Limited impact of homeostatic plasticity on motor learning in humans

Limited impact of homeostatic plasticity on motor learning in humans

Neuropsychologia 46 (2008) 2122–2128 Contents lists available at ScienceDirect Neuropsychologia journal homepage: www.elsevier.com/locate/neuropsych...

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Neuropsychologia 46 (2008) 2122–2128

Contents lists available at ScienceDirect

Neuropsychologia journal homepage: www.elsevier.com/locate/neuropsychologia

Limited impact of homeostatic plasticity on motor learning in humans Min-Fang Kuo, Mandy Unger, David Liebetanz, Nicolas Lang, Frithjof Tergau, Walter Paulus, Michael A. Nitsche ∗ Department of Clinical Neurophysiology, University of Goettingen, Robert Koch Str. 40, 37099 Goettingen, Germany

a r t i c l e

i n f o

Article history: Received 30 November 2007 Received in revised form 20 February 2008 Accepted 24 February 2008 Available online 29 February 2008 Keywords: Homeostatic plasticity tDCS Human Motor cortex Brain stimulation

a b s t r a c t Neuroplasticity is the adaptive modification of network connectivity in response to environmental demands and has been identified as a major physiological correlate of learning. Since unrestricted neuroplastic modifications of network connectivity will result in a de-stabilization of the system, metaplastic modification rules have been proposed for keeping plastic connectivity changes within a useful dynamic range. In this connection, the modification threshold to achieve synaptic strengthening is thought to correlate negatively with the history of activity of the respective neurons, i.e. high previous activity enhances the threshold for synaptic strengthening and vice versa. However, the relevance of metaplasticity for actual learning processes has not been tested so far. We reduced or enhanced motor cortex excitability before performance of the serial reaction time task (SRTT), a sequential motor learning paradigm, and a reaction time task (RTT) by transcranial direct current stimulation (tDCS). If homeostatic rules apply, excitability-diminishing cathodal tDCS should improve subsequent motor learning, especially if combined with the partial NMDA receptor-agonist d-cycloserine, which selectively enhances efficacy of active receptors, while excitability-enhancing anodal tDCS should reduce it. Only the results for anodal tDCS, when combined with d-cycloserine, were in accordance with the rules of homeostatic plasticity. We conclude that homeostatic plasticity, as tested here, has a limited influence on implicit sequential motor learning. © 2008 Elsevier Ltd. All rights reserved.

1. Introduction Motor learning involves the strengthening of synapses, reflecting long-term potentiation (LTP, Rioult-Pedotti, Friedman, & Donoghue, 2000). LTP-like processes are also involved in motor learning in humans (Stefan et al., 2006; Ziemann, Ilic, Pauli, Meintzschel, & Ruge, 2004). These take place at least in part in the primary motor cortex (Muellbacher et al., 2002; Nitsche, Schauenburg, et al., 2003). Since unrestricted plasticity will result in massive modifications of neuronal networks, which will de-stabilize the system and prevent further dynamic modifications, metaplastic rules were developed in artificial neuronal networks, but also experimentally in animal and human studies (Abbott & Nelson, 2000; Abraham & Tate, 1997; Turrigiano & Nelson, 2000). The Bienenstock–Cooper–Munro rule (Bienenstock, Cooper, & Munro, 1982), postulates the dependency of neuroplastic excitability enhancements or reductions from the history of activation: high-level previous activity diminishes the likelihood that ongoing neuroplastic events induce facilitation, while a history of low-level activity will favor

∗ Corresponding author. Tel.: +49 551 399571; fax: +49 551 398126. E-mail address: [email protected] (M.A. Nitsche). 0028-3932/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.neuropsychologia.2008.02.023

