Can noninvasive brain stimulation enhance function in the ageing brain?

J Neurophysiol 111: 1–3, 2014. First published September 4, 2013; doi:10.1152/jn.00088.2013.

Neuro Forum

Can noninvasive brain stimulation enhance function in the ageing brain? Ann-Maree Vallence and Mitchell R. Goldsworthy The Robinson Institute, School of Pediatrics and Reproductive Health, University of Adelaide, Adelaide, Australia Submitted 4 February 2013; accepted in final form 30 August 2013

Vallence A-M, Goldsworthy MR. Can noninvasive brain stimulation enhance function in the ageing brain? J Neurophysiol 111: 1–3, 2014. First published September 4, 2013; doi:10.1152/jn.00088.2013.—Advancing age is associated with cognitive and motor performance deficits and a reduced capacity for plasticity. Zimerman and colleagues (Zimerman M, Nitsch M, Giraux P, Gerloff C, Cohen LG, Hummel FC. Ann Neurol 73: 10 –15, 2013) have recently shown that noninvasive brain stimulation can enhance behavioral improvements following training on a motor sequence task in older adults. The work is of high clinical importance given the rapidly growing ageing population and the accompanying costs to health systems globally. noninvasive brain stimulation; ageing; skill acquisition; consolidation

suggests that advancing age is associated with cognitive and motor performance deficits, both of which have a profound impact on older adults’ independence, and, as a consequence, their quality of life (reviews Seidler et al. 2010 and Li et al. 2001). Given the rapid increase in the proportion of the population over the age of 65, it is important to develop interventions to improve motor and cognitive function in the ageing population. Evidence from both animal and human studies has shown that advanced ageing is associated with a reduction in the capacity for plasticity (Foster and Norris 1997; Landfield et al. 1978; Muller-Dahlhaus et al. 2008; Rogasch et al. 2009; for review see Burke and Barnes 2006). Experiments in animal studies have shown that at least some forms of motor learning are mediated by long-term potentiation (LTP) and long-term depression (LTD) in the motor cortex (Rioult-Pedotti et al. 1998, 2000). There is also evidence in humans to suggest that LTP-like processes in the primary motor cortex (M1) are important in the early stages of motor learning (Rosenkranz et al. 2007; Stefan et al. 2006; Ziemann 2004). The last decade has seen many groups investigate the potential of noninvasive brain stimulation (NBS) to induce plasticity. There is good evidence to suggest that, similar to motor learning, NBS protocols can induce plasticity via LTP- and LTD-like processes (for review see Cooke and Bliss 2006). Not surprisingly, this literature has generated excitement surrounding the potential of NBS to induce behaviorally important plasticity. In young adults, there is some evidence to suggest that NBS protocols are effective in enhancing learning (for example, Nitsche et al. 2003; Reis et al. 2009). The capacity for NBS to enhance learning in older adults might provide substantial clinical benefits in light of the growing ageing population and associated costs to health systems globally. Recently, Zimerman and colleagues (2013) investigated the important

A LARGE BODY OF LITERATURE

Address for reprint requests and other correspondence: A.-M. Vallence, NeuroPAD DX 650-517, Robinson Institute, School of Pediatrics and Reproductive Health, Univ. of Adelaide, SA 5005 (e-mail: ann-maree.vallence@ adelaide.edu.au). www.jn.org

