Impact of multisession 40Hz tACS on hippocampal perfusion in patients with Alzheimer's disease

Giulia Sprugnoli, Fanny Munsch, Davide Cappon, Rachel Paciorek, Joanna Macone, Ann Connor, Georges El Fakhri, Ricardo Salvador, Giulio Ruffini, Kevin Donohoe, Mouhsin M Shafi, Daniel Press, David C Alsop, Alvaro Pascual Leone, Emiliano Santarnecchi, Giulia Sprugnoli, Fanny Munsch, Davide Cappon, Rachel Paciorek, Joanna Macone, Ann Connor, Georges El Fakhri, Ricardo Salvador, Giulio Ruffini, Kevin Donohoe, Mouhsin M Shafi, Daniel Press, David C Alsop, Alvaro Pascual Leone, Emiliano Santarnecchi

Abstract

Background: Alzheimer's disease (AD) is associated with alterations in cortical perfusion that correlate with cognitive impairment. Recently, neural activity in the gamma band has been identified as a driver of arteriolar vasomotion while, on the other hand, gamma activity induction on preclinical models of AD has been shown to promote protein clearance and cognitive protection.

Methods: In two open-label studies, we assessed the possibility to modulate cerebral perfusion in 15 mild to moderate AD participants via 40Hz (gamma) transcranial alternating current stimulation (tACS) administered 1 h daily for 2 or 4 weeks, primarily targeting the temporal lobe. Perfusion-sensitive MRI scans were acquired at baseline and right after the intervention, along with electrophysiological recording and cognitive assessments.

Results: No serious adverse effects were reported by any of the participants. Arterial spin labeling MRI revealed a significant increase in blood perfusion in the bilateral temporal lobes after the tACS treatment. Moreover, perfusion changes displayed a positive correlation with changes in episodic memory and spectral power changes in the gamma band.

Conclusions: Results suggest 40Hz tACS should be further investigated in larger placebo-controlled trials as a safe, non-invasive countermeasure to increase fast brain oscillatory activity and increase perfusion in critical brain areas in AD patients.

Trial registration: Studies were registered separately on ClinicalTrials.gov ( NCT03290326 , registered on September 21, 2017; NCT03412604 , registered on January 26, 2018).

Keywords: CBF; Cerebral blood flow; Dementia; EEG; Gamma activity; Gamma band; Hippocampus; Neuromodulation; Neurostimulation; tES.

