SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

Alleviating the symptoms of neurological diseases by increasing cortical excitability through transcranial stimulation is an ongoing scientific challenge. Here, we tackle this issue by interfering with high frequency oscillations (80–250 Hz) via external application of transcranial alternating current stimulation (tACS) over the human motor cortex (M1). Twenty-one subjects participated in three different experimental studies and they received on separate days tACS at three frequencies (80 Hz, 140 Hz and 250 Hz) and sham stimulation in a randomized order. tACS with 140 Hz frequency increased M1 excitability as measured by transcranial magnetic stimulation-generated motor evoked potentials (MEPs) during and for up to 1 h after stimulation. Control experiments with sham and 80 Hz stimulation were without any effect, and 250 Hz stimulation was less efficient with a delayed excitability induction and reduced duration. After-effects elicited by 140 Hz stimulation were robust against inversion of test MEP amplitudes seen normally under activation. Stimulation at 140 Hz reduced short interval intracortical inhibition, but left intracortical facilitation, long interval cortical inhibition and cortical silent period unchanged. Implicit motor learning was not facilitated by 140 Hz stimulation. High frequency stimulation in the ripple range is a new promising non-invasive brain stimulation protocol to increase human cortical excitability during and after the end of stimulation.

Abbreviations 
AMT

active motor thresholds

CSP

cortical silent period

EMG

electromyogram

FDI

first dorsal interosseous muscle

ICF

intracortical facilitation

iTBS

intermittent theta burst stimulation

M1

primary motor cortex

MEP

motor evoked potential

PAS

paired associative stimulation

PPTMS

paired-pulse transcranial magnetic stimulation

RMT

resting motor threshold

SICI

short intracortical inhibition

SRTT

serial reaction time task

tACS

transcranial alternating current stimulation

tDCS

transcranial direct current stimulation

TMS

transcranial magnetic stimulation

tRNS

transcranial random noise stimulation

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

Specific linkages have been drawn between neuronal oscillations in defined frequency bands and a variety of cognitive functions and sensory selection (for a recent review see: Schroeder & Lakatos, 2009). One subgroup of high frequency oscillations are known as ‘ripples’, a term that generally refers to oscillations occurring at about 80–200 Hz. This subgroup has been well described in the hippocampus and parahippocampal structures and plays a key role both in normal behaviours and abnormal brain functions such as epilepsy (Buzsaki et al. 1992; Ylinen et al. 1995; Grenier et al. 2001, 2003; Diba & Buzsaki, 2007; Middleton et al. 2008; Engel et al. 2009).

Another subset, named ‘fast ripples’, comprises oscillations from 250 to 500 Hz, and has been proposed as a bio-marker of epileptic tissue (Bragin et al. 1999; Jacobs et al. 2009). These fast ripples have been recorded also in healthy neocortex but not in normal hippocampus and parahippocampal structures (Engel et al. 2009). Some cortical neurons are able to generate even higher frequencies of up to 800 Hz (Steriade et al. 1993; Amassian & Stewart, 2003).

So far interest in human oscillatory non-invasive brain stimulation has mainly focused on the traditional EEG frequency bands (Kanai et al. 2008; Pogosyan et al. 2009) and on higher gamma oscillations targeting aspects of cortical binding (Singer, 2009). Expanding transcranial stimulation frequencies in the range above 100 Hz is expected to be of importance to engender research in several directions. It represents a further step towards more targeted plasticity modulating protocols and also may have important implications for neurological disease accompanied by pathological oscillations and motor deficits. Interestingly frequencies in the ripple range are intensively used in deep brain stimulation for treatment of Parkinson's disease. Direct frequency-dependent effects of 120–130 Hz on afferents to the subthalamic nucleus region have become a major direct target of deep brain stimulation in PD (Hammond et al. 2007; Gradinaru et al. 2009). Here we modulate motor cortex excitability by transcranial high frequency alternating current stimulation (tACS) with a frequency of 140 Hz which is close to this frequency and is in the middle of the low ripple frequency range.