facilitation—due to a sliding synaptic modification threshold. The applicability of this rule has been demonstrated in human experiments: priming with excitability-enhancing repetitive transcranial magnetic stimulation (rTMS) of the motor cortex increased the excitability-reducing effects of a subsequent rTMS protocol (Iyer, Schleper, & Wassermann, 2003). Similarly, motor cortex excitability diminution by transcranial direct current stimulation (tDCS) caused rTMS protocols, which were without an effect on excitability when given alone, to increase excitability, while anodal tDCS had reverse effects (Lang et al., 2004; Siebner et al., 2004). Here we examined the relevance of the history of motor cortex excitability for motor learning, which was not explored before. tDCS was administered before performance of a sequential motor learning task (serial reaction time task (SRTT, Nissen & Bullemer, 1987)). tDCS induces modifications of the resting membrane potential. Hereby anodal tDCS enhances, cathodal stimulation reduces excitability of the primary motor cortex (Nitsche, Nitsche, et al., 2003; Nitsche & Paulus 2000, 2001). The after-effects are NMDA receptor-dependent (Liebetanz, Nitsche, Tergau, & Paulus, 2002; Nitsche, Fricke, et al., 2003; Nitsche et al., 2004). In a foregoing study (Nitsche, Schauenburg, et al., 2003), anodal tDCS of the primary motor cortex improved sequence acquisition if applied during SRTT performance. We decided to study specifically the influence of prior tDCS on SRTT performance as a model for the behavioral impact

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of homeostatic plasticity on learning, because the direct effects of tDCS are restricted to the area under the electrode (Nitsche, Doemkes, et al., 2007), and the SRTT has been shown to increase primary motor cortex excitability selectively during the early learning stages (Pascual-Leone, Grafman, & Hallett, 1994). Thus, the identical cortical area, i.e. the primary motor cortex, is affected by both protocols. Furthermore, since specifically tDCS during SRTT performance enhanced learning in the foregoing experiment, it is likely that both protocols influence identical neuronal populations. If metaplasticity influences motor learning, applying anodal tDCS prior to learning would decrease performance, while cathodal tDCS should improve it. To also pinpoint small effects of homeostatic plasticity on performance, we added an experimental arm, in which d-cycloserine (CYC) was administered. CYC is a partial NMDA receptor-agonist, which agonises active NMDA receptors (Thomas, Hood, Monahan, Contreras, & O’Donohue, 1988). After cathodal tDCS, general excitability of the primary motor cortex is diminished. Thus, during SRTT learning, learning-related synapses should be active, but background noise should be reduced. Thus, when combined with cathodal tDCS, CYC should selectively enhance the activity of learning-related synapses. Conversely, when combined with anodal tDCS, CYC should further reduce the strengthening of learning-related synapses, because it strengthens the efficacy of anodal tDCS to enhance global cortical excitability and thus due to homeostatic rules should diminish LTP of learning-related neuronal connections. To prove the specificity of the effects for motor learning, we added a control experiment in which only random stimuli blocks were performed in an otherwise identical task (reaction time task (RTT)). 2. Methods 2.1. Subjects In total, eighty healthy subjects without acute or chronic medication, recruited from the local university, who had given written informed consent were studied with ethics committee approval (SRTT experiment: 24 subjects each for anodal (12 females, age 23.8 years ±2.3 S.D.)) or cathodal tDCS (15 females, age 24.5 years ±1.9); RTT: 16 subjects for each tDCS condition (anodal tDCS group: 12 females, age 24.8 years ±5.3; cathodal tDCS group: 10 females, age 23.2 ± 2.6 years). Different numbers of subjects were used in the SRTT and RTT because it has been shown in a previous study that 12 subjects suffice to achieve significant results for the RTT task, while 20 were needed for the SRTT (Nitsche, Schauenburg, et al., 2003). The studies were performed by neurologists familiar with emergency situations in a room with life-support equipment. Each subject participated in one stimulation polarity condition only. A repeated measures design was thus performed separately for each stimulation polarity. All subjects received anodal or cathodal, and the respective placebo tDCS stimulation with or without medication in different sessions. The order of the different stimulation and medication conditions was balanced between subjects for each stimulation polarity. Right- and left-handed subjects were randomized between the groups. Allocation to different tasks (SRTT vs. RTT as well as with regard to the specific sequence performed under a specific medication/stimulation condition) and stimulation groups was also randomized.

