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Effects of repetitive paired associative stimulation on brain plasticity and working memory in Alzheimer’s disease: a pilot randomized double-blind-controlled trial

Published online by Cambridge University Press:  16 November 2020

Sanjeev Kumar ,
Reza Zomorrodi ,
Zaid Ghazala ,
Michelle S. Goodman ,
Daniel M. Blumberger ,
Zafiris J. Daskalakis ,
Corinne E. Fischer ,
Benoit H. Mulsant ,
Bruce G. Pollock  and
Tarek K. Rajji
Sanjeev Kumar
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
Reza Zomorrodi
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
Zaid Ghazala
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
Michelle S. Goodman
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
Daniel M. Blumberger
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
Zafiris J. Daskalakis
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
Corinne E. Fischer
Affiliation:
Department of Psychiatry, University of Toronto, Toronto, ON, Canada Keenan Research Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, Canada
Benoit H. Mulsant
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
Bruce G. Pollock
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
Tarek K. Rajji*
Affiliation:
Campbell Family Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada Department of Psychiatry, University of Toronto, Toronto, ON, Canada
*
Correspondence should be addressed to: Dr. Tarek Rajji, MD, FRCPC, Adult Neurodevelopment and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, 80 Workman Way, Toronto, ON M6J 1H4, Canada. Phone: +1 416 535 8501x33661; Fax: +1 416 583 1307. Email: Tarek.Rajji@camh.ca.
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Abstract

Design:

Pilot randomized double-blind-controlled trial of repetitive paired associative stimulation (rPAS), a paradigm that combines transcranial magnetic stimulation (TMS) of the dorsolateral prefrontal cortex (DLPFC) with peripheral median nerve stimulation.

Objectives:

To study the impact of rPAS on DLPFC plasticity and working memory performance in Alzheimer’s disease (AD).

Methods:

Thirty-two patients with AD (females = 16), mean (SD) age = 76.4 (6.3) years were randomized 1:1 to receive a 2-week (5 days/week) course of active or control rPAS. DLPFC plasticity was assessed using single session PAS combined with electroencephalography (EEG) at baseline and on days 1, 7, and 14 post-rPAS. Working memory and theta–gamma coupling were assessed at the same time points using the N-back task and EEG.

Results:

There were no significant differences between the active and control rPAS groups on DLPFC plasticity or working memory performance after the rPAS intervention. There were significant main effects of time on DLPFC plasticity, working memory, and theta–gamma coupling, only for the active rPAS group. Further, on post hoc within-group analyses done to generate hypotheses for future research, as compared to baseline, only the rPAS group improved on post-rPAS day 1 on all three indices. Finally, there was a positive correlation between working memory performance and theta–gamma coupling.

Conclusions:

This study did not show a beneficial effect of rPAS for DLPFC plasticity or working memory in AD. However, post hoc analyses showed promising results favoring rPAS and supporting further research on this topic. (Clinicaltrials.gov-NCT01847586)

Keywords

dementianeuroplasticitygeriatricstranscranial magnetic stimulationtheta–gamma couplingTMS-EEG
Type
Original Research Article
Information
International Psychogeriatrics , Volume 35 , Special Issue 3: Issue Theme: Thinking outside the box: later life wellbeing and functioning from new angles , March 2023 , pp. 143 - 155
Copyright
© International Psychogeriatric Association 2020