As control conditions we explored the effects of 80 and 250 Hz oscillations on motor cortex excitability. These frequencies represent the lower and higher border of the ripple range, and therefore we hypothesized that tACS stimulation with these frequencies would be less effective for changing cortical excitability than applying 140 Hz stimulation. Furthermore, in a recent study it was described that frequencies below 100 Hz did not modify intracortical and corticospinal excitability in a random noise stimulation protocol (Terney et al. 2008).

For evaluating cortical excitability changes we applied several transcranial magnetic stimulation (TMS) protocols that are known to test the functions and integrity of specific cortical circuits in the human motor network. The change in amplitude of the motor evoked potential (MEP) elicited by single pulse TMS represents the global change of corticospinal excitability in the motor system. As global parameters of cortico-spinal excitability we measured the input–output (I-O) curve and motor thresholds (Chen, 2000; Abbruzzese & Trompetto, 2002). Short intracortical inhibition (SICI) and facilitation (ICF) were studied using a paired-pulse stimulation protocol (Kujirai et al. 1993). Here a subthreshold TMS stimulus (conditioning pulse) was followed by a suprathreshold test stimulus. The resulting increase or decrease of the MEP amplitude elicited by the test stimulus is determined by the interstimulus interval (ISI): short ISIs (2 and 4 ms) and long ISIs (7, 9 and 12 ms). Furthermore we measured the long interval cortical inhibition (LICI) with two suprathreshold stimuli applied with 50, 100 and 150 ms stimulation intervals, (Valls-Sole et al. 1992). We also measured cortical silent period (CSP), which is commonly used to measure cortical and spinal inhibitory functions (Fuhr et al. 1991; Paulus et al. 2008).

In addition, we studied plastic after-effect changes under muscular activation in comparison to the effects in rest. Both abolition (Huang et al. 2008b) and reversal (Antal et al. 2007; Terney et al. 2008) of motor cortical excitability changes, induced by either intermittent theta burst stimulation (iTBS) (Huang et al. 2008b), transcranial direct current stimulation (tDCS) (Antal et al. 2007) or transcranial random noise stimulation (tRNS) (Terney et al. 2008), have been described under activation. Here we show that ripple stimulation after-effects are comparatively robust after switching the innervation state of the target muscle from rest to activation.

Furthermore, a behavioural task was used to study ripple oscillation-driven changes in performance during a variant of the serial reaction time task (SRTT) (Nissen & Bullemer, 1987), which is a standard protocol to test implicit motor learning.

We hypothesized that externally applied high frequency oscillation in the ripple range will interfere with ongoing oscillations and neuronal activity in the brain and therefore result in significant changes of cortical and corticospinal excitability.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

The study conformed to the Declaration of Helsinki, and the experimental protocol was approved by the Ethics Committee of the University of Göttingen.

Subjects

In total 21 subjects (age 25.9 ± 2.35 S.D. years, range: 23–30 years) participated in this study (for details see Table 1). All subjects were right handed, according to the Edinburgh handedness inventory (Oldfield, 1971), and they were naive with regard to the aim of the study. Those who were ill, pregnant, suffering from drug abuse, or had metallic implants/implanted electrical devices were excluded by an interview and a short physical examination. All gave written informed consent. Subjects, but not the investigator, were blinded for stimulation conditions in all of the studies.

Table 1.  Stimulations protocols, electrode sizes, subjects’ characteristics and baseline values for the performed experiments
ExperimentMeasurementElectrode sizeAC stimulated muscleNumber of subjectsBaseline (single TMS) and test pulse (ppTMS) amplitudes (mV) ±s.e.m.Sex: (f/m)
  1. Baseline MEP amplitude means of about 1 mV were calculated for each experimental condition. The single test-pulse TMS intensity was adjusted to achieve a baseline MEP of SI1mV, and re-adjusted during the respective stimulation protocol if needed, to compensate for effects of global excitability changes on test-pulse amplitude. They did not differ between the respective conditions (Student's t test, P < 0.05). f, female; m, male; R, reference electrode (frontopolar); S, motor cortex stimulation electrode; FDI, first dorsal interosseous muscle.