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contralateral orbit. tDCS was applied using a ramp-like switch, increasing current strength gradually for the first and last 10 s of tDCS. For sham tDCS, current was switched off after 30 s of stimulation. This protocol has been demonstrated to reliably blind subjects with regard to the stimulation condition (Gandiga, Hummel, & Cohen, 2006). 2.4. Serial reaction time task Subjects were seated in front of a computer screen at eye level and a response pad on the table with four buttons numbered 1–4. They were instructed to push each button with a different finger of the right hand (index finger for button 1, middle finger for button 2, ring finger for button 3, and little finger for button 4). An asterisk appeared in one of 4 positions that were horizontally spaced on a computer screen and permanently marked by dots. The subjects were instructed to press the key corresponding to the position of the asterisks as fast and correct as possible. After a button was pushed, the go signal disappeared. The next go signal was displayed 500 ms after the subject pushed the button, independent of correct or incorrect reaction. The learning test consisted of 8 blocks of 120 trials. In blocks 1 and 6 the sequence of asterisks followed a pseudo-random order in that asterisks were presented equally frequently in each position and never in the same position in two subsequent trials. In blocks 2–5 and 7 and 8, the same 12-trial sequence of asterisk positions was repeated 10 times (e.g. abadbcdacbdc). Subjects were not told about the repeating sequence, but asked after the last block of each session if they were aware of a repeating sequence, and if they were, to write it down. 4 versions of the SRTT were generated, each subject received each version only once in randomized order to avoid interference effects. 2.5. Reaction time task (RTT) The random stimulus control experiment was identical to the SRTT, apart from the fact that no sequences, but random stimuli were presented in each block. 2.6. Experimental course 2 h after CYC or placebo medication intake, subjects were placed on a comfortable chair in front of a computer monitor and received anodal, cathodal or sham tDCS for 10 min. Immediately after the end of stimulation, the SRTT or the RTT was conducted as described above (see Fig. 1). Performance of the motor task required between 10 and 15 min for each subject, depending on the length of the break between the blocks chosen by the subjects. The length of the break was chosen by the subjects and not pre-determined to enable subjects to have an appropriate break to keep attention constant. Subjects, but not the investigator were blinded to medication and tDCS condition. The subjects were not informed about a reverberating sequence in the learning

2.2. Pharmacological interventions 100 mg CYC or equivalent placebo (PLC) medication was administered to the subjects orally two hours before the start of each experimental session. Two hours after oral intake, CYC induces a stable plasma level (van Berckel et al., 1997) and alters the efficacy of anodal tDCS to enhance motor cortex excitability (Nitsche et al., 2004). Subjects were blinded to the respective pharmacological condition. 2.3. Transcranial direct current stimulation Current (1 mA, current density 0.029 mA/cm2 ) was induced through salinesoaked sponge electrodes (surface 35 cm2 ). tDCS was delivered by a specially developed, battery-driven constant-current stimulator (Schneider Electronic, Gleichen, Germany). Constant-current flow was controlled by an amperemeter. tDCS was delivered immediately before the motor learning experiment for 10 min. The stimulating electrode (to which the terms anodal and cathodal tDCS are applied) was placed contralaterally to the performing right hand, and the reference electrode ipsilaterally. For stimulation of the primary motor cortex, the stimulating electrode was placed above C3 (international 10–20 system) and the reference electrode above the

Fig. 1. Experimental course (SRTT). Depicted are the time-lines of the experimental procedures of the SRTT experiment. CYC or PLC medication was administered 2 h before tDCS. Anodal, cathodal or sham tDCS was performed for 10 min. Immediately afterwards, the SRTT was performed, which consisted of 8 blocks. Blocks 1 and 6 included random stimuli (r) without a specific sequence, in the remaining blocks the sequence (s) was presented. The duration of the SRTT was about 10 min, dependent on the individually determined duration of the breaks. Four different versions of the SRTT were presented to each group, the specific SRTT version presented in a medication-tDCS combination was randomized between subjects. One subject group received anodal tDCS and the respective sham conditions, the other group cathodal or sham tDCS. The principal course of the RTT experiment was identical with the exception that only random blocks were presented in the cognitive task.

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experiment. To avoid medication-, stimulation- or sequence-interference effects, a 1-week break between sessions was obligatory.

Table 1 Results of the repeated measure ANOVAs performed for the SRTT and RTT experiment

