1932

Abstract

Impaired cognition is common in many neuropsychiatric disorders and severely compromises quality of life. Synchronous electrophysiological rhythms represent a core mechanism for sculpting communication dynamics among large-scale brain networks that underpin cognition and its breakdown in neuropsychiatric disorders. Here, we review an emerging neuromodulation technology called transcranial alternating current stimulation that has shown remarkable early results in rapidly improving various domains of human cognition by modulating properties of rhythmic network synchronization. Future noninvasive neuromodulation research holds promise for potentially rescuing network activity patterns and improving cognition, setting groundwork for the development of drug-free, circuit-based therapeutics for people with cognitive brain disorders.

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2021-01-27
2024-04-13
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Literature Cited

  1. 1. 
    Vaidya CJ, Stollstorff M. 2008. Cognitive neuroscience of attention deficit hyperactivity disorder: current status and working hypotheses. Dev. Disabil. Res. Rev. 14:4261–67
    [Google Scholar]
  2. 2. 
    Kalkstein S, Hurford I, Gur RC 2010. Neurocognition in schizophrenia. Curr. Top. Behav. Neurosci. 4:373–90
    [Google Scholar]
  3. 3. 
    Baron-Cohen S, Belmonte MK. 2005. Autism: a window onto the development of the social and the analytic brain. Annu. Rev. Neurosci. 28:109–26
    [Google Scholar]
  4. 4. 
    Burdick KE, Robinson DG, Malhotra AK et al. 2008. Neurocognitive profile analysis in obsessive-compulsive disorder. J. Int. Neuropsychol. Soc. 14:4640–45
    [Google Scholar]
  5. 5. 
    Marazziti D, Consoli G, Picchetti M et al. 2010. Cognitive impairment in major depression. Eur. J. Pharmacol. 626:183–86
    [Google Scholar]
  6. 6. 
    Kurtz MM, Gerraty RT. 2009. A meta-analytic investigation of neurocognitive deficits in bipolar illness: profile and effects of clinical state. Neuropsychology 23:5551–62
    [Google Scholar]
  7. 7. 
    Millan MJ. 2006. Multi-target strategies for the improved treatment of depressive states: conceptual foundations and neuronal substrates, drug discovery and therapeutic application. Pharmacol. Ther. 110:2135–370
    [Google Scholar]
  8. 8. 
    Millan MJ, Agid Y, Brüne M et al. 2012. Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy. Nat. Rev. Drug Discov. 11:2141–68
    [Google Scholar]
  9. 9. 
    Vosskuhl J, Strüber D, Herrmann CS 2018. Non-invasive brain stimulation: a paradigm shift in understanding brain oscillations. Front. Hum. Neurosci. 12:211
    [Google Scholar]
  10. 10. 
    Schutter DJLG, Wischnewski M. 2016. A meta-analytic study of exogenous oscillatory electric potentials in neuroenhancement. Neuropsychologia 86:110–18
    [Google Scholar]
  11. 11. 
    Buzsáki G. 2006. Rhythms of the Brain Oxford/New York: Oxford Univ. Press
  12. 12. 
    Siegel M, Donner TH, Engel AK 2012. Spectral fingerprints of large-scale neuronal interactions. Nat. Rev. Neurosci. 13:121–34
    [Google Scholar]
  13. 13. 
    Helfrich RF, Knight RT. 2016. Oscillatory dynamics of prefrontal cognitive control. Trends Cogn. Sci. 20:12916–30
    [Google Scholar]
  14. 14. 
    Fries P. 2015. Rhythms for cognition: communication through coherence. Neuron 88:1220–35
    [Google Scholar]
  15. 15. 
    Buzsáki G, Anastassiou CA, Koch C 2012. The origin of extracellular fields and currents—EEG, ECoG, LFP and spikes. Nat. Rev. Neurosci. 13:6407–20
    [Google Scholar]
  16. 16. 
    Cardin JA, Carlén M, Meletis K et al. 2009. Driving fast-spiking cells induces gamma rhythm and controls sensory responses. Nature 459:7247663–67
    [Google Scholar]
  17. 17. 
    Heusser AC, Poeppel D, Ezzyat Y et al. 2016. Episodic sequence memory is supported by a theta-gamma phase code. Nat. Neurosci. 19:101374–80
    [Google Scholar]
  18. 18. 
    Fell J, Axmacher N. 2011. The role of phase synchronization in memory processes. Nat. Rev. Neurosci. 12:2105–18
    [Google Scholar]
  19. 19. 