Experiment 1Single pulseS: 16 cm2; R:Right FDISham: 120.99 ± 0.026/6
tAC stimulationTMS84 cm2 80 Hz: 80.95 ± 0.033/5
under complete   140 Hz: 121.01 ± 0.036/6
muscle relaxation   250 Hz: 81.06 ± 0.033/5
I-O, SICI/ICF,S: 16 cm2; R:Right FDISham: 91.03 ± 0.04 
LICI, CSP84 cm2 80 Hz: 90.98 ± 0.035/4
   140 Hz: 90.99 ± 0.02 
   250 Hz: 91.00 ± 0.03 
 
Experiment 2Single pulseS: 16 cm2; R:Right FDISham: 91.01 ± 0.02 
tAC stimulationTMS84 m2 80 Hz: 91.00 ± 0.026/3
under motor   140 Hz: 91.03 ± 0.03 
activation   250 Hz: 91.00 ± 0.03 
 
Experiment 3 S: 16 cm2; R:  Sham: 13 
Behavioural studies84 cm2   80 Hz: 135/8
(SRTT)    140 Hz: 13 
    250 Hz: 13 

Electrical stimulation of the motor cortex

Electrical stimulation was delivered by a battery-driven stimulator (NeuroConn GmbH, Ilmenau, Germany). tACS was applied for 10 min with a current intensity of 1000 μA. The waveform of the stimulation was sinusoidal without DC offset. The current was ramped up and down over the first and last 5 s of stimulation. For sham stimulation, the current was turned on for 5 s at the beginning and 5 s at the end of the stimulation. Since high frequency oscillations in the ‘ripple’ range did not induce a flickering sensation, subjects were kept blinded with regard to the type of the experiment.

The stimulating electrodes were attached to the scalp using electrode Ten20 EEG conductive paste. They were further fixed with a rubber band placed over the electrode and attached under the chin. This reduced electrode impedance and prevented movement of the electrodes during the experiment. Sufficient cream ensured low impedance during the stimulation time. The impedance was kept at <5 kΩ. The reference electrode was placed in a saline soaked sponge. To increase the focality of the stimulation, the electrode size was 4 × 4 cm whereas the reference electrode size at the forehead was 14 × 6 cm. In each experiment, the motor-cortical electrode was fixed over the representational field of right first dorsal interosseous (FDI), as identified by TMS.

Measurement of motor system excitability

To detect stimulation-driven changes of excitability, MEPs of the motor cortical representation of the right FDI were recorded during and following stimulation. The site of the stimulation was determined using single pulse TMS. MEPs were elicited using a Magstim 200 magnetic stimulator (Magstim Company, Whiteland, Wales, UK) with a figure-of-eight standard double magnetic coil (diameter of one winding, 70 mm; peak magnetic field, 2.2 T; average inductance, 16.35 μH). The coil was held tangentially to the skull, with the handle pointing backwards and laterally at 45 deg from the midline, resulting in a posterior–anterior direction of current flow in the brain. The coil was connected to two monophasic Magstim 200 stimulators via a bistim module during the paired-pulse TMS study. Surface EMG was recorded from the right FDI through a pair of Ag–AgCl surface electrodes in a belly-tendon montage. Raw signals were amplified, band-pass filtered (2 Hz to 2 kHz; sampling rate, 5 kHz), digitized with a micro 1401 AD converter (Cambridge Electronic Design, Cambridge, UK) controlled by Signal Software (Cambridge Electronic Design, version 2.13), and stored on a personal computer for off-line analysis. The FDI ‘hotspot’ was defined as the site where TMS resulted consistently in the largest MEP in the resting muscle.

For single pulse TMS studies in experiment 1, the TMS coil was placed over the electrode/rubber support band montage and TMS stimulation intensity was adjusted to achieve a baseline MEP of about 1 mV.

Experimental design

Subjects participated in three different experimental studies and they received on separate days tACS (80 Hz, 140 Hz and 250 Hz) and sham stimulations. The order of the stimulations with regard to all experiments occurred in a counterbalanced fashion.

Experiment 1. tAC stimulation under relaxed condition

Single pulse TMS study Twelve healthy volunteers participated in this study. All of them took part in the sham and 140 Hz stimulation experiments, while eight subjects participated in studies performed with 80 and 250 Hz.