2.7. Data analysis 2.7.1. SRTT In each trial, response time (RT) was recorded from the appearance of the go signal until the first button was pushed by the subject. For each block of trials of a given experimental condition, mean RT was calculated for each subject separately, incorrect responses and response times of less than 200 ms or more than 3000 ms or those that were above 3 standard deviations of the individual subject’s mean response time were discarded. Furthermore, the standard deviation of response times for each subject in every block was calculated as an index of variability of response times. An error rate (ER) was calculated to assess the number of incorrect responses for each block and each subject in each stimulation condition. Statistical analyses were performed for the absolute values of RT, ER and variability of RT via repeated measures ANOVA (level of significance 0.05, between-subject factor tDCS polarity (anodal, cathodal), within-subject factors tDCS vs. sham stimulation, medication (CYC or placebo), and block). Additionally, RT, ER, and variability value differences between the respective tDCS/medication conditions were compared by paired samples two-tailed Student’s t-tests (level of significance 0.05) within each block of the task for a given stimulation polarity and medication condition. Since RT and ER differences between blocks 5 and 6 are thought to represent an exclusive measure of implicit learning, interactive Student’s t-tests (Cohen, 1977) were performed to compare the respective differences for the anodal/cathodal/CYC stimulation conditions on the one hand, and the sham tDCS/placebo medication condition on the other (SRTT only). Technically, the interactive t-test compares group differences of the dependent variable (here RT and ER) with regard to two different states of a factor combination (here, e.g. blocks 5 and 6 of the SRTT under placebo medication/sham stimulation vs. CYC and anodal tDCS). Thus, a significant result means that the respective differences are not identical for the factor combinations. 2.7.2. RTT For the random sequence control experiment, repeated measures ANOVAs (between-subject factor: tDCS polarity (anodal, cathodal), within-subject factors tDCS vs. sham stimulation, medication (CYC or placebo), and block) and post hoc t-tests were calculated for absolute RT, ER and variability. Critical p-values were set to 0.05 for all tests. For each ANOVA, the data were tested for multivariate normal distribution by the Mauchly-test of sphericity. When necessary, the Greenhouse-Geisser correction was applied.

3. Results 3.1. SRTT With regard to absolute response time, the ANOVA revealed a significant main effect of block. The other main effects and interactions were not significant (Table 1). This is due to a shortening of RT throughout the experiment in all medication/tDCS conditions in all blocks containing the sequence block. As revealed by the post hoc t-tests, the RT difference between blocks 5 and 6 was significant within all conditions reflecting the sequence learning. The interactive t-tests comparing sham stimulation/placebo medication on the one hand with the respective real medication/tDCS condition combinations for blocks 5 and 6 resulted in a significant difference only for the cathodal tDCS and CYC combination condition (t-value 2.612, p = 0.032). Here the response time difference between the sequence and the random block was smaller as compared to the sham tDCS/placebo medication condition. The other interactive t-tests revealed no significances (p between 0.254 and 0.912). Additionally, for the anodal tDCS/CYC condition, RTs were significantly longer as compared to the sham tDCS/placebo medication group for some sequential blocks (block 3: t-value 2.268, p = 0.033; block 7: t-value 2.161, p = 0.041; block 8: t-value 2.330, p = 0.029), as shown in Fig. 2. Baseline RT did not differ significantly between the experimental conditions. For ER and variability, the ANOVA shows significant main effects of block (ER: F = 11.767, p < 0.001; variability F = 15.794, p < 0.001), due to a reduced number of errors and less variability during performance in the later blocks, but no significant effect of tDCS or medication or interaction of these variables.

Experiment 1 (SRTT) absolute reaction time Block tDCS vs. sham Medication tDCS polarity Block × tDCS vs. sham Block × medication Block × tDCS polarity tDCS vs. sham × medication tDCS vs. sham × tDCS polarity Medication × tDCS polarity Block × tDCS vs. sham × medication Block × tDCS vs. sham × tDCS polarity Block × medication × tDCS polarity tDCS vs. sham × medication × tDCS polarity Block × tDCS vs. sham × medication × tDCS polarity Experiment 2 (RT) absolute reaction time Block tDCS vs. sham Medication tDCS polarity Block × tDCS vs. sham Block × medication Block × tDCS polarity tDCS vs. sham × medication tDCS vs. sham × tDCS polarity Medication × tDCS polarity Block × tDCS vs. sham × medication Block × tDCS vs. sham × tDCS polarity Block × medication × tDCS polarity tDCS vs. sham × medication × tDCS polarity Block × tDCS vs. sham × medication × tDCS polarity Experiment 2 (RT) errors Block tDCS vs. sham Medication tDCS polarity Block × tDCS vs. sham Block × medication Block × tDCS polarity tDCS vs. sham × medication tDCS vs. sham × tDCS polarity Medication × tDCS polarity Block × tDCS vs. sham × medication Block × tDCS vs. sham × tDCS polarity Block × medication × tDCS polarity tDCS vs. sham × medication × tDCS polarity Block × tDCS vs. sham × medication × tDCS polarity

d.f.