    Reinhart RMG, Nguyen JA. 2019. Working memory revived in older adults by synchronizing rhythmic brain circuits. Nat. Neurosci. 22:5820–27
    [Google Scholar]
  20. 20. 
    Daume J, Gruber T, Engel AK et al. 2017. Phase-amplitude coupling and long-range phase synchronization reveal frontotemporal interactions during visual working memory. J. Neurosci. 37:2313–22
    [Google Scholar]
  21. 21. 
    Cohen MX, Axmacher N, Lenartz D et al. 2009. Good vibrations: cross-frequency coupling in the human nucleus accumbens during reward processing. J. Cogn. Neurosci. 21:5875–89
    [Google Scholar]
  22. 22. 
    Cohen MX, Elger CE, Fell J 2009. Oscillatory activity and phase-amplitude coupling in the human medial frontal cortex during decision making. J. Cogn. Neurosci. 21:2390–402
    [Google Scholar]
  23. 23. 
    Voytek B, Kayser AS, Badre D et al. 2015. Oscillatory dynamics coordinating human frontal networks in support of goal maintenance. Nat. Neurosci. 18:91318–24
    [Google Scholar]
  24. 24. 
    Reinhart RMG, Woodman GF. 2014. Oscillatory coupling reveals the dynamic reorganization of large-scale neural networks as cognitive demands change. J. Cogn. Neurosci. 26:1175–88
    [Google Scholar]
  25. 25. 
    Szczepanski SM, Crone NE, Kuperman RA et al. 2014. Dynamic changes in phase-amplitude coupling facilitate spatial attention control in fronto-parietal cortex. PLOS Biol 12:8e1001936
    [Google Scholar]
  26. 26. 
    Watrous AJ, Tandon N, Conner CR et al. 2013. Frequency-specific network connectivity increases underlie accurate spatiotemporal memory retrieval. Nat. Neurosci. 16:3349–56
    [Google Scholar]
  27. 27. 
    Polanía R, Nitsche MA, Korman C et al. 2012. The importance of timing in segregated theta phase-coupling for cognitive performance. Curr. Biol. 14:1314–18
    [Google Scholar]
  28. 28. 
    Reinhart RMG. 2017. Disruption and rescue of interareal theta phase coupling and adaptive behavior. PNAS 114:4311542–47
    [Google Scholar]
  29. 29. 
    Palva JM, Monto S, Kulashekhar S et al. 2010. Neuronal synchrony reveals working memory networks and predicts individual memory capacity. PNAS 107:7580–85
    [Google Scholar]
  30. 30. 
    Saalmann YB, Pinsk MA, Wang L et al. 2012. The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337:6095753–56
    [Google Scholar]
  31. 31. 
    Salazar RF, Dotson NM, Bressler SL et al. 2012. Content-specific fronto-parietal synchronization during visual working memory. Science 338:1097–100
    [Google Scholar]
  32. 32. 
    von Nicolai C, Engler G, Sharott A et al. 2014. Corticostriatal coordination through coherent phase-amplitude coupling. J. Neurosci. 34:175938–48
    [Google Scholar]
  33. 33. 
    Bullmore E, Sporns O. 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10:3186–98
    [Google Scholar]
  34. 34. 
    Buzsáki G, Draguhn A. 2004. Neuronal oscillations in cortical networks. Science 304:56791926–29
    [Google Scholar]
  35. 35. 
    Uhlhaas PJ, Singer W. 2015. Oscillations and neuronal dynamics in schizophrenia: the search for basic symptoms and translational opportunities. Biol. Psychiatry 77:121001–9
    [Google Scholar]
  36. 36. 
    Voytek B, Knight RT. 2015. Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease. Biol. Psychiatry 77:121089–97
    [Google Scholar]
  37. 37. 
    Başar E. 2013. Brain oscillations in neuropsychiatric disease. Dialogues Clin. Neurosci. 15:3291–300
    [Google Scholar]
  38. 38. 
    Mathalon DH, Sohal VS. 2015. Neural oscillations and synchrony in brain dysfunction and neuropsychiatric disorders: It's about time. JAMA Psychiatry 72:8840–44
    [Google Scholar]
  39. 39. 
    Uhlhaas PJ, Singer W. 2006. Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology. Neuron 52:1155–68
    [Google Scholar]
  40. 40. 
    Uhlhaas PJ, Singer W. 2012. Neuronal dynamics and neuropsychiatric disorders: toward a translational paradigm for dysfunctional large-scale networks. Neuron 75:6963–80
    [Google Scholar]
  41. 41. 