The experiments were performed with at least 5 days in between and at the same time of the day for each subject.

tAC stimulation was performed under complete relaxation, which was controlled through visual feedback of electromyogram (EMG) activity. During stimulation we have recorded TMS elicited MEPs. Twenty single test-pulse MEPs were recorded at 0, 5 and 10 min after stimulation and then every 10 min up to 60 min.

The study with regard to I-O curve, SICI/ICF, LICI, CSP protocols To explore the origin of the excitability modulation in more detail, we measured the input–output curve and motor thresholds as global parameters of cortico-spinal excitability, and determined short intracortical inhibition and intracortical facilitation as well as long interval cortical inhibition and cortical silent period. Nine subjects participated in four experimental sessions on separate days. Stimulus intensities (as a percentage of maximal stimulator output) of TMS were determined at the beginning of each experiment. SI1mV (the intensity required to evoke MEPs of ∼ 1 mV peak-to-peak amplitude) was determined with single-pulse TMS first (the amplitude of the test MEP was matched before and after tACS).

Motor threshold determination

The rest motor threshold (RMT) was determined as the minimum stimulator output needed to produce a response of at least 50 μV in the relaxed FDI in at least 3 of 6 consecutive trials. The active motor threshold (AMT) was defined as the lowest stimulus intensity at which 5 out of 10 consecutive stimuli elicited reliable MEPs (above 200 μV in amplitude) during isometric contraction of the contralateral FDI muscle (Rothwell et al. 1999) in at least 3 of 6 recordings.

Input–output curve

I-O curve were measured with three different and increasing stimulus intensities (110%, 130% and 150% of RMT), each with 10 pulses. A mean was calculated for all intensities.

Short intracortical inhibition and facilitation

For SICI/ICF, two magnetic stimuli were given through the same stimulating coil, and the effect of the first (conditioning) stimulus on the second (test) stimulus was investigated (Kujirai et al. 1993). To avoid any floor or ceiling effect, the intensity of the conditioning stimulus was set to a relatively low value of 80% of AMT. The single test-pulse TMS intensity was adjusted to achieve a baseline MEP of SI1mV, and re-adjusted during the respective stimulation protocols, to compensate for effects of global excitability changes on test-pulse amplitude caused by tACS. SICI was taken as the mean percentage of inhibition at ISIs of 2 and 4 ms, whereas ICF was taken as the mean facilitation at ISIs of 7, 9 and 12 ms.

The control condition (test pulse alone) was tested 20 times, and each of the conditioning-test stimuli 10 times. The mean peak-to-peak amplitude of the conditioned MEP at each ISI was expressed as a percentage of the mean peak-to-peak size of the unconditioned test pulse.

Long intracortical inhibition

We tested LICI with two suprathreshold stimuli applied with ISIs of 50, 100, 150 and 200 ms (Valls-Sole et al. 1992). The intensity of both stimuli was set to 110% of RMT. Here as well, the intensity was set to this relatively low value to avoid any floor or ceiling effect. The control condition (first pulse alone) was tested 20 times, whereas each of the paired stimuli was tested 10 times. LICI was taken as the mean percentage inhibition of conditioned MEP at ISIs of 50, 100, 150 and 200 ms.

Cortical silent period

Ten pulses with SI1mV and 10 pulses with 120% RMT were applied under tonic contraction of the right FDI muscle. The subjects had to squeeze a ball with a size of 8 cm connected to a display on which the actual pressure values of the ball were quantified. They were instructed to maintain a voluntary contraction of about 20% of maximum voluntary force using visual feedback. CSPs were separately determined; in rectified and averaged EMG traces with a prestimulus period of 100 ms. CSP (in ms) was measured from the TMS stimulus to the point where the signal reached the amplitude of the mean prestimulus EMG activity.