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References

Alexopoulos, G. S., Abrams, R. C., Young, R. C. and Shamoian, C. A. (1988). Cornell scale for depression in dementia. Biological Psychiatry, 23(3), 271–284.CrossRefGoogle ScholarPubMed
Baddeley, A. (1996). The fractionation of working memory. Proceedings of the National Academy of Sciences of the United States of America, 93(24), 13468–13472.CrossRefGoogle ScholarPubMed
Baddeley, A. D., Bressi, S., Dellasala, S., Logie, R. and Spinnler, H. (1991). The decline of working memory in Alzheimer’s disease – a longitudinal-study. Brain, 114, 2521–2542.Google ScholarPubMed
Battaglia, F. et al. (2007) Cortical plasticity in Alzheimer’s disease in humans and rodents. Biological Psychiatry, 62(12), 1405–1412.CrossRefGoogle ScholarPubMed
Bentwich, J. et al. (2011). Beneficial effect of repetitive transcranial magnetic stimulation combined with cognitive training for the treatment of Alzheimer’s disease: a proof of concept study. Journal of Neural Transmission, 118(3), 463–471.CrossRefGoogle ScholarPubMed
Birks, J. (2006). Cholinesterase inhibitors for Alzheimer’s disease. Cochrane Library: Cochrane Reviews, 2006(1), CD005593.Google ScholarPubMed
Buzsaki, G. (2002). Theta oscillations in the hippocampus. Neuron, 33(3), 325–340.CrossRefGoogle ScholarPubMed
Cheeran, B. et al. (2008). A common polymorphism in the brain-derived neurotrophic factor gene (BDNF) modulates human cortical plasticity and the response to rTMS. Journal of Physiology, 586(23), 5717–5725.CrossRefGoogle ScholarPubMed
Crary, J. F., Shao, C. Y., Mirra, S. S., Hernandez, A. I. and Sacktor, T. C. (2006). Atypical protein kinase C in neurodegenerative disease I: PKMzeta aggregates with limbic neurofibrillary tangles and AMPA receptors in Alzheimer disease. Journal of Neuropathology and Experimental Neurology, 65(4), 319–326.CrossRefGoogle ScholarPubMed
Cummings, J. L., Morstorf, T. and Zhong, K. (2014). Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimer’s Research & Therapy, 6(4), 37.CrossRefGoogle ScholarPubMed
Daskalakis, Z. J., Farzan, F., Barr, M. S., Maller, J. J., Chen, R. and Fitzgerald, P. B. (2008). Long-interval cortical inhibition from the dorsolateral prefrontal cortex: a TMS-EEG study. Neuropsychopharmacology, 33(12), 2860–2869.CrossRefGoogle ScholarPubMed
Dong, X. et al. (2018). Repetitive transcranial magnetic stimulation for the treatment of Alzheimer’s disease: a systematic review and meta-analysis of randomized controlled trials. PLOS ONE, 13(10), e0205704.CrossRefGoogle ScholarPubMed
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U. and May, A. (2004). Neuroplasticity: changes in grey matter induced by training. Nature, 427(6972), 311–312.CrossRefGoogle ScholarPubMed
Dubois, B. et al. (2007). Research criteria for the diagnosis of Alzheimer’s disease: revising the NINCDS-ADRDA criteria. Lancet Neurology, 6(8), 734–746.CrossRefGoogle ScholarPubMed
Faul, F., Erdfelder, E., Lang, A.-G. and Buchner, A. (2007) G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191.CrossRefGoogle ScholarPubMed
First, M. B. (2002). Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Non-patient Edition. New York: Biometrics Research, New York State Psychiatric Institute.Google Scholar
Folstein, M. F., Folstein, S. E. and McHugh, P. R. (1975). Mini-mental state - practical method for grading cognitive state of patients for clinician. Journal of Psychiatric Research, 12(3), 189–198.CrossRefGoogle ScholarPubMed
Fuster, J. M., Bodner, M. and Kroger, J. K. (2000) Cross-modal and cross-temporal association in neurons of frontal cortex. Nature, 405(6784), 347–351.CrossRefGoogle ScholarPubMed
Geddes, J., Monaghan, D., Cotman, C., Lott, I., Kim, R. and Chui, H. (1985). Plasticity of hippocampal circuitry in Alzheimer’s disease. Science, 230(4730), 1179–1181.Google ScholarPubMed
Geddes, J. W., Wilson, M. C., Miller, F. D. and Cotman, C. W. (1990). Molecular markers of reactive plasticity. Advances in Experimental Medicine and Biology, 268, 425–432.CrossRefGoogle ScholarPubMed
Gevins, A., Smith, M. E., McEvoy, L. and Yu, D. (1997). High-resolution EEG mapping of cortical activation related to working memory: effects of task difficulty, type of processing, and practice. Cerebral Cortex, 7(4), 374–385.CrossRefGoogle ScholarPubMed