    Uhlhaas PJ. 2015. Neural dynamics in mental disorders. World Psychiatry 14:2116–18
    [Google Scholar]
  42. 42. 
    Brennan AM, Williams LM, Harris AWF 2018. Intrinsic, task-evoked and absolute gamma synchrony during cognitive processing in first onset schizophrenia. J. Psychiatr. Res. 99:10–21
    [Google Scholar]
  43. 43. 
    Cea-Cañas B, Gomez-Pilar J, Núñez P et al. 2020. Connectivity strength of the EEG functional network in schizophrenia and bipolar disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry 98:109801
    [Google Scholar]
  44. 44. 
    Sharma A, Weisbrod M, Kaiser S et al. 2011. Deficits in fronto-posterior interactions point to inefficient resource allocation in schizophrenia. Acta Psychiatr. Scand. 123:2125–35
    [Google Scholar]
  45. 45. 
    Griesmayr B, Berger B, Stelzig-Schoeler R et al. 2014. EEG theta phase coupling during executive control of visual working memory investigated in individuals with schizophrenia and in healthy controls. Cogn. Affect. Behav. Neurosci. 14:41340–55
    [Google Scholar]
  46. 46. 
    Popov T, Wienbruch C, Meissner S et al. 2015. A mechanism of deficient interregional neural communication in schizophrenia. Psychophysiology 52:5648–56
    [Google Scholar]
  47. 47. 
    Reinhart RMG, Zhu J, Park S et al. 2015. Synchronizing theta oscillations with direct-current stimulation strengthens adaptive control in the human brain. PNAS 112:309448–53
    [Google Scholar]
  48. 48. 
    Barr MS, Rajji TK, Zomorrodi R et al. 2017. Impaired theta-gamma coupling during working memory performance in schizophrenia. Schizophr. Res. 189:104–10
    [Google Scholar]
  49. 49. 
    Bassett DS, Bullmore ET, Meyer-Lindenberg A et al. 2009. Cognitive fitness of cost-efficient brain functional networks. PNAS 106:2811747–52
    [Google Scholar]
  50. 50. 
    Michelini G, Jurgiel J, Bakolis I et al. 2019. Atypical functional connectivity in adolescents and adults with persistent and remitted ADHD during a cognitive control task. Transl. Psychiatry 9:1137
    [Google Scholar]
  51. 51. 
    Urbain C, Vogan VM, Ye AX et al. 2016. Desynchronization of fronto-temporal networks during working memory processing in autism. Hum. Brain Mapp. 37:1153–64
    [Google Scholar]
  52. 52. 
    Wiesman AI, Heinrichs-Graham E, McDermott TJ et al. 2016. Quiet connections: reduced fronto-temporal connectivity in nondemented Parkinson's disease during working memory encoding. Hum. Brain Mapp. 37:93224–35
    [Google Scholar]
  53. 53. 
    Pinal D, Zurrón M, Díaz F et al. 2015. Stuck in default mode: inefficient cross-frequency synchronization may lead to age-related short-term memory decline. Neurobiol. Aging 36:41611–18
    [Google Scholar]
  54. 54. 
    Goodman MS, Kumar S, Zomorrodi R et al. 2018. Theta-gamma coupling and working memory in Alzheimer's dementia and mild cognitive impairment. Front. Aging Neurosci. 10:101
    [Google Scholar]
  55. 55. 
    Salvadore G, Cornwell BR, Sambataro F et al. 2010. Anterior cingulate desynchronization and functional connectivity with the amygdala during a working memory task predict rapid antidepressant response to ketamine. Neuropsychopharmacology 35:71415–22
    [Google Scholar]
  56. 56. 
    Khan S, Gramfort A, Shetty NR et al. 2013. Local and long-range functional connectivity is reduced in concert in autism spectrum disorders. PNAS 110:83107–12
    [Google Scholar]
  57. 57. 
    Jaime M, McMahon CM, Davidson BC et al. 2016. Brief report: reduced temporal-central EEG alpha coherence during joint attention perception in adolescents with autism spectrum disorder. J. Autism Dev. Disord. 46:41477–89
    [Google Scholar]
  58. 58. 
    Bestmann S, Walsh V. 2017. Transcranial electrical stimulation. Curr. Biol. 27:23R1258–62
    [Google Scholar]
  59. 59. 
    Schutter DJLG. 2014. Syncing your brain: electric currents to enhance cognition. Trends Cogn. Sci. 18:7331–33
    [Google Scholar]
  60. 60. 