Conflict of interest statement

DCA is the inventor of the pseudo-continuous ASL technique employed for perfusion MRI in this work. He receives post-market royalties through his institution from licenses to GE Healthcare, Philips Healthcare, Hitachi Medical, Siemens Healthineers, and UIH America. GR is co-founder of Neuroelectrics and RS is an employer. ES and APL are listed co-inventors on an issued patent on the use of tACS in AD. All other authors declare they have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Experimental protocol. A Study design and relevant pre-post tACS measures. Fifteen participants with mild to moderate dementia due to AD were enrolled in total (mean age 72 years, male = 9; MMSE = 23.53, SD = 3.35). Participants received 1 h of daily tACS for 2 or 4 weeks in hospital settings (Monday to Friday), with baseline (pre-tACS) and follow-up (post-tACS) assessments composed of cognitive and memory testing, EEG, and perfusion MRI (ASL) data. Participants underwent additional assessments pre/post tACS not reported in the present manuscript and beyond the scope of the present study, e.g. PET imaging for Aβ and p-tau, transcranial magnetic stimulation (TMS) measures, combined TMS-EEG recording, voice biomarkers recording, blood biomarkers. tACS was conducted targeting the normal component of the electric field either to the bilateral temporal lobes (bitemporal tACS hereafter) or unilateral (right) temporal and frontal lobes (temporo-frontal tACS hereafter), thus always impacting the right temporal lobe across all participants (corresponding to T8 on the 10/20 EEG system). Therefore, participants can be subdivided into three subgroups: (i) subjects receiving 2 weeks (10 sessions = 10h) of unilateral temporo-frontal tACS (Group 1; n=5); (ii) subjects receiving 2 weeks (10 sessions = 10h) of bitemporal tACS (Group 2; n=5); (iii) subjects receiving 4 weeks (20 sessions = 20h) of bitemporal tACS (Group 3; n=5). Common site of stimulation across montages was represented by the right temporal lobe. B On the left, normal electrical field (En-field) for representative subject receiving unilateral temporo-frontal tACS (Group 1), on the right En-field for participants receiving bilateral temporal lobe stimulation (Groups 2 and 3)
Fig. 2
Fig. 2
Perfusion results. A CBF increase after tACS. Paired t test (post>pre, p<0.05, FDR-corrected) revealed an increase of CBF selectively involving the right temporal lobe, representing the common site of stimulation across participants (n = 15). B Whole cortical brain CBF analyses of participants who received the highest dose of tACS (20h of bilateral temporal lobe stimulation over 4 weeks, n = 5, Group 3) revealed a selective increase in CBF in the bilateral temporal lobes, accordingly to the stimulation template (p<0.05, FDR-corrected). C Examples of CBF variations in two representative participants belonging to Group 2 (pt #8) and 3 (pt #14)
Fig. 3
Fig. 3
Comparison of CBF increases between tACS montages. A When looking at significant CBF increase after tACS in Group #1 of participants who received right temporo-frontal stimulation, a pattern of predominant right temporo-frontal CBF increases was found, matching with tACS targeting. B CBF increase in participants from Group #2 + #3 (n = 10) who received bilateral temporal lobe stimulation showed a significant increase of CBF predominantly localized in bilateral temporal regions
Fig. 4
Fig. 4
CBF changes, EEG results and correlations with cognition. A Changes in spectral power in the gamma band for a cluster of EEG electrodes indexing regions displaying post-tACS increase in perfusion (T8, P8, P7, T7; left panel) are reported, as well as for the electrode T8 (right panel) representing the common tACS electrode across all participants and the scalp electrode more proximal to the right anterior temporal lobe displaying the highest change in CBF post-tACS. B Spectral power changes in the narrow gamma band (38-42 Hz) detected on T8 significantly correlate with CBF changes in the right temporal lobe (left panel). Significant CBF variations also showed a significant correlation with variations in memory performance scores pre-post tACS. Specifically, CBF variation in the right temporal regions across all participants (n=15) positively correlated with performance changes at both paraphrase (mid panel) and verbatim (right panel) recollection components of an episodic memory task

