) label to include data showing improvement in processing speed, an important aspect of cognitive function in acute major depressive disorder (MDD) [EB/OL]. 2020/2020-05-04. [9] Miskowiak KW, Kessing LV, Ott CV, et al. Does a single session of electroconvulsive therapy alter the neural response to emotional faces in depression? A randomised sham-controlled functional magnetic resonance imaging study [J]. J Psychopharmacol, 2017, 31(9): 1215-1224. [10] Razza LB, Moffa AH, Moreno ML, et al. A systematic review and meta-analysis on placebo response to repetitive transcranial magnetic stimulation for depression trials [J]. Prog Neuropsychopharmacol Biol Psychiatry, 2018, 81: 105-113. [11] Millet B, Jaafari N, Polosan M, et al. Limbic versus cognitive target for deep brain stimulation in treatment-resistant depression: accumbens more promising than caudate [J]. Eur Neuropsychopharmacol, 2014, 24(8): 1229-1239. [12] Palm U, Hasan A, Strube W, et al. tDCS for the treatment of depression: a comprehensive review [J]. Eur Arch Psychiatry Clin Neurosci, 2016, 266(8): 681-694. [13] Enriquez-Geppert S, Huster RJ, Herrmann CS. EEG-neurofeedback as a tool to modulate cognition and behavior: A review tutorial [J]. Front Hum Neurosci, 2017, 11: 51. [14] Markiewcz R. The use of EEG Biofeedback/Neurofeedback in psychiatric rehabilitation [J]. Psychiatr Pol, 2017, 51(6): 1095-1106. [15] Peeters F, Oehlen M, Ronner J, et al. Neurofeedback as a treatment for major depressive disorder-A pilot study [J]. PLoS ONE, 2014, 9(3): e91837. [16] Davidson RJ. Anterior cerebral asymmetry and the nature of emotion [J]. Brain Cogn,1992, 20 (1): 125-151. [17] Wang SY, Lin IM, Fan SY, et al. The effects of alpha asymmetry and high-beta down-training neurofeedback for patients with the major depressive disorder and anxiety symptoms [J]. J Affect Disord, 2019, 257: 287-296. [18] Hardt JV. Alpha brain-wave neurofeedback training reduces psychopathology in a cohort of male and female Canadian aboriginals [J]. Adv Mind Body Med, 2012, 26(2): 8-12. [19] Baehr E, Rosenfeld P, Baehr R. The clinical use of an alpha asymmetry protocol in the neurofeedback treatment of depression: Two case studies [J]. J Neurothe, 1997, 2(3): 10-23. [20] Brzezicka A, Kamiński J, Kamińska OK, et al. Frontal EEG alphaalpha band asymmetry as a predictor of reasoning deficiency in depressed people [J]. Cogn Emot, 2017, 31(5): 868-878. [21] Pizzagalli DA. Frontocingulate dysfunction in depression: Toward biomarkers of treatment response [J]. Neuropsychopharmacology, 2011, 36(1): 183-206. [22] Smart OL, Tiruvadi VR, Mayberg HS. Multimodal approaches to define network oscillations in depression [J]. Biol Psychiatry, 2015, 77(12): 1061-1070. [23] Dharmadhikari AS, Tandle AL, Jaiswal SV, et al. Frontal theta asymmetry as a biomarker of depression [J]. East Asian Arch Psychiatry, 2018, 28(1): 17-22. [24] Chen TC, Lin IM. The learning effects and curves during high beta down-training neurofeedback for patients with major depressive disorder [J]. J Affect Disord, 2020,266: 235-242. [25] Grin-Yatsenko VA, Baas I, Ponomarev VA, et al. Independent component approach to the analysis of EEG recordings at early stages of depressive disorders [J]. Clin Neurophysiol, 2010, 121(3): 281-289. [26] Choi SW, Chi SE, Chung SY, et al. Is alpha wave neurofeedback effective with randomized clinical trials in depression? A pilot study [J]. Neuropsychobiology, 2011, 63(1): 43-51. [27] Peeters F, Ronner J, Bodar L, et al. Validation of a neurofeedback paradigm: manipulating frontal EEG alpha-activity and its impact on mood [J]. Int J Psychophysiol, 2014, 93(1): 116-120. [28] Escolano C, Navarro-Gil M, Garcia-Campayo J, et al. A controlled study on the cognitive effect of alpha neurofeedback training in patients with major depressive disorder [J]. Front Behav Neurosci, 2014, 8: 296. [29] Cheon EJ, Koo BH, Choi JH. The efficacy of neurofeedback in patients with major depressive disorder: An open labeled prospective study [J]. Appl Psychophysiol Biofeedback, 2016, 41(1): 103-110. [30] Lee YJ, Lee GW, Seo WS, et al. Neurofeedback treatment on depressive symptoms and functional recovery in treatment-resistant patients with major depressive disorder: An open-label pilot study [J]. J Korean Med Sci, 2019, 34(42): e287. [31] Marzbani H, Marateb HR, Mansourian M. Neurofeedback: A comprehensive review on system design, methodology and clinical applications [J]. Basic Clin Neurosci, 2016, 7(2): 143-158. [32] Begemann MJH, Florisse EJR, van Lutterveld R, et al. Efficacy of EEG neurofeedback in psychiatry: A comprehensive overview and meta-analysis [J]. Translational Brain Rhythmicity, 2016, 1(1): 19-29. [33] Schabus M. Reply: Noisy but not placebo: Defining metrics for effects of neurofeedback [J]. Brain, 2018, 141(5): e41. [34] Micoulaud-Franchi JA, Geoffroy PA, Fond G, et al. EEG neurofeedback treatments in children with ADHD: An updated meta-analysis of randomized controlled trials [J]. Front