Age-related features of alpha rhythm dynamics: a brief review

In this mini-review, the age-related features of alpha rhythm dynamics, its generation sources, and its connection to cognitive functions are discussed. The review focuses on a brief systematization of data regarding the alpha rhythm of human brain bioelectrical activity and its informativeness in determining the biological age of the human brain. The alpha rhythm is characterized by high individual stability and exhibits pronounced age-related dynamics in its U-shape. The peak frequency of the alpha rhythm increases from infancy to young adulthood and then decreases during brain aging. Discussions about the sources of alpha rhythm generation are still ongoing. Current data show a lack of a clear connection between the peak frequency of alpha rhythm and human cognitive abilities and intelligence. Parameters of the alpha rhythm, such as individual stability, genetic predisposition, and age-related characteristics, make it a promising marker for both normative development and brain aging in determining cognitive and biological age.

1. Antipanova N.A., Sataeva A.M., Zhumabaeva G.T. Gendernyj podhod v razvitii rechi mal'chikov i devochek [Gender approach in the development of speech of boys and girls]. Mezhdunarodnyj zhurnal gumanitarnyh i estestvennyh nauk = International Journal of Humanities and Natural Sciences, No. 3, pp. 52–55. (In Russ.)
2. Veraksa A.N., Kurilenko V.B., Novikova I.A. Fenomenologija detstva v sovremennyh kontekstah [Phenomenology of childhood in modern contexts]. Vestnik Rossijskogo universiteta druzhby narodov. Serija: Psihologija i pedagogika = RUDN Journal of Psychology and Pedagogics, Vol. 20, no. 3, pp. 419–430. DOI: 10.22363/2313-1683-2023-20-3-419-430 (In Russ., abstr. in Engl.)
3. Novikova L.A. Vlijanie narushenij zrenija i sluha na funkcional'noe sostojanie mozga [Influence of visual and hearing impairments on the functional state of the brain]. Moscow: Prosveshhenie, 1966. 319 p. (In Russ.)
4. Polikanova I. S., Balan P. V., Martynova O. V. Kognitivnyj i biologicheskij vozrast cheloveka: aktual'nye voprosy i novye perspektivy v issledovanii starenija [Cognitive and biological age of a person: current issues and new perspectives in the study of aging]. Teoreticheskaja i eksperimental'naja psihologija = Theoretical and Experimental Psychology, Vol. 5(4), pp. 106–120. DOI: 10.24412/2073-0861-2022-4-106-120 (In Russ., abstr. in Engl.)
5. Sazonova E.A., Bykov E.V. Vlijanie elektromagnitnogo izluchenija nizkoj intensivnosti na bioelektricheskuju aktivnost' golovnogo mozga studentov-sportsmenov [Influence of electromagnetic radiation of low intensity on the bioelectrical activity of the brain of student-athletes]. Nauchno-sportivnyj vestnik Urala i Sibiri = Scientific and Sports Bulletin of the Urals and Siberia, No. 4, pp. 32–39. (In Russ.)
6. Jakshina A.N. Raznovozrastnye gruppy v detskom sadu: vozmozhnosti i riski dlja razvitija doshkol'nikov [Different-age groups in kindergarten: opportunities and risks for the development of preschoolers]. Sovremennoe doshkol'noe obrazovanie = Modern preschool education, Vol. 109, no. 1, pp. 4–14. DOI: 10.24412/1997-9657-2022-1109-4-14 (In Russ., abstr. in Engl.)