References

    1. Hebert LE, Weuve J, Scherr PA, Evans DA. Alzheimer disease in the United States (2010-2050) estimated using the 2010 census. Neurology. 2013;80:1778–1783.
    1. Forester BP, Patrick RE, Harper DG. Setbacks and opportunities in disease-modifying therapies in alzheimer disease. JAMA Psychiatry. 2019;77(1):7–8. doi: 10.1001/jamapsychiatry.2019.2332.
    1. Dai W, Lopez OL, Carmichael OT, Becker JT, Kuller LH, Gach HM. Mild cognitive impairment and Alzheimer disease: patterns of altered cerebral blood flow at MR imaging. Radiology. 2009;250:856–866.
    1. Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73:102–116.
    1. Alsop DC, Detre JA, Grossman M. Assessment of cerebral blood flow in Alzheimer’s disease by spin-labeled magnetic resonance imaging. Ann Neurol. 2000;47:93–100.
    1. Alsop DC, Casement M, de Bazelaire C, Fong T, Press DZ. Hippocampal hyperperfusion in Alzheimer’s disease. Neuroimage. 2008;42:1267–1274.
    1. Chen W, Song X, Beyea S, D’Arcy R, Zhang Y, Rockwood K. Advances in perfusion magnetic resonance imaging in Alzheimer’s disease. Alzheimers Dement. 2011;7:185–196.
    1. Huang C-W, Hsu S-W, Chang Y-T, Huang S-H, Huang Y-C, Lee C-C, et al. Cerebral perfusion insufficiency and relationships with cognitive deficits in alzheimer’s disease: a multiparametric neuroimaging study. Sci Rep. 2018;8:1541.
    1. Binnewijzend MAA, Benedictus MR, Kuijer JPA, van der Flier WM, Teunissen CE, Prins ND, et al. Cerebral perfusion in the predementia stages of Alzheimer’s disease. Eur Radiol. 2016;26:506–514.
    1. Chao LL, Buckley ST, Kornak J, Schuff N, Madison C, Yaffe K, et al. ASL perfusion MRI predicts cognitive decline and conversion from MCI to dementia. Alzheimer Dis Assoc Disord. 2010;24:19–27.
    1. Mateo C, Knutsen PM, Tsai PS, Shih AY, Kleinfeld D. Entrainment of arteriole vasomotor fluctuations by neural activity is a basis of blood-oxygenation-level-dependent “resting-state” connectivity. Neuron. 2017;96:936–948.e3.
    1. Drew PJ, Mateo C, Turner KL, Yu X, Kleinfeld D. Ultra-slow oscillations in fMRI and resting-state connectivity: neuronal and vascular contributions and technical confounds. Neuron. 2020;107:782–804.
    1. van Veluw SJ, Hou SS, Calvo-Rodriguez M, Arbel-Ornath M, Snyder AC, Frosch MP, et al. Vasomotion as a driving force for paravascular clearance in the awake mouse brain. Neuron. 2020;105:549–561.e5.
    1. Nedergaard M, Goldman SA. Glymphatic failure as a final common pathway to dementia. Science. 2020;370:50–56.
    1. Iaccarino HF, Singer AC, Martorell AJ, Rudenko A, Gao F, Gillingham TZ, et al. Gamma frequency entrainment attenuates amyloid load and modifies microglia. Nature. 2016;540:230–235.
    1. Palop JJ, Mucke L. Network abnormalities and interneuron dysfunction in Alzheimer disease. Nat Rev Neurosci. 2016;17:777–792.
    1. Adaikkan C, Middleton SJ, Marco A, Pao P-C, Mathys H, Kim DN-W, et al. Gamma entrainment binds higher-order brain regions and offers Neuroprotection. Neuron. 2019;102(5):929–43.e8. 10.1016/j.neuron.2019.04.011. Epub 2019 May 7.
    1. Verret L, Mann EO, Hang GB, Barth AMI, Cobos I, Ho K, et al. Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell. 2012;149:708–721.
    1. Babiloni C, Lizio R, Marzano N, Capotosto P, Soricelli A, Triggiani AI, et al. Brain neural synchronization and functional coupling in Alzheimer’s disease as revealed by resting state EEG rhythms. Int J Psychophysiol. 2016;103:88–102.
    1. Thomson H. How flashing lights and pink noise might banish Alzheimer’s, improve memory and more. Nature. 2018;555:20–22.
    1. Fröhlich F, McCormick DA. Endogenous electric fields may guide neocortical network activity. Neuron. 2010;67:129–143.
    1. Ozen S, Sirota A, Belluscio MA, Anastassiou CA, Stark E, Koch C, et al. Transcranial electric stimulation entrains cortical neuronal populations in rats. JNeurosci. 2010;30:11476–11485.
    1. Johnson L, Alekseichuk I, Krieg J, Doyle A, Yu Y, Vitek J, et al. Dose-dependent effects of transcranial alternating current stimulation on spike timing in awake nonhuman primates. Sci Adv. 2020;6(36):eaaz2747. 10.1126/sciadv.aaz2747. Print 2020 Sep.