Goodman, M. S. et al. (2018). Theta-gamma coupling and working memory in Alzheimer’s dementia and mild cognitive impairment. Frontiers in Aging Neuroscience, 10, 101.CrossRefGoogle ScholarPubMed
Grady, C. L., McIntosh, A. R., Beig, S., Keightley, M. L., Burian, H. and Black, S. E. (2003). Evidence from functional neuroimaging of a compensatory prefrontal network in Alzheimer’s disease. Journal of Neuroscience, 23(3), 986–993.CrossRefGoogle ScholarPubMed
Howard, M. W. et al. (2003). Gamma oscillations correlate with working memory load in humans. Cerebral Cortex, 13(12), 1369–1374.CrossRefGoogle ScholarPubMed
Hu, Y-S., Xu, P., Pigino, G., Brady, ST., Larson, J. and Lazarov, O. (2010). Complex environment experience rescues impaired neurogenesis, enhances synaptic plasticity, and attenuates neuropathology in familial Alzheimer’s disease-linked APPswe/PS1ΔE9 mice. The FASEB Journal, 24(6), 1667–1681.CrossRefGoogle ScholarPubMed
Kaufman, L. D., Pratt, J., Levine, B. and Black, S. E. (2012). Executive deficits detected in mild Alzheimer’s disease using the antisaccade task. Brain and Behavior, 2(1), 15–21.CrossRefGoogle ScholarPubMed
Kim, S. J. and Linden, D. J. (2007). Ubiquitous plasticity and memory storage. Neuron, 56(4), 582–592.CrossRefGoogle ScholarPubMed
Kumar, S. et al. (2017). Extent of dorsolateral prefrontal cortex plasticity and its association with working memory in patients with Alzheimer disease. JAMA Psychiatry, 74(12), 1266–1274.CrossRefGoogle ScholarPubMed
Lee, J., Choi, B. H., Oh, E., Sohn, E. H. and Lee, A. Y. (2016). Treatment of Alzheimer’s disease with repetitive transcranial magnetic stimulation combined with cognitive training: a prospective, randomized, double-blind, placebo-controlled study. Journal of Clinical Neurology, 12(1), 57– 64.CrossRefGoogle ScholarPubMed
Lega, B., Burke, J., Jacobs, J., and Kahana, M. J. (2016). Slow-theta-to-gamma phase-amplitude coupling in human hippocampus supports the formation of new episodic memories. Cereb Cortex, 26(1), 268–278.CrossRefGoogle ScholarPubMed
Liao, X. et al. (2015). Repetitive transcranial magnetic stimulation as an alternative therapy for cognitive impairment in Alzheimer’s disease: a meta-analysis. Journal of Alzheimer’s Disease, 48(2), 463–472.CrossRefGoogle ScholarPubMed
Lisman, J. E. and Idiart, M. A. P. (1995). Storage of 7+/-2 short-term memories in oscillatory subcycles. Science, 267(5203), 1512–1515.CrossRefGoogle ScholarPubMed
Malenka, R. C. and Bear, M. F. (2004). LTP and LTD: An embarrassment of riches. Neuron, 44(1), 5-21.CrossRefGoogle ScholarPubMed
Malenka, R. C. and Nicoll, R. A. (1999). Neuroscience – long-term potentiation – a decade of progress? Science, 285(5435), 1870–1874.CrossRefGoogle Scholar
McKay, D. R., Ridding, M. C., Thompson, P. D. and Miles, T. S. (2002). Induction of persistent changes in the organisation of the human motor cortex. Experimental Brain Research, 143(3), 342–349.CrossRefGoogle ScholarPubMed
Nowrangi, M. A. et al. (2020). The association of neuropsychiatric symptoms with regional brain volumes from patients in a tertiary multi-disciplinary memory clinic. International Psychogeriatrics, doi: 10.1017/S1041610220000113.CrossRefGoogle Scholar
Padala, P. R., Padala, K. P., Samant, R. S. and James, G. A. (2020). Improvement of neuronal integrity with methylphenidate treatment for apathy in Alzheimer’s disease. International Psychogeriatrics, 32(4), 539–540.CrossRefGoogle ScholarPubMed
Parker, M., Barlow, S., Hoe, J. and Aitken, L. (2020). Persistent barriers and facilitators to seeking help for a dementia diagnosis: a systematic review of 30 years of the perspectives of carers and people with dementia. International Psychogeriatrics, 32(5), 611–634.CrossRefGoogle Scholar
Pasupathy, A. and Miller, E. K. (2005). Different time courses of learning-related activity in the prefrontal cortex and striatum. Nature, 433(7028), 873–876.CrossRefGoogle ScholarPubMed
Pignatelli, M., Beyeler, A. and Leinekugel, X. (2012). Neural circuits underlying the generation of theta oscillations. Journal of Physiology (Paris), 106(3-4), 81–92.CrossRefGoogle ScholarPubMed
Poole, M., Wilcock, J., Rait, G., Brodaty, H. and Robinson, L. (2020). Overcoming barriers to a diagnosis of dementia: can we do it? International Psychogeriatrics, 32(5), 555–557.CrossRefGoogle Scholar