Hum Neurosci, 2014, 8: 906. [35] Thibault RT, Lifshitz M, Raz A. The self-regulating brain and neurofeedback: Experimental science and clinical promise [J]. Cortex, 2016, 74: 247-261. [36] Omejc N, Rojc B, Battaglini PP, et al. Review of the therapeutic neurofeedback method using electroencephalography: EEG Neurofeedback [J]. Bosn J Basic Med Sci, 2019, 19(3): 213-220. [37] Alkoby O, Abu-Rmileh A, Shriki O, et al. Can we predict who will respond to neurofeedback? A review of the inefficacy problem and existing predictors for successful EEG neurofeedback learning [J]. Neuroscience, 2018, 378: 155-164. [38] Gruzelier JH. EEG-neurofeedback for optimising performance. III: A review of methodological and theoretical considerations [J]. Neuroscience & Biobehavioral Reviews, 2014, 44: 159-182. [39] Linden DE. Neurofeedback and networks of depression [J]. Dialogues Clin Neurosci, 2014, 16(1): 103-112. [40] Engelbregt HJ, Keeser D, van Eijk L, et al. Short and long-term effects of sham-controlled prefrontal EEG-neurofeedback training in healthy subjects [J]. Clin Neurophysiol, 2016, 127(4): 1931-1937. [41] Sitaram R, Ros T, Stoeckel L, et al. Closed-loop brain training:The science of neurofeedback [J]. Nat Rev Neurosci, 2017, 18(2): 86-100. [42] Hamilton JP, Glover GH, Bagarinao E, et al. Effects of salience-network-node neurofeedback training on affective biases in major depressive disorder [J]. Psychiatry Research: Neuroimaging, 2016, 249: 91-96. [43] Malykhin NV, Carter R, Seres P, Coupland NJ. Structural changes in the hippocampus in major depressive disorder: contributions of disease and treatment [J]. J Psychiatry Neurosci, 2010, 35(5): 337-343. [44] Bora E, Fornito A, Pantelis C, Yücel M. Gray matter abnormalities in Major Depressive Disorder: a meta-analysis of voxel based morphometry studies [J]. J Affect Disord, 2012, 138(1-2): 9-18. [45] Bauer RH. Short-term memory: EEG alpha correlates and the effect of increased alpha [J]. Behav Biol, 1976, 17(4): 425-433. [46] Nan W, Rodrigues JP, Ma J, et al. Individual alpha neurofeedback training effect on short term memory [J]. Int J Psychophysiol, 2012, 86(1): 83-87. [47] Hammond DC. The need for individualization in neurofeedback: heterogeneity in QEEG patterns associated with diagnoses and symptoms [J]. Appl Psychophysiol Biofeedback, 2010, 35(1): 31-36. [48] Fingelkurts AA, Fingelkurts AA, Rytsälä H, et al. Impaired functional connectivity at EEG alpha and theta frequency bands in major depression [J]. Hum Brain Mapp, 2007, 28(3): 247-261. [49] Lee TW, Wu YT, Yu YW, et al. The implication of functional connectivity strength in predicting treatment response of major depressive disorder: a resting EEG study [J]. Psychiatry Res, 2011, 194(3): 372-377. [50] Schiller MJ. Quantitative electroencephalography in guiding treatment of major depression [J]. Front Psychiatry, 2019, 9: 779. [51] Damborská A, Honzírková E, Bartecˇek R, et al. Altered directed functional connectivity of the right amygdala in depression: high-density EEG study [J]. Sci Rep, 2020, 10(1): 4398. [52] Koush Y, Meskaldji DE, Pichon S, et al. Learning control over emotion networks through connectivity-based neurofeedback [J]. Cereb Cortex, 2017, 27(2): 1193-1202. [53] Nikolin S, Martin D, Loo CK, et al. Assessing neurophysiological changes associated with combined transcranial direct current stimulation and cognitive-emotional training for treatment-resistant depression [J]. Eur J Neurosci, 2020,51(10):2119-2133. [54] Gonda X, Pompili M, Serafini G, et al. The role of cognitive dysfunction in the symptoms and remission from depression [J]. Ann Gen Psychiatry, 2015, 14: 27. [55] Albert J, López-Martín S, Carretié L. Emotional context modulates response inhibition: Neural and behavioral data [J]. Neuroimage, 2010, 49(1): 914-921. [56] Erickson K, Drevets WC, Clark L, et al. Mood-congruent bias in affective go/no-go performance of unmedicated patients with major depressive disorder [J]. Am J Psychiatry, 2005, 162(11): 2171-2173. [57] Zhang D, Xie H, He Z, et al. Impaired working memory updating for emotional stimuli in depressed patients [J]. Front Behav Neurosci, 2018, 12: 65. [58] Li Y, Kang C, Qu X, et al. Depression-related brain connectivity analyzed by EEG event-related phase synchrony measure [J]. Frontiers in Human Neuroscience, 2016, 10: 477. [59] Zotev V, Yuan H, Misaki M, et al. Correlation between amygdala BOLD activity and frontal EEG asymmetry during real-time fMRI neurofeedback training in patients with depression [J]. Neuroimage Clin, 2016, 11: 224-238. [60] Zotev V, Mayeli A, Misaki M, et al. Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback [J]. arXiv, 2019: 1909.05764. [61] Cai H, Wang Z, Zhang Y, et al. A virtual-reality based neurofeedback game framework for depression rehabilitation using pervasive three-electrode EEG collector[C]//Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing. Chongqing: Association for Computing Machinery, 2017: 173-176.