    1. Krause MR, Vieira PG, Csorba BA, Pilly PK, Pack CC. Transcranial alternating current stimulation entrains single-neuron activity in the primate brain. Proc Natl Acad Sci U S A. 2019;116:5747–5755.
    1. Schmidt SL, Iyengar AK, Foulser AA, Boyle MR, Fröhlich F. Endogenous cortical oscillations constrain neuromodulation by weak electric fields. Brain Stimul. 2014;7:878–889.
    1. Ahn S, Mellin JM, Alagapan S, Alexander ML, Gilmore JH, Jarskog LF, et al. Targeting reduced neural oscillations in patients with schizophrenia by transcranial alternating current stimulation. Neuroimage. 2019;186:126–36. 10.1016/j.neuroimage.2018.10.056. Epub 2018 Oct 24.
    1. Ahn S, Prim JH, Alexander ML, McCulloch KL, Fröhlich F. Identifying and engaging neuronal oscillations by Transcranial alternating current stimulation in patients with chronic low Back pain: a randomized, crossover, double-blind, sham-controlled pilot study. J Pain. 2019;20(3):277.e1–277.e11. 10.1016/j.jpain.2018.09.004. Epub 2018 Sep 27.
    1. Antonenko D, Faxel M, Grittner U, Lavidor M, Flöel A. Effects of Transcranial alternating current stimulation on cognitive functions in healthy young and older adults. Neural Plast. 2016;2016:4274127.
    1. Santarnecchi E, Biasella A, Tatti E, Rossi A, Prattichizzo D, Rossi S. High-gamma oscillations in the motor cortex during visuo-motor coordination: a tACS interferential study. Brain Res Bull. 2017;131:47–54.
    1. Santarnecchi MT, Rossi S, Sarkar A, Polizzotto NR, Rossi A, et al. Individual differences and specificity of prefrontal gamma frequency-tACS on fluid intelligence capabilities. Cortex. 2016;75:33–43.
    1. Santarnecchi E, Sprugnoli G, Bricolo E, Costantini G, Liew S-L, Musaeus CS, et al. Gamma tACS over the temporal lobe increases the occurrence of Eureka! Moments. Sci Rep. 2019;9:5778.
    1. Santarnecchi E, Polizzotto NR, Godone M, Giovannelli F, Feurra M, Matzen L, et al. Frequency-dependent enhancement of fluid intelligence induced by transcranial oscillatory potentials. Curr Biol. 2013;23:1449–1453.
    1. Kasten FH, Dowsett J, Herrmann CS. Sustained aftereffect of α-tACS lasts up to 70 min after stimulation. Front Hum Neurosci. 2016;10:245.
    1. Pontecorvo MJ, Devous MD, Navitsky M, Lu M, Salloway S, Schaerf FW, et al. Relationships between flortaucipir PET tau binding and amyloid burden, clinical diagnosis, age and cognition. Brain. 2017;140:748–763.
    1. Ruffini G, Wendling F, Sanchez-Todo R, Santarnecchi E. Targeting brain networks with multichannel transcranial current stimulation (tCS) Curr Opin Biomed Eng. 2018;8:70–77.
    1. Antal A, Alekseichuk I, Bikson M, Brockmöller J, Brunoni AR, Chen R, et al. Low intensity transcranial electric stimulation: safety, ethical, legal regulatory and application guidelines. Clin Neurophysiol. 2017;128:1774–1809.
    1. Fischer DB, Fried PJ, Ruffini G, Ripolles O, Salvador R, Banus J, et al. Multifocal tDCS targeting the resting state motor network increases cortical excitability beyond traditional tDCS targeting unilateral motor cortex. Neuroimage. 2017;157:34–44.
    1. Ruffini G, Fox MD, Ripolles O, Miranda PC, Pascual-Leone A. Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields. Neuroimage. 2014;89:216–225.
    1. Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38:95–113.
    1. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004;134:9–21.
    1. Tadel F, Baillet S, Mosher JC, Pantazis D, Leahy RM. Brainstorm: a user-friendly application for MEG/EEG analysis. Comput Intell Neurosci. 2011;2011:879716. 10.1155/2011/879716. Epub 2011 Apr 13.
    1. Claus JJ, Kwa VI, Teunisse S, Walstra GJ, van Gool WA, Koelman JH, et al. Slowing on quantitative spectral EEG is a marker for rate of subsequent cognitive and functional decline in early Alzheimer disease. Alzheimer Dis Assoc Disord. 1998;12:167–174.
    1. Rosen WG, Mohs RC, Davis KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry. 1984;141:1356–1364.
    1. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–198.
    1. Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53:695–699.
    1. Galasko D, Bennett D, Sano M, Ernesto C, Thomas R, Grundman M, et al. An inventory to assess activities of daily living for clinical trials in Alzheimer’s disease. The Alzheimer’s disease cooperative study. Alzheimer Dis Assoc Disord. 1997;11 Suppl 2:S33–S39.