Experiment 2. Motor task-related modulation of different frequency tACS

Single pulse TMS study In this experiment nine subjects were instructed to squeeze a ball (8 cm diameter) in their right hand during tACS. The ball was connected to a display where the actual values related to pressure were quantified. Before the stimulation session, the subjects were asked to push the ball as hard as possible. During the tACS session, subjects had to squeeze the ball to half-maximal contraction as previously shown. Due to EMG contamination during squeezing we confined our measurements of MEP responses to the relaxed state after tACS; 20 single test-pulse MEPs were recorded at 0, 5 and 10 min after stimulation and then every 10 min up to 60 min.

Experiment 3. Behavioural studies (SRTT)

Thirteen subjects participated in the behavioural experiment. All subjects received sham, 80 Hz, 140 Hz and 250 Hz stimulation in different sessions separated by at least 1 week to prevent carryover effects of task learning and stimulation. The order of the different stimulation conditions was randomized between subjects and they received different sequences for SRTT. Subjects were seated in front of a computer screen at eye level behind a response pad with four buttons numbered 1–4 and 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 four 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 asterisk as fast as possible. After a button was pushed, the go signal disappeared. The next go signal was displayed 500 ms later. The test consisted of eight blocks of 120 trials. In blocks 1 and 6, the sequence of asterisks followed a pseudorandom 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, 7 and 8, the same 12-trial sequence of asterisk positions was repeated 10 times. Subjects were not informed about the repeating sequence.

Analysis and statistics

In the first stage of analysis, the power analysis was conducted for each experiment separately using the Statistica software 7.1 (StatSoft Inc., Tulsa, OK, USA). According to the mean difference in MEP amplitudes between the sham and tACS treated groups based on preliminary studies, n > 7 at each group is sufficient to detect the relevant difference with 80% power at an α level of 0.05 (two-sided) using repeated measures ANOVA.

Single pulse TMS studies First the TMS intensity resulting in MEP amplitudes of 1 mV was established. The baseline of TMS-evoked MEPs (20 stimuli) was recorded at 0.25 Hz before the stimulation. 20 single test-pulse MEPs were recorded at 0, 5 and 10 min after stimulation and then every 10 min up to 60 min. In experiment 1 (Single pulse TMS studies) the MEPs measured during tACS were analysed in successive groups of 15, each covering a time range of 1 min, and the means for each group were calculated.

In the first experiment a repeated measures ANOVA with the within subject factor time, the inbetween subject factor tACS, and the dependent variable MEP amplitude has been used (TYPE OF STIMULATION4 levels× TIME19 levels, independent variables time course before, during and after electrical stimulation and frequency of stimulation; dependent variable MEP amplitude).

In Experiment 2 a repeated measures ANOVA was performed with TYPE OF STIMULATION4 levels× TIME9 levels (independent variables: time course before and after electrical stimulation and frequency of stimulation; dependent variable: MEP amplitude). In the case of a significant main effect of TYPE OF STIMULATION or the interaction of TIME and TYPE OF STIMULATION, Fisher's least significant difference (LSD) test was performed.

The study with regard to I-O curve and SICI/ICF, LICI and CSP protocols First intra-individual MEP amplitudes means were calculated for the TMS stimulation conditions, TMS intensity with regard to I-O curve and CSP and ISI with regard to SICI/ICF and LICI. For paired-pulse stimulation protocols, the resulting means were standardized to the respective single-pulse condition. Then inter-individual means were calculated for each condition. In order to determine significant changes related to a given stimulation condition, repeated-measures ANOVAs were performed, entering four level ANOVA; independent variables: ISI/stimulation intensities and type of stimulation, dependent variable: MEP amplitude. In the case of a significant type of stimulation or interaction between ISI/intensity and type of stimulation, Fisher's LSD test was performed.

Implicit learning Concerning the implicit learning (Experiment 3) statistical analysis was performed using repeated measures ANOVA (type of stimulation × 8 blocks) for reaction time (RT), error rate (ER), and variability. Because the RT and ER differences between Blocks 5 and 6 are thought to represent an exclusive measure of implicit learning, an interactive Student's t test was performed to compare the respective differences for the tAC stimulation condition versus sham condition. An ER was calculated to assess the number of incorrect responses for each block and each subject in each stimulation condition.