question: Can NBS enhance the learning and retention of complex skills, yielding longer-lasting behavioral improvements, in older adults? Zimerman and colleagues (2013) examined the effect of anodal transcranial direct current stimulation (atDCS), a facilitatory protocol that increases cortical excitability via LTP-like synaptic changes (Nitsche et al. 2008), on learning and retention of a motor sequence task in young (aged between 22–31 years old) and older adults (aged between 55– 88 years old) (see Zimerman et al. 2013, Fig. 1). The motor sequence task comprised a five-element key-pressing sequence to be performed as quickly and as accurately as possible, a task known to engage a large, distributed network of motor areas, including the M1 contralateral to the hand performing the task (Grafton et al. 1995; Penhune and Doyon 2002; Ungerleider et al. 2002). Participants completed five blocks of training, each lasting 3 min with a 2-min break between blocks. atDCS or sham stimulation (control condition) was applied with the anode placed over the hand knob of left M1 and the cathode placed over the contralateral supraorbital region. Learning and retention was assessed by measuring the number of correct sequences achieved in each block during the training phase and retest phase, respectively. As expected, older adults performed worse on the motor task than young adults. This finding is in line with the large body of literature showing age-related deficits in motor performance (for example, Grabiner and Enoka 1995; Light and Spirduso 1990; Smith et al. 1999). Zimerman and colleagues (2013) suggest that the poorer performance across the training blocks of older than younger adults shows significantly reduced learning in older adults. Zimmerman and colleagues (2013) also showed significantly greater behavioral improvements in older adults receiving atDCS than sham during training. Furthermore, when tested 90 min and 24 h after training, performance of the learned skill was significantly greater in older adults who received atDCS than sham during training. Zimerman and colleagues suggest that these data show that increasing excitability of M1 (using atDCS) during the training phase of the motor sequence task can increase both learning and retention in older adults. While the results of Zimerman and colleagues’ (2013) study provide some evidence that atDCS can enhance learning in older adults, two limitations are worth noting. First, it is very difficult to quantify learning differences between two groups when baseline performance is different. While the change in performance across training blocks was significantly smaller for older adults than young adults, the older adults also had a lower baseline performance. As a result, it is not possible to determine the effect of learning independently of baseline performance. Furthermore, in older adults, an absolute difference in baseline performance was evident between the atDCS

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NEUROENHANCEMENT OF THE AGEING BRAIN

and sham groups; this small difference in performance at baseline might act as a confound when assessing differences in learning. While the difference was not statistically significant, a power analysis would be useful to determine the importance, if any, of the absolute difference in this sample. To accurately assess age-related changes in learning, differences in baseline performance between groups could be either eliminated by modifying task difficulty (for example, Heuninckx et al. 2005; Wu and Hallett 2005) or controlled for by performing analyses on subgroups of participants with similar baseline performance levels. Second, behavioral improvements during training differed between the two groups, and, therefore, it is not possible to distinguish the effect of atDCS on retention independent of learning; the degree of retention might be a function of learning such that those who learn more retain more. Using a task in which there are no in-session learning differences between target groups would allow the investigation of the effect of atDCS on retention, independent of learning. There is good evidence from animal studies to show that motor learning results in structural changes in M1 (RioultPedotti et al. 1998, 2000). In humans, studies using transcranial magnetic stimulation (TMS) have provided evidence that motor learning induces LTP-like plasticity in M1 (Rosenkranz et al. 2007; Stefan et al. 2006; Ziemann et al. 2004). In line with this, Zimerman and colleagues (2013) suggested that the greater behavioral improvements evident in older adults who received atDCS (compared with sham) during training is due to facilitation of LTP-like processes in M1, likely mediated by a modulation of GABAergic neurotransmission and an enhancement of NMDA-dependent processes. It is, in fact, possible to test this suggestion: paired-pulse TMS protocols can be used to measure GABAergic and NMDA-dependent processes acting within M1. When a subthreshold TMS stimulus (S1) precedes a suprathreshold TMS stimulus (S2) by 1– 6 ms, the amplitude of the motor-evoked potential (MEP) elicited by S2 is suppressed due to the activation (by S1) of short-interval intracortical inhibitory (SICI) circuits (Kujirai et al. 1993). When the interval between S1 and S2 is 10 –15 ms, the amplitude of the MEP elicited by S2 is facilitated due to the activation (by S1) of intracortical facilitatory (ICF) circuits (Kujirai et al. 1993). Pharmacological studies have shown that SICI and ICF are mediated by GABAA receptor and NMDA-dependent processes, respectively (Di Lazzaro et al. 2000; Ziemann et al. 1998). Measuring SICI and ICF before and after training of the motor sequence task, accompanied by either atDCS or sham tDCS, would provide knowledge regarding the proposed role of GABAergic and NMDA-dependent processes in the atDCSfacilitated motor learning in older adults. If modulation of GABAergic and NMDA-dependent processes is involved in the atDCS-facilitated motor learning, we would expect to observe a decrease in SICI and an increase in ICF following training accompanied by atDCS compared with baseline, and compared with training accompanied by sham in older adults. While Zimerman and colleagues (2013) were interested in testing the possibility of neuroenhancement of learning generally, their use of a motor task to test this hypothesis highlights the important issue of age-related deficits in motor function (for review, see Seidler et al. 2010). Visuomotor adaptation, which requires adaptation to external perturbations, is often used to investigate motor function (for review, see Krakauer 2009). While both motor sequence learning and visuomotor