    Miniussi C, Harris JA, Ruzzoli M 2013. Modelling non-invasive brain stimulation in cognitive neuroscience. Neurosci. Biobehav. Rev. 37:81702–12
    [Google Scholar]
  61. 61. 
    Krause MR, Vieira PG, Csorba BA et al. 2019. Transcranial alternating current stimulation entrains single-neuron activity in the primate brain. PNAS 116:125747–55
    [Google Scholar]
  62. 62. 
    Helfrich RF, Schneider TR, Rach S et al. 2014. Entrainment of brain oscillations by transcranial alternating current stimulation. Curr. Biol. 24:3333–39
    [Google Scholar]
  63. 63. 
    Antal A, Alekseichuk I, Bikson M et al. 2017. Low intensity transcranial electric stimulation: safety, ethical, legal regulatory and application guidelines. Clin. Neurophysiol. 128:91774–809
    [Google Scholar]
  64. 64. 
    Grover S, Nguyen JA, Viswanathan V et al. 2020. High-frequency neuromodulation improves obsessive-compulsive behavior. Nat. Med. In press
    [Google Scholar]
  65. 65. 
    Alekseichuk I, Turi Z, Amador de Lara G et al. 2016. Spatial working memory in humans depends on theta and high gamma synchronization in the prefrontal cortex. Curr. Biol. 26:121513–21
    [Google Scholar]
  66. 66. 
    Alexander ML, Alagapan S, Lugo CE et al. 2019. Double-blind, randomized pilot clinical trial targeting alpha oscillations with transcranial alternating current stimulation (tACS) for the treatment of major depressive disorder (MDD). Transl. Psychiatry 9:1106
    [Google Scholar]
  67. 67. 
    Borghini G, Candini M, Filannino C et al. 2018. Alpha oscillations are causally linked to inhibitory abilities in ageing. J. Neurosci. 38:184418–29
    [Google Scholar]
  68. 68. 
    Tseng P, Chang Y-T, Chang C-F et al. 2016. The critical role of phase difference in gamma oscillation within the temporoparietal network for binding visual working memory. Sci. Rep. 6:32138
    [Google Scholar]
  69. 69. 
    Zaehle T, Rach S, Herrmann CS 2010. Transcranial alternating current stimulation enhances individual alpha activity in human EEG. PLOS ONE 5:11e13766
    [Google Scholar]
  70. 70. 
    Vossen A, Gross J, Thut G 2015. Alpha power increase after transcranial alternating current stimulation at alpha frequency (α-tACS) reflects plastic changes rather than entrainment. Brain Stimul 8:3499–508
    [Google Scholar]
  71. 71. 
    Goto Y, Yang CR, Otani S 2010. Functional and dysfunctional synaptic plasticity in prefrontal cortex: roles in psychiatric disorders. Biol. Psychiatry 67:3199–207
    [Google Scholar]
  72. 72. 
    Reato D, Rahman A, Bikson M et al. 2010. Low-intensity electrical stimulation affects network dynamics by modulating population rate and spike timing. J. Neurosci. 30:4515067–79
    [Google Scholar]
  73. 73. 
    Ozen S, Sirota A, Belluscio MA et al. 2010. Transcranial electric stimulation entrains cortical neuronal populations in rats. J. Neurosci. 30:3411476–85
    [Google Scholar]
  74. 74. 
    Opitz A, Falchier A, Yan C-G et al. 2016. Spatiotemporal structure of intracranial electric fields induced by transcranial electric stimulation in humans and nonhuman primates. Sci. Rep. 6:31236
    [Google Scholar]
  75. 75. 
    Kar K, Duijnhouwer J, Krekelberg B 2017. Transcranial alternating current stimulation attenuates neuronal adaptation. J. Neurosci. 37:92325–35
    [Google Scholar]
  76. 76. 
    Huang Y, Liu AA, Lafon B et al. 2018. Correction: Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation. eLife 7:e35178
    [Google Scholar]
  77. 77. 
    Vöröslakos M, Takeuchi Y, Brinyiczki K et al. 2018. Direct effects of transcranial electric stimulation on brain circuits in rats and humans. Nat. Commun. 9:1483
    [Google Scholar]
  78. 78. 
    Kasten FH, Duecker K, Maack MC et al. 2019. Integrating electric field modeling and neuroimaging to explain inter-individual variability of tACS effects. Nat. Commun. 10:15427
    [Google Scholar]
  79. 79. 
    Alagapan S, Schmidt SL, Lefebvre J et al. 2016. Modulation of cortical oscillations by low-frequency direct cortical stimulation is state-dependent. PLOS Biol 14:3e1002424
    [Google Scholar]
  80. 80. 