7. Abubaker M., Al Qasem W., Kvašňák E. Working memory and cross-frequency coupling of neuronal oscillations. Frontiers in Psychology, 2021. Vol. 12, pp. 756661. DOI: 3389/fpsyg.2021.756661
8. Adrian E.D., Matthews B.H.C. The Berger rhythm: potential changes from the occipital lobes in man. Brain, 1934. Vol. 57(4), pp. 355–385. DOI: 1093/brain/57.4.355
9. Angelakis E., Lubar J.F., Stathopoulou S., Kounios J. Peak alpha frequency: an electroencephalographic measure of cognitive preparedness. Clinical Neurophysiology, 2004. Vol. 115 (4), pp. 887–897. DOI: 1016/j.clinph.2003.11.034
10. Anokhin A.P. Genetic psychophysiology: Advances, problems, and future directions. International Journal of Psychophysiology, 2014. Vol. 93 (2), pp. 173–197. DOI: 1016/j.ijpsycho.2014.04.003
11. Anokhin A., Vogel F. EEG alpha rhythm frequency and intelligence in normal adults. Intelligence, 1996. Vol. 23 (1), pp. 1–14. DOI: 1016/S0160-2896(96)80002-X
12. Barry R.J., Clarke A.R., McCarthy R. et al. Age and gender effects in EEG coherence: I. Developmental trends in normal children. Clinical neurophysiology, 2004. Vol. 115 (10), pp. 2252–2258. DOI: 1016/j.clinph.2004.05.004
13. Barzegaran E., Vildavski V.Y., Knyazeva M.G. Fine structure of posterior alpha rhythm in human EEG: Frequency components, their cortical sources, and temporal behavior. Scientific Reports, 2017. Vol. 7 (1), pp. 1–12. DOI: 1038/s41598-017-08421-z
14. Benninger C., Matthis, P., Scheffner D. EEG development of healthy boys and girls. Results of a longitudinal study. Electroencephalography and clinical neurophysiology, 1984. Vol. 57 (1), pp. 1–12. DOI: 1016/0013-4694(84)90002-6
15. Berger H. Uber das Elektroenkephalogramm des Menschen. Archiv fur Psychiatrie und Nervenkrankheiten, 1929. Vol. 87, pp. 527–570. DOI: 1007/BF01797193
16. Bertaccini R., Ellena G., Macedo-Pascual J. et al. Parietal alpha oscillatory peak frequency mediates the effect of practice on visuospatial working memory performance. Vision, 2022. Vol. 6 (2), pp. 30. DOI: 3390/vision6020030
17. Bobby J.S. Peak alpha neurofeedback training on cognitive performance in elderly subjects. International Journal of Medical Engineering and Informatics, 2020. Vol. 12 (3), pp. 237–247. DOI: 1504/IJMEI.2020.107093
18. Buzsaki G. Rhythms of the Brain. New York: Oxford University Press, 2006. 464 p. DOI: 1093/acprof:oso/9780195301069.001.0001
19. Cellier D., Riddle J., Petersen I., Hwang K. The development of theta and alpha neural oscillations from ages 3 to 24 years. Developmental cognitive neuroscience, 2021. Vol. 50, p. 100969. DOI:1016/j.dcn.2021.100969
20. Chiang A.K.I., Rennie C.J., Robinson P.A. et al. Age trends and sex differences of alpha rhythms including split alpha peaks. Clinical Neurophysiology, 2011. Vol. 122 (8), pp. 1505–1517. DOI: 1016/j.clinph.2011.01.040
21. Clarke A.R., Barry R.J., McCarthy R., Selikowitz M. Age and sex effects in the EEG: development of the normal child. Clinical Neurophysiology, 2011. Vol. 112 (5), pp. 806–814. DOI: 1016/S1388-2457(01)00488-6
22. Cuevas K., Bell M.A. EEG frequency development across infancy and childhood. In: P.A. Gable, M.W. Miller, E.M. Bernat (Eds). The Oxford Handbook of EEG Frequency, Oxford Library of Psychology. 2022. Pp. 293–323. DOI: 1093/oxfordhb/9780192898340.013.13
23. D’Souza R.D., Wang Q., Ji W. et al. Hierarchical and nonhierarchical features of the mouse visual cortical network. Nature Communications, 2022. Vol. 13 (1), pp. 503. DOI: 1038/s41467-022-28035-y
24. Da Silva F.H.L., Van Leeuwen W.S. The cortical source of the alpha rhythm. Neuroscience Letters, 1977. Vol. 6 (2-3), pp. 237–241. DOI: 1016/0304-3940(77)90024-6