F

p

2.792 1 1 1 3.504 3.786 2.792 1 1 1 3.290 3.504 7 1

117.958 1.825 1.207 0.936 0.558 1.673 0.756 0.017 0.593 0.685 0.778 0.442 1.380 0.052

<0.001* 0.183 0.278 0.338 0.671 0.162 0.512 0.896 0.445 0.412 0.518 0.753 0.213 0.821

3.290

0.445

0.739

3.638 1 1 1 4.107 3.132 3.638 1 1 1 4.471 4.107 3.132 1

3.45 0.009 0.430 1.519 1.272 0.898 0.991 0.100 0.438 1.136 0.396 0.845 1.827 0.013

0.013* 0.926 0.517 0.227 0.284 0.449 0.410 0.754 0.513 0.295 0.831 0.502 0.145 0.908

4.471

1.049

0.388

5.365 1 1 1 5.523 4.845 5.365 1 1 1 5.316 5.523 4.845 1

4.477 0.709 5.545 2.092 1.453 1.480 2.100 3.239 0.054 0.085 0.725 0.197 0.694 2.834

0.001* 0.406 0.025* 0.158 0.202 0.201 0.063 0.082 0.818 0.773 0.614 0.972 0.624 0.103

5.316

2.185

0.055

For the repeated measures ANOVAs, the inner-subject factors were tDCS vs. sham stimulation, block, medication, and the between-subject factor tDCS polarity (anodal or cathodal tDCS). The asterisks mark significances (critical p-value 0.05). d.f. = degrees of freedom, F = F-value, p = probability.

Some of the subjects reported, especially after the last sessions, that they had the impression of a reverberating sequence. However, none of the subjects was able to recall the sequence or parts of it correctly in each condition. 3.2. RTT With regard to the random stimuli reaction time task, for RT the ANOVA revealed a main effect of block, but no main effect of the other variables tested or interactions (Table 1). This is due to slightly enhanced RTs during the experimental course, maybe due

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Fig. 2. SRTT performance (response time). Depicted are the mean response times (ms) for each medication/tDCS combination during learning (blocks 1–8). In blocks 1 and 6, random stimuli, and in the remaining blocks, the sequence is presented. The results show that subjects become faster during learning and recall in each condition, but that response time is significantly longer in the anodal tDCS/CYC condition as compared to the sham tDCS/placebo medication condition, especially for later sequence blocks. Moreover, the RT difference between blocks 5 and 6, which is a pure index of motor learning, is smaller for the cathodal tDCS/CYC condition as compared to sham tDCS/placebo medication, indicating impaired learning under this condition. Asterisks indicate significant deviations between sham tDCS/placebo medication and the other conditions within the respective blocks (paired, two-tailed t-tests, p < 0.05). Hash symbols indicate a significant difference of RT difference between blocks 5 and 6 with regard to the sham tDCS/placebo medication on the one hand and the remaining conditions on the other (paired, two-tailed interactive t-tests, p < 0.05). Vertical bars depict standard error of mean (S.E.).

to variability of attention (Fig. 3). For ER, the main effects of block and medication were significant, and the interaction between block and polarity and the 4-way interaction between all variables tested showed a respective trend (Table 1). This is caused by a reduction of errors – in relation to the placebo medication/sham tDCS condition – under CYC (anodal condition only, block 1: t-value 2.883, p = 0.011; block 2: t-value 2.203, p = 0.044; block 7: t-value 2.751, p = 0.015), anodal tDCS (block 1: t-value 2.224, p = 0.042) and the combination of cathodal tDCS with CYC (block 3: t-value 4.156, p = 0.001) (Fig. 4). However, this effect was significant only for some blocks. The ANOVA performed for variability revealed a significant main effect for block (F = 2.860, p < 0.007), but no other significances. 4. Discussion Homeostatic plasticity is suggested to control for the amount and direction of neuroplastic cortical network modification to avoid de-stabilization. The relevance of homeostatic influences on cortical plasticity in humans has so far only been confirmed neurophysiologically. Here, we explored the impact of homeostatic plasticity on motor learning in healthy humans. The results of our