    Nguyen J, Deng Y, Reinhart RMG 2018. Brain-state determines learning improvements after transcranial alternating-current stimulation to frontal cortex. Brain Stimul 11:4723–26
    [Google Scholar]
  81. 81. 
    Schwab BC, Misselhorn J, Engel AK 2019. Modulation of large-scale cortical coupling by transcranial alternating current stimulation. Brain Stimul 12:51187–96
    [Google Scholar]
  82. 82. 
    Helfrich RF, Knepper H, Nolte G et al. 2014. Selective modulation of interhemispheric functional connectivity by HD-tACS shapes perception. PLOS Biol 12:12e1002031
    [Google Scholar]
  83. 83. 
    Violante IR, Li LM, Carmichael DW et al. 2017. Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance. eLife 6:e22001
    [Google Scholar]
  84. 84. 
    Polanía R, Moisa M, Opitz A et al. 2015. The precision of value-based choices depends causally on fronto-parietal phase coupling. Nat. Commun. 6:8090
    [Google Scholar]
  85. 85. 
    Tseng P, Iu K-C, Juan C-H 2018. The critical role of phase difference in theta oscillation between bilateral parietal cortices for visuospatial working memory. Sci. Rep. 8:1349
    [Google Scholar]
  86. 86. 
    Cavanagh JF, Frank MJ. 2014. Frontal theta as a mechanism for cognitive control. Trends Cogn. Sci. 18:8414–21
    [Google Scholar]
  87. 87. 
    Yaple Z, Vakhrushev R. 2018. Modulation of the frontal-parietal network by low intensity anti-phase 20 Hz transcranial electrical stimulation boosts performance in the attentional blink task. Int. J. Psychophysiol. 127:11–16
    [Google Scholar]
  88. 88. 
    Hsu W-Y, Zanto TP, van Schouwenburg MR et al. 2017. Enhancement of multitasking performance and neural oscillations by transcranial alternating current stimulation. PLOS ONE 12:5e0178579
    [Google Scholar]
  89. 89. 
    Hsu W-Y, Zanto TP, Gazzaley A 2019. Parametric effects of transcranial alternating current stimulation on multitasking performance. Brain Stimul 12:173–83
    [Google Scholar]
  90. 90. 
    Lustenberger C, Boyle MR, Foulser AA et al. 2015. Functional role of frontal alpha oscillations in creativity. Cortex 67:74–82
    [Google Scholar]
  91. 91. 
    Mellin JM, Alagapan S, Lustenberger C et al. 2018. Randomized trial of transcranial alternating current stimulation for treatment of auditory hallucinations in schizophrenia. Eur. Psychiatry 51:25–33
    [Google Scholar]
  92. 92. 
    Klimke A, Nitsche MA, Maurer K et al. 2016. Case report: successful treatment of therapy-resistant OCD with application of transcranial alternating current stimulation (tACS). Brain Stimul 9:3463–65
    [Google Scholar]
  93. 93. 
    Neuling T, Ruhnau P, Fuscà M et al. 2015. Friends, not foes: magnetoencephalography as a tool to uncover brain dynamics during transcranial alternating current stimulation. Neuroimage 118:406–13
    [Google Scholar]
  94. 94. 
    Noury N, Siegel M. 2018. Analyzing EEG and MEG signals recorded during tES, a reply. NeuroImage 167:53–61
    [Google Scholar]
  95. 95. 
    Ketz N, Jones AP, Bryant NB et al. 2018. Closed-loop slow-wave tACS improves sleep-dependent long-term memory generalization by modulating endogenous oscillations. J. Neurosci. 38:337314–26
    [Google Scholar]
  96. 96. 
    Alekseichuk I, Falchier AY, Linn G et al. 2019. Electric field dynamics in the brain during multi-electrode transcranial electric stimulation. Nat. Commun. 10:12573
    [Google Scholar]
  97. 97. 
    Saturnino GB, Madsen KH, Siebner HR et al. 2017. How to target inter-regional phase synchronization with dual-site transcranial alternating current stimulation. Neuroimage 163:68–80
    [Google Scholar]
  98. 98. 
    Avena-Koenigsberger A, Misic B, Sporns O 2017. Communication dynamics in complex brain networks. Nat. Rev. Neurosci. 19:117–33
    [Google Scholar]
  99. 99. 
    Grossman N, Bono D, Dedic N et al. 2017. Noninvasive deep brain stimulation via temporally interfering electric fields. Cell 169:61029–41.e16
    [Google Scholar]
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