25. de Munck J.C., Gonçalves S.I., Huijboom L. et al. The hemodynamic response of the alpha rhythm: an EEG/fMRI study. Neuroimage, 2007. Vol. 35 (3), pp. 1142–1151. DOI: 1016/j.neuroimage.2007.01.022
26. ElShafei H.A., Orlemann C., Haegens S. The impact of eye closure on anticipatory α activity in a tactile discrimination task. eNeuro, 2022. Vol. 9 (1). DOI: 1523/ENEURO.0412-21.2021
27. Engemann D.A., Mellot A., Höchenberger R. et al. A reusable benchmark of brain-age prediction from M/EEG resting-state signals. Neuroimage, 2022. Vol. 262, p. 119521. DOI: 1016/j.neuroimage.2022.119521
28. Freschl J., Al Azizi L., Balboa L. et al. The development of peak alpha frequency from infancy to adolescence and its role in visual temporal processing: A meta-analysis. Developmental Cognitive Neuroscience, 2022. Vol. 57, pp. 101146. DOI: 1016/j.dcn.2022.101146
29. Goetz P., Hu D., To P.D. et al. Scalp EEG markers of normal infant development using visual and computational approaches. 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2021. Pp. 6528–6532. DOI: 1109/EMBC46164.2021.9629909
30. Goljahan A., D’Avanzo C., Schiff S. et al. A novel method for the determination of the EEG individual alpha frequency. Neuroimage, 2012. Vol. 60, pp. 774–786. DOI: 1016/j.neuroimage.2011.12.001
31. Gonçalves S.I., de Munck J.C., Pouwels P.J. et al. Correlating the alpha rhythm to BOLD using simultaneous EEG/fMRI: inter-subject variability. Neuroimage, 2006. Vol. 30 (1), pp. 203–213. DOI: 1016/j.neuroimage.2005.09.062
32. Grandy T.H., Werkle‐Bergner M., Chicherio C. et al. Peak individual alpha frequency qualifies as a stable neurophysiological trait marker in healthy younger and older adults. Psychophysiology, 2013. Vol. 50 (6), pp. 570–582. DOI: 1111/psyp.12043
33. Gratton G., Villa A.E., Fabiani M. et al. Functional correlates of a three-component spatial model of the alpha rhythm. Brain Research, 1992. Vol. 582 (1), pp. 159–162. DOI: 1016/0006-8993(92)90332-4
34. Haegens S., Händel B.F., Jensen O. Top-down controlled alpha band activity in somatosensory areas determines behavioral performance in a discrimination task. The Journal of Neuroscience, 2011. Vol. 31 (14), pp. 5197–5204. DOI: 1523/JNEUROSCI.5199-10.2011
35. Halgren M., Ulbert I., Bastuji H. et al. The generation and propagation of the human alpha rhythm. Proceedings of the National Academy of Sciences of the United States of America, 2019. Vol. 116 (47), pp. 23772–23782. DOI: 1073/pnas.1913092116
36. Hinault T., Baillet S., Courtney S.M. Age-related changes of deep-brain neurophysiological activity. Cerebral Cortex, 2023. Vol. 33 (7), pp. 3960–3968. DOI: 1093/cercor/bhac319
37. Hughes S.W., Crunelli V. Thalamic mechanisms of EEG alpha rhythms and their pathological implications. Neuroscientist, 2005. Vol. 11 (4), pp. 357–372. DOI: 1177/1073858405277450
38. Iacono W.G., Malone S.M., Vrieze S.I. Endophenotype best practices. International Journal of Psychophysiology, 2017. Vol. 111, pp. 115–144. DOI: 1016/j.ijpsycho.2016.07.516
39. Inamoto T., Ueda M., Ueno K. et al. Motor-related mu/beta rhythm in older adults: a comprehensive review. Brain Sciences, 2023. Vol. 13 (5), pp. 751. DOI: 3390/brainsci13050751
40. Klimesch W. Alpha-band oscillations, attention, and controlled access to stored information. Trends in Cognitive Sciences, 2012. Vol. 16 (12), pp. 606–617. DOI: 1016/j.tics.2012.10.007
41. Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research. Brain Research Reviews, 1999. Vol. 29 (2-3), pp. 169–95. DOI: 1016/S0165-0173(98)00056-3
42. Klimesch W. EEG-alpha rhythms and memory processes. International Journal of Psychophysiology, 1997. Vol. 26 (1-3), pp. 319–330. DOI: 1016/S0167-8760(97)00773-3