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Fig. 3. RTT (response time). Depicted are the mean absolute RT (ms) for each medication/tDCS combination during performance of the random sequences. The results show no clear trend for a reduction of RT during the course of the experiment, but a slight increase of RT, which might be due to attentional shifts. Additionally, a nonsignificant trend for diminished RT under CYC in the cathodal tDCS subjects group can be noticed. This trend however was not replicated for the anodal tDCS group. Vertical bars depict standard error of mean (S.E.).

study are in favor for a limited effect. Selectively, an excitability enhancement induced by combined anodal tDCS and CYC medication reduced subsequent learning in accordance with homeostatic plasticity rules. Anodal tDCS alone, however, in discrepancy to former neurophysiological experiments, did not alter learning in any direction. Moreover, excitability diminution by cathodal tDCS prior to motor learning, if combined with the partial NMDA receptoragonist CYC, did not improve, as predicted by homeostatic plasticity rules, but impair performance. These effects were specific for the sequential blocks and thus for learning. Random block RT, and thus learning-independent behavior, was not influenced by prior excitability modulation. Our findings therefore are only in partial accordance with the proposed impact of homeostatic plasticity on motor learning in humans.

4.1. Impact of preconditioning excitability modulation on sequential motor learning The results of our study show that prior excitability-enhancing anodal tDCS slows down response time in the SRTT, when combined with the partial NMDA receptor-agonist CYC. This effect is significant only for the sequence blocks. However, since the interactive t-test (comparing sequence block 5 and random block 6) reveal no significant difference between anodal tDCS/CYC and the sham tDCS/placebo medication condition, it has to be considered to be relatively minor. A learning-independent effect on performance modulation, however, is ruled out by the missing influence of this medication/tDCS combination on RT in the RTT (see below). Anodal tDCS alone did not modify performance in any direction.

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Fig. 4. RTT (error counts). Depicted are the mean error counts for each medication/tDCS combination during performance of the random sequences. The results show no clear trend for a reduction of errors during the course of the experiment. However, in the anodal tDCS group, CYC and anodal stimulation – but not the combination of both – reduce errors in single blocks, while in the cathodal tDCS group, the combination of tDCS and CYC reduces errors in one block. These results favor a slight positive effect of CYC on performance. Asterisks indicate significant deviations between sham tDCS/placebo medication and the other conditions within the respective blocks (paired, two-tailed t-tests, p < 0.05). Vertical bars depict standard error of mean (S.E.).

This is in contrast to the neurophysiological studies in homeostatic plasticity, combining tDCS and rTMS (Lang et al., 2004; Siebner et al., 2004), where anodal tDCS alone did suffice to induce homeostatic effects. In the present study the tDCS-induced excitability-enhancement had to be further enhanced by CYC to be effective. This could be indicative for a dependency of the induction of homeostatic plasticity on the exact amount of preconditioning activity, which might differ for specific tasks. While these results are in principal accordance with mechanisms of homeostatic plasticity, they, at least at first sight, differ in part from prior behavioral studies. In a study in chronic stroke patients anodal tDCS of the primary motor cortex, which started before task performance, improved task performance (Fregni et al., 2005; Hummel et al., 2005). In this task, however, tDCS continued during task performance, and thus was not restricted to preconditioning stimulation. Thus, simultaneous task performance and anodal tDCS, which has been demonstrated to improve task performance in another study (Nitsche, Schauenburg, et al., 2003), might have caused the effect. Also pharmacological intervention with excitabilityenhancing drugs has been shown to improve task performance. Here, medication is usually applied before task performance, which might be thought to induce homeostatic effects, but is administered in dosages which on their own do not cause major cortical