adaptation engage a large distributed cortical network, there is some evidence to suggest that the cortico-cerebellar network is particularly important in motor adaptation (Martin et al. 1996; Maschke et al. 2004; Smith and Shadmehr 2005). Therefore, the cerebellum might prove an effective target for NBS as a means to improve the ability to adapt to changes in the environment in the ageing population, thereby improving motor function. Indeed, some support for this suggestion comes from work in young adults where atDCS delivered to the cerebellum was shown to enhance performance in the acquisition phase of a visuomotor adaptation task compared with sham (Galea et al. 2011). In summary, Zimerman and colleagues (2013) have provided novel and clinically relevant evidence suggesting that NBS could be used to enhance motor function in the ageing population. This work is of high clinical importance given the rapidly growing ageing population and the accompanying costs to health systems globally. A plausible next step is to further develop NBS protocols and identify new, effective targets for neuroenhancement of the ageing brain that will lead to functional improvements in both the motor and cognitive domains. An equally important next step is to develop a better understanding of the neurophysiological causes of age-related deficits in motor function. The outcome: the development of safe NBS protocols that can increase independence and quality of life in the ageing population. ACKNOWLEDGMENTS We thank Michael C. Ridding for valuable feedback. DISCLOSURES No conflicts of interest, financial or otherwise, are declared by the author(s). AUTHOR CONTRIBUTIONS A.-M.V. and M.R.G. interpreted results of experiments; A.-M.V. prepared figures; A.-M.V. drafted manuscript; A.-M.V. and M.R.G. edited and revised manuscript; A.-M.V. and M.R.G. approved final version of manuscript. REFERENCES Burke SN, Barnes CA. Neural plasticity in the ageing brain. Nat Rev Neurosci 7: 30 – 40, 2006. Cooke SF, Bliss TV. Plasticity in the human central nervous system. Brain 129: 1659 –1673, 2006. Di Lazzaro V, Oliviero A, Meglio M, Cioni B, Tamburrini G, Tonali P, Rothwell JC. Direct demonstration of the effect of lorazepam on the excitability of the human motor cortex. Clin Neurophysiol 111: 794 –799, 2000. Foster TC, Norris CM. Age-associated changes in Ca2⫹-dependent processes: relation to hippocampal synaptic plasticity. Hippocampus 7: 602– 612, 1997. Galea JM, Vazquez A, Pasricha N, de Xivry JJ, Celnik P. Dissociating the roles of the cerebellum and motor cortex during adaptive learning: the motor cortex retains what the cerebellum learns. Cereb Cortex 21: 1761–1770, 2011. Grabiner MD, Enoka RM. Changes in movement capabilities with aging. Exerc Sport Sci Rev 23: 65–104, 1995. Grafton ST, Hazeltine E, Ivry R. Functional mapping of sequence learning in normal humans. J Cogn Neurosci 7: 497–510, 1995. Heuninckx S, Wenderoth N, Debaere F, Peeters R, Swinnen SP. Neural basis of aging: the penetration of cognition into action control. J Neurosci 25: 6787– 6796, 2005. Krakauer JW. Motor learning and consolidation: the case of visuomotor rotation. In: Progress in Motor Control: A Multidisciplinary Perspective, edited by Sternad D. Adv Exp Med Biol, 2009, vol 629, p. 405– 421.