43. Klimesch W., Doppelmayr M., Pachinger T., Russegger H. Event-related desynchronization in the alpha band and the processing of semantic information. Cognitive Brain Research, 1997. Vol. 6 (2), pp. 83–94. DOI: 1016/S0926-6410(97)00018-9
44. Klimesch W., Schimke H., Pfurtscheller G. Alpha frequency, cognitive load and memory performance. Brain Topography, 1993. Vol. 5 (3), pp. 241–251. DOI: 1007/BF01128991
45. Klimesch W., Doppelmayr M., Schimke H., Pachinger T. Alpha frequency, reaction time, and the speed of processing information. Journal of Clinical Neurophysiology, 1996. Vol. 13 (6), pp. 511–518. DOI: 1097/00004691-199611000-00006
46. Knyazeva M.G., Barzegaran E., Vildavski V.Y., Demonet J.F. Aging of human alpha rhythm. Neurobiology of Aging, 2018. Vol. 69, pp. 261–273. DOI: 1016/j.neurobiolaging.2018.05.018
47. Kondacs A., Szabó M. Long-term intra-individual variability of the background EEG in normal. Clinical Neurophysiology, 1999. Vol. 110 (10), pp. 1708–1716. DOI: 1016/S1388-2457(99)00122-4
48. Kriegseis A., Hennighausen E., Rösler F., Röder B. Reduced EEG alpha activity over parieto-occipital brain areas in congenitally blind adults. Clinical Neurophysiology, 2006. Vol. 117 (7), pp. 1560–1573. DOI: 1016/j.clinph.2006.03.030
49. Kumral D., Cesnaite E., Beyer F. et al. Relationship between regional white matter hyperintensities and alpha oscillations in older adults. Neurobiology of Aging, 2022. Vol. 112, pp. 1–11. DOI: 1016/j.neurobiolaging.2021.10.006
50. Laufs H., Holt J.L., Elfont R. et al. Where the BOLD signal goes when alpha EEG leaves. Neuroimage, 2006. Vol. 31 (4), pp. 1408–1418. DOI: 1016/j.neuroimage.2006.02.002
51. Leonardsen E.H., Vidal-Piñeiro D., Roe J.M. et al. Genetic architecture of brain age and its causal relations with brain and mental disorders. Molecular Psychiatry, 2023. Vol. 28 (7), pp. 3111–3120. DOI: 10.1038/s41380-023-02087-y
52. Leybina A.V., Kashapov M.M. Understanding kindness in the Russian Context. Psychology in Russia: State of the Art, 2022. Vol. 15 (1), pp. 66–82. DOI: 10.11621/pir.2022.0105
53. Manor R., Cheaha D., Kumarnsit E., Samerphob N. Age-related Deterioration of Alpha Power in Cortical Areas Slowing Motor Command Formation in Healthy Elderly Subjects. In Vivo, 2023. Vol. 37 (2), pp. 679–684. DOI: 21873/invivo.13128
54. Markov N.T., Vezoli J., Chameau P. et al. Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex. The Journal of Comparative Neurology, 2014. Vol. 522 (1), pp. 225–259. DOI: 10.1002/cne.23458
55. Markovic A., Kaess M., Tarokh L. Gender differences in adolescent sleep neurophysiology: a high-density sleep EEG study. Scientific Reports, 2020. Vol. 10 (1), pp. 15935. DOI: 1038/s41598-020-72802-0
56. Marosi E., Harmony T., Becker J. et al. Sex differences in EEG coherence in normal children. International Journal of Neuroscience, 1993. Vol. 72 (1-2), pp. 115–121. DOI: 3109/00207459308991628
57. Marshall P.J., Bar-Haim Y., FoхA. Development of the EEG from 5 months to 4 years of age. Clinical Neurophysiology, 2002. Vol. 113 (8), pp. 1199–1208. DOI: 10.1016/S1388-2457(02)00163-3
58. Martinović Z., Jovanović V., Ristanović D. EEG power spectra of normal preadolescent twins. Gender differences of quantitative EEG maturation. Neurophysiologie Clinique / Clinical Neurophysiology, 1998. 28 (3), pp. 231–248. DOI: 10.1016/S0987-7053(98)80114-7
59. Mathewson K.E., Lleras A., Beck D.M. et al. Pulsed out of awareness: EEG alpha oscillations represent a pulsed-inhibition of ongoing cortical processing. Frontiers in Psychology, 2011. Vol. 2, pp. 99. DOI: 3389/fpsyg.2011.00099
60. Mejias J.F., Murray J.D., Kennedy H., Wang X.J. Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex. Science Advances, 2016. Vol. 2 (11), art. e1601335. DOI: 1126/sciadv.1601335