excitability changes (Meintzschel & Ziemann, 2006). Moreover, the tasks are performed during peak dose concentration of the respective drugs. Thus, any resulting excitability alteration is most probably task-related and thus does not encompass a change of pretask excitability, which might explain the absence of homeostatic effects. A similar argument might apply for a non-homeostatic effect of excitability-enhancing ischemic nerve block on motor practice (Ziemann, Muellbacher, Hallett, & Cohen, 2001). Also here the nerve block was induced before, but still present during task performance. All in all, the pattern of results of the different behavioral studies are in favor for a critical importance of an excitability enhancement induced before task performance to induce homeostatic effects. Cathodal tDCS administered prior to motor learning also impaired learning in our study, but only if combined with CYC. This effect is also specific for the learned sequence, since RTs in the RTT were not compromised by this medication/tDCS combination, and is clearly not in accordance with homeostatic plasticity rules. At first sight, one might assume that this deleterious effect of the combined pharmacological-tDCS intervention might be attributed to the impact of CYC on motor learning; however, this is improbable because CYC alone did not influence SRTT performance. One possible explanation is that cathodal tDCS did not suppress the activation of “wrong responses” during learning sufficiently, thus that CYC in this case – given that cathodal tDCS decreases the strengthening of learning-related synapses – would strengthen not only correct, but also false responses. In accordance with this hypothesis, cathodal tDCS, when administered during SRTT performance, failed to impair performance in a former study (Nitsche, Schauenburg, et al., 2003). Conversely, inhibitory 1 Hz rTMS worsened motor learning in a study of another group (Muellbacher et al., 2002), maybe due to a larger inhibitory effect. Alternatively, one could argue that our healthy subjects were already performing at an optimum level without medication or stimulation, and hence no intervention would have been able to improve performance. This seems unlikely, since in another study with similar subject characteristics, performance was indeed improved when tDCS was administered during performance (Nitsche, Schauenburg, et al., 2003). These results of the former study are also ruling out the argument that tDCS generally disturbs motor learning, and thus an unspecific effect of tDCS on learning. On the contrary, they are in favor for a specific timingdependent effect of tDCS on performance, in partial accordance with homeostatic plasticity rules. Interestingly, implicit motor learning was nearly at a maximum level – as shown by the RT – during the first sequential block (block 2) in all conditions. However, slight shortenings of RT can be seen also in later blocks. This relatively fast learning process might be caused by the fact that young subjects and mainly students were recruited as subjects. A similar pattern of results appeared in a former study of our group (Nitsche, Schauenburg, et al., 2003). Also similar to the results in this former study, only some of the subjects had the impression of a reverberating sequence, especially with regard to the later sessions, but no subject was able to actually report the actual sequence, in accordance with implicit, but not explicit motor learning. 4.2. Impact of preconditioning excitability modulation on reaction time task performance The results of the RTT show that tDCS of either polarity, as well as CYC and any combination of these interventions, do not modify RT significantly, if applied before RTT performance. There is a trend for CYC medication to reduce RT, especially in the cathodal tDCS group, which however is not replicated for the other subject group, and thus most probably is due to chance. The missing reduction of

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RT during time course, which has been found in other studies using the same protocol and can be dedicated to increasing task routine (Nitsche, Schauenburg, et al., 2003) is most probably caused by the multiple sessions conducted in randomized order in the present experiment and thus due to a ceiling effect. In any case, ER was slightly, but significantly reduced in single blocks for anodal tDCS, CYC medication and the combination of cathodal tDCS and CYC as compared to sham stimulation/placebo medication. This might be due to a benefit from a general network excitability enhancement, as delivered by anodal tDCS and CYC, or by increasing task-related excitability in a relatively silent cortical network, as delivered by the combination of cathodal tDCS with CYC—both of which might have helped the subject to choose the correct key press by increasing flexibility in this task. Clearly, tDCS and CYC did not modify performance in a direction compatible with homeostatic mechanisms. 4.3. General remarks Taken altogether, the results of this study do argue for a limited impact of homeostatic plasticity on motor learning, as tested here. The result compatible with a homeostatic effect is a diminution of motor learning by the combination of CYC and excitabilityenhancing anodal tDCS applied before learning. However, motor learning was not improved by homeostatic regulations following cathodal tDCS combined with CYC, which had been hypothesized if homeostatic plasticity were functionally relevant in this condition. Interestingly, for the RTT, there is no clear indication that homeostatic effects improved performance. Conversely, here a pharmacologically or tDCS-induced excitability-enhancement was slightly beneficial. This pattern of results shows that (a) the impact of homeostatic plasticity on behavior was restricted to learning, which is supposed to involve LTP-like processes, but does not generalize to learning-independent behavior and (b) that, at least in this study, homeostatic plasticity does not fully account for the impact of prior excitability modulation on learning. When compared with neurophysiological studies on homeostatic plasticity, the behavioral results are not in complete accordance, since preconditioning with anodal and cathodal tDCS determined the direction of plasticity induced by repetitive transcranial magnetic stimulation homeostatically (Lang et al., 2004; Siebner et al., 2004). This indicates that a simple transfer of neurophysiological data regarding homeostatic influences on LTP-like plasticity to learning mechanisms does not seem likely. Since rTMS might differ relevantly from learning-related plasticity, in another study, we explored the impact of preconditioning tDCS on associative plasticity, as induced by paired associative stimulation (PAS), which might be more closely linked to learning processes (Stefan et al., 2006; Ziemann et al., 2004). Here, excitability-enhancing tDCS boosted the efficacy of the subsequent PAS protocol, while excitability-diminishing tDCS resulted in reverse effects (Nitsche, Roth, et al., 2007). Also these results do not fit well with those accomplished with tDCS prior to SRTT performance. It might thus be argued that the plasticity-inducing protocols used in the purely neurophysiological studies do not mimic learning processes closely enough, and that the induction of homeostatic plasticity depends on the kind of plasticity generated. Specifically, the reason for this could be that any homeostatic effect on learning is critically dependent on the condition that only the excitability of learning-related synapses is modified by preconditioning stimulation, i.e. a functionally synapse-specific kind of homeostatic plasticity. This is clearly not the case for tDCS, which due to its relatively large electrode size is relatively non-focal. However, this might also need to be taken into account for related non-invasive cortical stimulation