Safety aspects

All subjects completed a questionnaire, which contained rating scales regarding the presence and severity of headache, difficulties in concentrating, acute mood changes, and any discomforting sensation like pain, tingling, itching or burning under the electrodes, during and after stimulation. None of them reported any side effects. In a previous study, Terney et al. (2008) showed that the concentration of the serum neuron-specific enolase (NSE), a sensitive marker of neuronal damage, was unchanged after tRNS. In the present study we used frequencies from 80 to 250 Hz, which are in the range of 0–640 Hz.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

Experiment 1. tAC stimulation under complete muscle relaxation

Single pulse TMS study The repeated measures of ANOVA revealed a significant main effects of TYPE OF STIMULATION (F3.36= 14.64, P < 0.0001) and TIME (F18.65= 5.07, P < 0.0001). The interaction between TYPE OF STIMULATION and TIME was also significant (F54.65= 2.41, P < 0.0001).

The most important finding of this experiment was that when 140 Hz tACS was applied to the M1, cortical excitability increased up to 44% above baseline. According to Fisher's LSD test, significantly increased MEPs were observed with 140 Hz tACS between 2 min and 10 min during stimulation (ST2-ST10) and post-stimulation up to 60 min (PST0–PST60) compared to sham stimulation (P < 0.005). We compare MEP amplitudes at the single time points during and post-stimulation with baseline MEP amplitudes. tACS of 140 Hz applied with 1 mA intensity induced a significant elevation in MEP amplitude compared to baseline at the time points ST2–ST10 and PST0–PST60 (Fisher's LSD, P < 0.005). See Fig. 1A.

image

Figure 1. tAC stimulation under complete muscle relaxation A, 140 Hz AC stimulation significantly increased MEPs at the ST2–ST10 and PST0–PST60 time points compared to the sham stimulation (*P < 0.05). B, controls by sham and 80 Hz stimulation were without any effect. C, 250 Hz AC stimulation significantly increased MEPs at the ST6–ST10 and PST0–PST5. The figure shows mean amplitudes of MEPs and their s.e.m. during 10 min and after tAC stimulation up to 60 min. Filled symbols indicate significant deviations of the during- and post-measurements of MEP amplitudes from baseline values; *P < 0.05. D, recalculated data of A, B and C in order to sum up the 1 mA tACS induced effects on cortical excitability. Different frequencies show different behaviours. Using 140 Hz stimulation MEP amplitudes increased most. Post hoc tests showed that the 140 Hz tACS applied with 1 mA intensity induced a significant elevation in MEP compared to 80 Hz and 250 Hz stimulation (Fisher's LSD test, P < 0.05). Error bars indicate s.e.m. The bar graphs show the MEP value from ST1 to PST60. *P < 0.05.

Download figure to PowerPoint

In contrast to the effect of 140 Hz stimulation, 80 Hz AC stimulation did not modify the MEP amplitudes significantly, when compared with sham stimulation. See Fig. 1B.

According to Fisher's LSD analysis, 250 Hz AC stimulation induced a significant increase of MEPs compared to the sham stimulation at time points ST6–ST10 (P < 0.005) and PST0–PST5 (P < 0.005). This short-duration facilitation was followed by a decline in excitation back to baseline. Compared to baseline, MEPs were increased at the time points PST6–PST10 (P= 0.02) and PST0–PST5 (Fisher's LSD, P < 0.05). See Fig. 1C.

Post hoc tests showed that the 140 Hz tACS applied with 1 mA intensity induced a significant elevation in MEP compared to 80 Hz and 250 Hz stimulation (Fisher's LSD, P < 0.05), while 250 Hz did not modify MEP amplitudes significantly when we compared with 80 Hz stimulation. See Fig. 1D.