61. Modarres M., Cochran D., Kennedy D.N., Frazier J.A. Comparison of comprehensive quantitative EEG metrics between typically developing boys and girls in resting state eyes-open and eyes-closed conditions. Frontiers in Human Neuroscience, 2023. Vol. 17, p. 1237651. DOI: 3389/fnhum.2023.1237651
62. Morosanova V.I., Fomina T.G., Bondarenko I.N. Conscious Self-Regulation as a Meta-Resource of Academic Achievement and Psychological Well-Being of Young Adolescents. Psychology in Russia: State of the Art, 2023 Vol. 16 (3), pp. 168–188. DOI:11621/pir.2023.0312
63. Morrow A., Elias M., Samaha J. Evaluating the evidence for the functional inhibition account of alpha-band oscillations during preparatory attention. Journal of Cognitive Neuroscience, 2023. Vol. 35 (8), pp. 1195–1211. DOI: 1162/jocn_a_02009
64. Ociepka M., Kałamała P., Chuderski A. High individual alpha frequency brains run fast, but it does not make them smart. Intelligence, 2022. Vol. 92, p. 101644. DOI: 1016/j.intell.2022.101644
65. Pahor A., Jaušovec N. Making brains run faster: are they becoming smarter? The Spanish Journal of Psychology, 2016. Vol. 19. Art. E88. DOI: 1017/sjp.2016.83
66. Ponomareva N.V., Andreeva T.V., Protasova M. et al. Genetic association of apolipoprotein E genotype with EEG alpha rhythm slowing and functional brain network alterations during normal aging. Frontiers in Neuroscience, 2022. Vol. 16. Art. 931173. DOI: 3389/fnins.2022.931173
67. Portnova G.V., Atanov M.S. Age-dependent changes of the EEG data: comparative study of correlation dimension D2, spectral analysis, peak alpha frequency and stability of rhythms. International Journal of Innovative Research in Computer Science & Technology (IJIRCST), 2016. Vol. 4 (2), pp. 56–61.
68. Posthuma D., Neale M.C., Boomsma D.I., De Geus E.J.C. Are smarter brains running faster? Heritability of alpha peak frequency, IQ, and their interrelation. Behavior Genetics, 2001. Vol. 31, pp. 567–579. DOI: 1023/A:1013345411774
69. Radecke J.O., Fiene M., Misselhorn J. et al. Personalized alpha-tACS targeting left posterior parietal cortex modulates visuo-spatial attention and posterior evoked EEG activity. Brain Stimulation, 2023. Vol. 16 (4), pp. 1047–1061. DOI: 1016/j.brs.2023.06.013
70. Rempel S., Colzato L., Zhang W. et al. Distinguishing multiple coding levels in theta band activity during working memory gating processes. Neuroscience, 2021. Vol. 478, pp. 11–23. DOI: 1016/j.neuroscience.2021.09.025
71. Roux F., Uhlhaas P.J. Working memory and neural oscillations: alpha–gamma versus theta–gamma codes for distinct WM information? Trends in Cognitive Sciences, 2014. Vol. 18 (1), pp. 16–25. DOI: 1016/j.tics.2013.10.010
72. Saalmann Y.B., Pinsk M.A., Wang L. et al. The pulvinar regulates information transmission between cortical areas based on attention demands. Science, 2012. Vol. 337(6095), pp. 753–756. DOI: 1126/science.1223082
73. Schneider D., Herbst S.K., Klatt L.I., Wöstmann M. Target enhancement or distractor suppression? Functionally distinct alpha oscillations form the basis of attention. The European Journal of Neuroscience, 2022. Vol. 55 (11-12), pp. 3256–3265. DOI: 1111/ejn.15309
74. Schubert J.T., Buchholz V.N., Föcker J. et al. Oscillatory activity reflects differential use of spatial reference frames by sighted and blind individuals in tactile attention. NeuroImage, 2015. Vol. 117, pp. 417–428. DOI: 10.1016/j.neuroimage.2015.05.068
75. Senzai Y., Fernandez-Ruiz A., Buzsáki G. Layer-specific physiological features and interlaminar interactions in the primary visual cortex of the mouse. Neuron, 2019. Vol. 101 (3), pp. 500–513. Art. e5. DOI: 1016/j.neuron.2018.12.009