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techniques. This non-focal stimulation could – for example via lateral inhibition and other mechanisms – diminish the impact of the preconditioning stimulation on the excitability of learning-related synapses. Thus, the results of our study do not exclude a relevant influence of homeostatic effects on learning in general, but show that homeostatic mechanisms explored on the neurophysiological level by techniques inducing effects not restricted to neurons involved in task performance, cannot be simply transferred to the behavioral level. Moreover, the results of this study show that an excitability modulation prior to performance of a motor task might be less suited to improve motor learning than tDCS administered during learning or motor behavior. In a former study, we applied anodal or cathodal tDCS during the same tasks as in the current study. There, excitability-enhancing anodal tDCS improved both motor learning in the SRTT and motor behavior in the RTT (Nitsche, Schauenburg, et al., 2003). The reason for this divergent result might be that during tDCS not only NMDA receptors, but also calcium channels are modulated, while the after-effects of tDCS are achieved by modifications of NMDA receptors alone (Nitsche, Fricke, et al., 2003). Since intracellular calcium concentration is important for LTP induction (Canepari, Djurisic, & Zecevic, 2007), enhanced transmembrane calcium conduction, as probably achieved during anodal tDCS, might improve learning processes. Conversely, a pure modulation of synaptic strength prior to learning might compromise performance, due to a homeostatic or defocusing effects. Therefore, the results of this study favor administering tDCS during, and not before, learning to optimize performance. Moreover, the results of this study imply that for neurorehabilitative purposes tDCS should be performed always during and not before physical therapy. CYC, a partial NMDA receptor-agonist, has been promoted as a putative cognitive enhancer in recent years. Indeed this drug has been demonstrated to improve cognition in Alzheimer’s patients in some pilot studies (Tsai, Falk, & Gunther 1998; Tsai, Falk, Gunther, & Coyle, 1999). In our study with healthy subjects, however, CYC alone was without effect on motor learning, and deteriorated performance when combined with tDCS before learning. This pattern of results argues against a relevant positive effect of CYC on learning in healthy subjects. There might be a slight positive effect on learning-independent motor behavior however, as shown by the reduced error count in the RTT under CYC, but this effect was discrete. Since CYC as applied in our study was shown to modulate neurophysiologically induced neuroplasticity prominently in healthy subjects, it is improbable that this minor effect was caused by an insufficient dosage of the medication (Nitsche et al., 2004). Taken together, the results of the current study are in support for a minor role of homeostatic plasticity in modulating learning in healthy human subjects. They also favor a partial dissociation between neurophysiologically induced metaplasticity and behavioral consequences. Since it is possible that homeostatic mechanisms differ for the specific kinds of neuroplasticity induced, more studies are needed to explore this topic systematically. Acknowledgements This project was supported by the CNS—Hannelore Kohl Foundation, and the BMBF, Bernstein-Center for Computational Neuroscience, Goettingen. References Abbott, L. F., & Nelson, S. B. (2000). Synaptic plasticity: Taming the beast. Nature Neuroscience, 3(Suppl.), 1178–1183. Abraham, W. C., & Tate, W. P. (1997). Metaplasticity: A new vista across the field of synaptic plasticity. Progress in Neurobiology, 52, 303–323.

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