    1. Craft S, Newcomer J, Kanne S, Dagogo-Jack S, Cryer P, Sheline Y, et al. Memory improvement following induced hyperinsulinemia in Alzheimer’s disease. Neurobiol Aging. 1996;17:123–130.
    1. Morris JC, Heyman A, Mohs RC, Hughes JP, van Belle G, Fillenbaum G, et al. The consortium to establish a registry for Alzheimer’s disease (CERAD). Part I. clinical and neuropsychological assessment of Alzheimer’s disease. Neurology. 1989;39:1159–1165.
    1. Iizuka T, Kameyama M. Cholinergic enhancement increases regional cerebral blood flow to the posterior cingulate cortex in mild Alzheimer’s disease. Geriatr Gerontol Int. 2017;17:951–958.
    1. Li W, Antuono PG, Xie C, Chen G, Jones JL, Ward BD, et al. Changes in regional cerebral blood flow and functional connectivity in the cholinergic pathway associated with cognitive performance in subjects with mild Alzheimer’s disease after 12-week donepezil treatment. Neuroimage. 2012;60:1083–1091.
    1. Bahr-Hosseini M, Bikson M. Neurovascular-modulation: a review of primary vascular responses to transcranial electrical stimulation as a mechanism of action. Brain Stimul. 2021;14:837–847.
    1. Turner DA, Degan S, Galeffi F, Schmidt S, Peterchev AV. Rapid, dose-dependent enhancement of cerebral blood flow by transcranial AC stimulation in mouse. Brain Stimul. 2020;14:80–87.
    1. Zheng X, Alsop DC, Schlaug G. Effects of transcranial direct current stimulation (tDCS) on human regional cerebral blood flow. Neuroimage. 2011;58:26–33.
    1. Peppiatt CM, Howarth C, Mobbs P, Attwell D. Bidirectional control of CNS capillary diameter by pericytes. Nature. 2006;443:700–704.
    1. Masamoto K, Unekawa M, Watanabe T, Toriumi H, Takuwa H, Kawaguchi H, et al. Unveiling astrocytic control of cerebral blood flow with optogenetics. Sci Rep. 2015;5:11455.
    1. Chen Y, Wolk DA, Reddin JS, Korczykowski M, Martinez PM, Musiek ES, et al. Voxel-level comparison of arterial spin-labeled perfusion MRI and FDG-PET in Alzheimer disease. Neurology. 2011;77:1977–1985.
    1. Jueptner M, Weiller C. Review: does measurement of regional cerebral blood flow reflect synaptic activity? Implications for PET and fMRI. Neuroimage. 1995;2:148–156.
    1. Musiek ES, Chen Y, Korczykowski M, Saboury B, Martinez PM, Reddin JS, et al. Direct comparison of fluorodeoxyglucose positron emission tomography and arterial spin labeling magnetic resonance imaging in Alzheimer’s disease. Alzheimers Dement. 2012;8:51–59.
    1. Palop JJ, Mucke L. Amyloid-beta-induced neuronal dysfunction in Alzheimer’s disease: from synapses toward neural networks. Nat Neurosci. 2010;13:812–818.
    1. Rubinski A, Tosun D, Franzmeier N, Neitzel J, Frontzkowski L, Weiner M, et al. Lower cerebral perfusion is associated with tau-PET in the entorhinal cortex across the Alzheimer’s continuum. Neurobiol Aging. 2021;102:111–118.
    1. Seethalakshmi R, Parkar SR, Nair N, Adarkar SA, Pandit AG, Batra SA, et al. Regional brain metabolism in schizophrenia: an FDG-PET study. Indian J Psychiatry. 2006;48:149–153.
    1. Kayarian FB, Jannati A, Rotenberg A, Santarnecchi E. Targeting gamma-related pathophysiology in autism Spectrum disorder using Transcranial electrical stimulation: opportunities and challenges. Autism Res. 2020;13(7):1051–71. 10.1002/aur.2312. Epub 2020 May 28.
    1. Nakazono T, Jun H, Blurton-Jones M, Green KN, Igarashi KM. Gamma oscillations in the entorhinal-hippocampal circuit underlying memory and dementia. Neurosci Res. 2018;129:40–46.
    1. Düzel E, Penny WD, Burgess N. Brain oscillations and memory. Curr Opin Neurobiol. 2010;20:143–149.
    1. Takeshima N, Ishiwata K, Sozu T, Furukawa TA. Primary endpoints in current phase II/III trials for Alzheimer disease: a systematic survey of trials registered at . Alzheimer Dis Assoc Disord. 2020;34:97–100.
    1. Sandran N, Hillier S, Hordacre B. Strategies to implement and monitor in-home transcranial electrical stimulation in neurological and psychiatric patient populations: a systematic review. J Neuroeng Rehabil. 2019;16:58.
    1. Long JM, Holtzman DM. Alzheimer disease: an update on pathobiology and treatment strategies. Cell. 2019;179:312–339.

Source: PubMed

3
Suscribir