The study with regard to I-O curve and SICI/ICF, LICI and CSP protocolsInput–output curve. As shown in Fig. 2, 140 Hz tACS increased the slope of the I–O curve. Controls by sham, 80 and 250 Hz stimulation were without any effect. The repeated measures of ANOVA revealed a significant main effects of TYPE OF STIMULATION (F3.24= 3.73, P= 0.02) and INTENSITY (F2.16= 39.10, P < 0.01). The interaction between TYPE OF STIMULATION and INTENSITY was not significant (F6.48= 1.11, P= 0.4).

image

Figure 2. tACS of 140 Hz under complete muscle relaxation shifts the slope of the input–output curve The MEP amplitudes (means ±s.e.m.) at 110, 130 and 150% of resting MT (RMT) are shown for sham, 80, 140 and 250 Hz tAC stimulations. *P < 0.05, Fisher's LSD test.

Download figure to PowerPoint

Short intracortical inhibition and facilitation. The ANOVA revealed a significant effect of TYPE OF STIMULATION (F3.24= 3.15, P= 0.04). However, the interaction between TYPE OF STIMULATION and ISI was not significant (F3.24= 0.63, P= 0.6).

According to the post hoc analysis, MEPs were significantly less decreased at ISI of 2 and 4 ms after 140 Hz stimulation compared with the sham condition. P < 0.05 (See Fig. 3).

image

Figure 3. Intracortical inhibition and facilitation is modulated by tACS The single-pulse standardized double-stimulation MEP amplitude ratios ±s.e.m. are depicted for ISIs revealing inhibitory (ISIs of 2 and 4 ms) and facilitatory (ISIs of 7, 9 and 12 ms) effects for the different tACS protocols. A and C, 80 Hz (A) and 250 Hz (C) stimulation do not shift inhibition and facilitation relative to the sham stimulation. B, 140 Hz stimulation reduces SICI. D, bar graphs show the mean of MEP value (±s.e.m.) for SICI (ISI 2 and 4 ms) and ICF (ISI 7, 9 and 12 ms) for each condition. *P < 0.05, Fisher's LSD test.

Download figure to PowerPoint

Administration of 140 Hz had no effect on ICF, LICI and CSP as revealed by the results of the respective ANOVAs (Table 2).

Table 2.  Results of the repeated measurement ANOVAs for the study with regard to I-O curve, SICI/ICF, LICI and CSP protocols
 FactordfFP
  1. Bold indicates significant values (*P < 0.05).

I-OType of stimulation33.730.02
Intensity239.10<0.01
Type of stimulation × intensity61.110.4
SICIType of stimulation33,150.04
ISI10.840.39
Type of stimulation × ISI30.630.6
ICFType of stimulation30.620.61
ISI26.480.002
Type of stimulation × ISI60.840.54
LICIType of stimulation30.080.97
ISI39.46<0.01
Type of stimulation × ISI90.230.99
CSPType of stimulation30.730.54
Intensity14.520.07
Type of stimulation × Intensity30.810.5

Experiment 2. Motor task-related modulation of different frequency tACS

Single pulse TMS study In previous publications, muscle contraction decreased MEP observed after mental effort and motor activation using tDCS (Antal et al. 2007), paired associative stimulation (PAS) (Stefan et al. 2004), theta burst stimulation (TBS) (Huang et al. 2008a) and tRNS (Terney et al. 2008). In this study for the first time sham stimulation combined with muscle activation was recorded. Muscle contraction itself results in a significant decrease in MEP amplitude compared to baseline observed at the time points PST0–PST10 (Fisher LSD, P < 0.01). Baseline comparisons for each verum stimulation showed suppression of MEP amplitudes at the 0 time point (P < 0.05). See Fig. 4.

image

Figure 4. Motor task-related modulation of different frequency tACS The figure shows mean amplitudes of MEPs and their s.e.m. after tAC stimulation under motor activation up to 60 min. Stimulation of 80 Hz AC and 250 Hz did not modify the MEP amplitudes significantly, when compared with sham stimulation. In contrast, 140 Hz stimulation during contraction still induced a significant elevation in MEP amplitude compared to sham stimulation. According to the post hoc analysis, significantly increased MEPs were observed in 140 Hz at the PST5–PST50 time points compared to the time point using sham stimulation. Filled symbols indicate significant deviations of the post-measurements of MEP amplitudes from baseline values. *P < 0.05, Fisher's LSD test.

Download figure to PowerPoint

tACS of 80 Hz and 250 Hz did not modify the activation-induced decrease of MEP size; only 140 Hz resulted in a MEP size increase.