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Neuro Forum NEUROENHANCEMENT OF THE AGEING BRAIN Kujirai T, Caramia MD, Rothwell JC, Day BL, Thompson PD, Ferbert A, Wroe S, Asselman P, Marsden CD. Corticocortical inhibition in human motor cortex. J Physiol 471: 501–519, 1993. Landfield PW, McGaugh JL, Lynch G. Impaired synaptic potentiation processes in hippocampus of aged, memory-deficient rats. Brain Res 150: 85–101, 1978. Li SC, Lindenberger U, Sikstrom S. Aging cognition: from neuromodulation to representation. Trends Cogn Sci 5: 479 – 486, 2001. Light KE, Spirduso WW. Effects of adult aging on the movement complexity factor of response programming. J Gerontol 45: P107–P109, 1990. Martin TA, Keating JG, Goodkin HP, Bastian AJ, Thach WT. Throwing while looking through prisms. I. Focal olivocerebellar lesions impair adaptation. Brain 119: 1183–1198, 1996. Maschke M, Gomez CM, Ebner TJ, Konczak J. Hereditary cerebellar ataxia progressively impairs force adaptation during goal-directed arm movements. J Neurophysiol 91: 230 –238, 2004. Muller-Dahlhaus JFM, Orekhov Y, Liu Y, Ziemann U. Interindividual variability and age-dependency of motor cortical plasticity induced by paired associative stimulation. Exp Brain Res 187: 467– 475, 2008. Nitsche MA, Cohen LG, Wassermann EM, Priori A, Lang N, Antal A, Paulus W, Hummel F, Boggio PS, Fregni F, Pascual-Leone A. Transcranial direct current stimulation: state of the art 2008. Brain Stimul 1: 206 –223, 2008. Nitsche MA, Schauenburg A, Lang N, Liebetanz D, Exner C, Paulus W, Tergau F. Facilitation of implicit motor learning by weak transcranial direct current stimulation of the primary motor cortex in the human. J Cogn Neurosci 15: 619 – 626, 2003. Penhune VB, Doyon J. Dynamic cortical and subcortical networks in learning and delayed recall of timed motor sequences. J Neurosci 22: 1397–1406, 2002. Reis J, Schambra HM, Cohen LG, Buch ER, Fritsch B, Zarahn E, Celnik PA, Krakauer JW. Noninvasive cortical stimulation enhances motor skill acquisition over multiple days through an effect on consolidation. Proc Natl Acad Sci USA 106: 1590 –1595, 2009. Rioult-Pedotti MS, Friedman D, Donoghue JP. Learning-induced LTP in neocortex. Science 290: 533–536, 2000.

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Rioult-Pedotti MS, Friedman D, Hess G, Donoghue JP. Strengthening of horizontal cortical connections following skill learning. Nat Neurosci 1: 230 –234, 1998. Rogasch NC, Dartnall TJ, Cirillo J, Nordstrom MA, Semmler JG. Corticomotor plasticity and learning of a ballistic thumb training task are diminished in older adults. J Appl Physiol 107: 1874 –1883, 2009. Rosenkranz K, Kacar A, Rothwell JC. Differential modulation of motor cortical plasticity and excitability in early and late phases of human motor learning. J Neurosci 27: 12058 –12066, 2007. Seidler RD, Bernard JA, Burutolu TB, Fling BW, Gordon MT, Gwin JT, Kwak Y, Lipps DB. Motor control and aging: links to age-related brain structural, functional, and biochemical effects. Neurosci Biobehav Rev 34: 721–733, 2010. Smith CD, Umberger GH, Manning EL, Slevin JT, Wekstein DR, Schmitt FA, Markesbery WR, Zhang Z, Gerhardt GA, Kryscio RJ, Gash DM. Critical decline in fine motor hand movements in human aging. Neurology 53: 1458 –1461, 1999. Smith MA, Shadmehr R. Intact ability to learn internal models of arm dynamics in Huntington’s disease but not cerebellar degeneration. J Neurophysiol 93: 2809 –2821, 2005. Stefan K, Wycislo M, Gentner R, Schramm A, Naumann M, Reiners K, Classen J. Temporary occlusion of associative motor cortical plasticity by prior dynamic motor training. Cereb Cortex 16: 376 –385, 2006. Ungerleider LG, Doyon J, Karni A. Imaging brain plasticity during motor skill learning. Neurobiol Learn Mem 78: 553–564, 2002. Wu T, Hallett M. The influence of normal human ageing on automatic movements. J Physiol 562: 605– 615, 2005. Ziemann U. TMS induced plasticity in human cortex. Rev Neurosci 15: 253–266, 2004. Ziemann U, Chen R, Cohen LG, Hallett M. Dextromethorphan decreases the excitability of the human motor cortex. Neurology 51: 1320 –1324, 1998. Ziemann U, Iliac TV, Pauli C, Meintzschel F, Ruge D. Learning modifies subsequent induction of long-term potentiation-like and long-term depression-like plasticity in human motor cortex. J Neurosci 24: 1666 –1672, 2004. Zimerman M, Nitsch M, Giraux P, Gerloff C, Cohen LG, Hummel FC. Neuroenhancement of the aging brain: restoring skill acquisition in old subjects. Ann Neurol 73: 10 –15, 2013.

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