76. Shaw J.C. The brain’s alpha rhythms and the mind. Amsterdam; Boston: Elsevier, 2003. 337 p.
77. Shen G., Green H.L., Franzen R.E. et al. Resting-state activity in children: Replicating and extending findings of early maturation of alpha rhythms in autism spectrum disorder. Journal of Autism and Developmental Disorders, 2023. Vol. 54, pp. 1–16. DOI: 1007/s10803-023-05926-7
78. Silva L.R., Amitai Y., Connors B.W. Intrinsic oscillations of neocortex generated by layer 5 pyramidal neurons. Science, 1991. Vol. 251 (4992), pp. 432–435. DOI: 1126/science.1824881
79. Soldatova G.U., Rasskazova E.I. Multitasking as a Personal choice of the Mode of activity in Russian children and adolescents: its relationship to experimental multitasking and its effectiveness. Psychology in Russia: State of the Art, 2022. Vol. 15 (2), pp. 113–123. DOI: 10.11621/pir.2022.0208
80. Srinivasan R. Spatial structure of the human alpha rhythm: global correlation in adults and local correlation in children. Clinical Neurophysiology, 1999. Vol. 110 (8), pp. 1351–1362. DOI: 1016/S1388-2457(99)00080-2
81. Stroganova T.A., Orekhova E.V., Posikera I.N. EEG alpha rhythm in infants. Clinical Neurophysiology, 1999. Vol. 110 (6), pp. 997–1012. DOI: 1016/S1388-2457(98)00009-1
82. Sumi Y., Miyamoto T., Sudo S. et al. Explosive sound without external stimuli following electroencephalography kappa rhythm fluctuation: A case report. Cephalalgia, 2021. Vol. 41 (13), pp. 1396–1401. DOI: 1177/03331024211021773
83. Thorpe S.G., Cannon E.N., Fox N.A. Spectral and source structural development of mu and alpha rhythms from infancy through adulthood. Clinical Neurophysiology, 2016. Vol. 127 (1), pp. 254–269. DOI: 1016/j.clinph.2015.03.004
84. Thut G., Nietzel A., Brandt S.A., Pascual-Leone A. α-Band electroencephalographic activity over occipital cortex indexes visuospatial attention bias and predicts visual target detection. The Journal of Neuroscience, 2006. Vol. 26 (37), pp. 9494–9502. DOI: 1523/JNEUROSCI.0875-06.2006
85. Vidal-Pineiro D., Wang Y., Krogsrud S.K. et al. Individual variations in ‘brain age’ relate to early-life factors more than to longitudinal brain change. ELife, 2021. Vol. 10, art. e69995. DOI: 7554/eLife.69995
86. Vijayan S., Kopell N.J. Thalamic model of awake alpha oscillations and implications for stimulus processing. Proceedings of the National Academy of Sciences of the United States of America, Vol. 109 (45), pp. 18553–18558. DOI: 10.1073/pnas.1215385109
87. Vogt F., Klimesch W., Doppelmayr M. High-frequency components in the alpha band and memory performance. Journal of Clinical Neurophysiology, 1998. Vol. 15 (2), pp. 167–172. DOI: 1097/00004691-199803000-00011
88. Vysata O., Kukal J., Prochazka A. et al. Age-related changes in the energy and spectral composition of EEG. Neurophysiology, 2012. Vol. 44 (1), pp. 63–67. DOI: 1007/s11062-012-9268-y
89. Wisniewski M.G., Joyner C.N., Zakrzewski A.C., Makeig S. Finding tau rhythms in EEG: An independent component analysis approach. Human Brain Mapping, 2024. Vol. 45 (2), art. e26572. DOI: 1002/hbm.26572
90. Wöstmann M., Alavash M., Obleser J. Alpha oscillations in the human brain implement distractor suppression independent of target selection. Journal of Neuroscience, 2019. Vol. 39 (49), pp. 9797–9805. DOI: 10.1523/JNEUROSCI.1954-19.2019