Prince, M. W. A., Guerchet, M., Ali, G. C., Wu, Y. T. and Prina, M. (2015). World Alzheimer report 2015—the global impact of dementia: an analysis of prevalence, incidence, cost and trends. London: Alzheimer’s Disease International.Google Scholar
Rabey, J. M., Dobronevsky, E., Aichenbaum, S., Gonen, O., Marton, R. G., and Khaigrekht, M. (2013). Repetitive transcranial magnetic stimulation combined with cognitive training is a safe and effective modality for the treatment of Alzheimer’s disease: a randomized, double-blind study. Journal of Neural Transmission, 120(5), 813–819.CrossRefGoogle ScholarPubMed
Rajji, T. K. et al. (2013). PAS-induced potentiation of cortical evoked activity in the dorsolateral prefrontal cortex. Neuropsychopharmacology, 38, 2545–2552.CrossRefGoogle ScholarPubMed
Rajji, T. K., Zomorrodi, R., Barr, M. S., Blumberger, D. M., Mulsant, B. H. and Daskalakis, Z. J. (2017). Ordering information in working memory and modulation of gamma by theta oscillations in humans. Cerebral Cortex, 27(2), 1482–1490.Google ScholarPubMed
Randolph, C., Tierney, M. C., Mohr, E. and Chase, T. N. (1998). The repeatable battery for the assessment of neuropsychological status (RBANS): preliminary clinical validity. Journal of Clinical and Experimental Neuropsychology, 20(3), 310–319.CrossRefGoogle ScholarPubMed
Reinhart, R. M. G. and Nguyen, J. A. (2019). Working memory revived in older adults by synchronizing rhythmic brain circuits. Nature Neuroscience, 22(5), 820.CrossRefGoogle ScholarPubMed
Rolland, Y., Abellan van Kan, G. and Vellas, B. (2008). Physical activity and alzheimer’s disease: from prevention to therapeutic perspectives. Journal of the American Medical Directors Association, 9(6), 390–405.CrossRefGoogle ScholarPubMed
Rowan, M. J., Klyubin, I., Cullen, W. K. and Anwyl, R. (2003). Synaptic plasticity in animal models of early Alzheimer’s disease. Philosophical Transactions of the Royal Society B: Biological Sciences, 358(1432), 821–828.CrossRefGoogle ScholarPubMed
Royall, D. R., Mahurin, R. K. and Gray, K. F. (1992). Bedside Assessment of Executive cognitive impairment - the executive interview. Journal of the American Geriatrics Society, 40(12), 1221–1226.CrossRefGoogle ScholarPubMed
Sabbagh, M. et al. (2019). Effects of a combined transcranial magnetic stimulation (TMS) and cognitive training intervention in patients with Alzheimer’s disease. Alzheimer’s & Dementia.Google Scholar
Smithson, M. (2003). Confidence Intervals. Thousand Oaks, CA: Sage Publications.CrossRefGoogle Scholar
Stefan, K., Kunesch, E., Cohen, LG., Benecke, R. and Classen, J. (2000). Induction of plasticity in the human motor cortex by paired associative stimulation. Brain, 123, 572–584.CrossRefGoogle ScholarPubMed
Stoiljkovic, M., Kelley, C., Horvath, T. L., and Hajos, M. (2018). Neurophysiological signals as predictive translational biomarkers for Alzheimer’s disease treatment: effects of donepezil on neuronal network oscillations in TgF344-AD rats. Alzheimer’s Research & Therapy, 10(1), 105.CrossRefGoogle ScholarPubMed
Terranova, C. et al. (2013). Impairment of sensory-motor plasticity in mild Alzheimer’s disease. Brain Stimulation, 6(1), 62–66.CrossRefGoogle ScholarPubMed
Tort, A. B., Scheffer-Teixeira, R., Souza, B. C., Draguhn, A. and Brankack, J. (2013). Theta-associated high-frequency oscillations (110-160Hz) in the hippocampus and neocortex. Progress in Neurobiology, 100, 1–14.CrossRefGoogle ScholarPubMed
Tort, A. B. L., Komorowski, R., Eichenbaum, H. and Kopell, N. (2010). Measuring phase-amplitude coupling between neuronal oscillations of different frequencies. Journal of Neurophysiology, 104(2), 1195–1210.CrossRefGoogle ScholarPubMed
Vallence, A. M. and Ridding, M. C. (2014). Non-invasive induction of plasticity in the human cortex: uses and limitations. Cortex, 58, 261-271.CrossRefGoogle ScholarPubMed
Voytek, B., Davis, M., Yago, E., Barcelo, F., Vogel, E. K., and Knight, R. T. (2010). Dynamic neuroplasticity after human prefrontal cortex damage. Neuron, 68(3), 401–408.CrossRefGoogle ScholarPubMed
Ziemann, U. et al. (2008). Consensus: motor cortex plasticity protocols. Brain Stimulation, 1(3), 164–182.CrossRefGoogle ScholarPubMed