Repeated measures ANOVA revealed a significant effect of TYPE OF STIMULATION (F3.24= 4.87, P= 0.009) and TIME (F8.64= 7.06, P < 0.0001). The interaction between TYPE OF STIMULATION and TIME was not significant (F24.192= 1. 29, P= 0.2).

According to Fisher's LSD analysis, significantly increased MEPs were observed with 140 Hz at the PST5–PST50 time points compared to the time point using sham stimulation (P < 0.05). See Fig. 4.

Experiment 3. Behavioural studies (SRTT)

No improvement of reaction times was evident during 140 Hz, in contrast to tDCS (Nitsche et al. 2003) and to tRNS (Terney et al. 2008).

For reaction time the repeated measures ANOVA revealed a significant main effect of blocks (F7.77= 20.43, P < 0.0001); however the main effect of TYPE OF STIMULATION (F3.33= 0.83, P= 0.5) and interaction between TYPE OF STIMULATION and BLOCKS (F21.23= 1.43, P= 0.1) were not significant. Interactive t tests revealed no significant differences between blocks 5 and 6 between active and sham conditions.

As shown in Fig. 5C, with 250 Hz a slight improvement was evident in Blocks 2–5.

image

Figure 5. Serial reaction time task (SRTT) and tACS Stimulation at 80 Hz and 140 Hz of the primary motor cortex did not improve implicit motor learning. Interestingly, with 250 Hz a slight but non-significant improvement was evident in Blocks 2–5. Reduced RTs in Blocks 7 and 8 have been identified in two tACS frequency conditions: 80 and 250 Hz, compared to the sham condition. This effect was missing in the 140 Hz tACS condition.

Download figure to PowerPoint

Figure 5 shows the differences between 80 Hz, 140 Hz and 250 Hz tACS and sham stimulation.

For the error rate (ER) in all conditions, the ANOVAs showed a significant main effect on blocks. Despite this, the results of all other tests in all condition remained non-significant.

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

Here we demonstrate for the first time that high frequency oscillatory non-invasive brain stimulation is capable of inducing frequency-specific long-lasting cerebral excitability elevations in humans. Using 10 min tACS at the peak ripple frequency of 140 Hz we could increase M1 excitability as measured by TMS immediately and for at least an hour afterwards. Controls of sham and 80 Hz stimulation were without any effect. A 10 min application of 250 Hz also elicited a less prominent increase of MEP amplitudes, which predominates later during the stimulation and persisted for a shorter time post-stimulation compared to 140 Hz tACS. Support for the assumption that tACS in a frequency range above 100 Hz is effective comes from a recent study in the dorsal column pathway using epidural stimulation as a tool to restore locomotive capability in animal models of Parkinson's disease symptoms. In this study the effect was strongest for 300 Hz stimulation (Fuentes et al. 2009).

Taking into account our previous studies on tDCS, tACS at 140 Hz stimulation duration seems to be at least as effective as anodal tDCS (Nitsche & Paulus, 2001) or tRNS (Terney et al. 2008) applied at the same intensity and stimulation duration of 1 mA and 10 min. However, tACS avoids the direction sensitivity that is observed by using tDCS and goes along completely unnoticed by the subjects. In contrast to tDCS so far we see no possibility of reducing corticospinal excitability with 140 Hz tACS of the motor cortex.

tACS of 140 Hz has a better blinding potential for controlled studies compared to rTMS or tDCS. It confirms also the sensitivity to high frequency stimulation seen in human cortical excitability studies with tRNS (Terney et al. 2008). In this study a random noise frequency range between 100 and 640 Hz was responsible for excitatory after-effects, in contrast to the frequency range below 100 Hz, which was also ineffective, such as the 80 Hz condition here. It remains to be determined if the tRNS result was essentially based on inducing a resonance phenomenon in the ripple frequency range. Not only DC fields, but also AC fields may cause polarization of cell membranes (Deans et al. 2007). Since the membrane is loaded with lots of voltage gated channels, which are ‘non-linear’, these induced changes in membrane fluctuation are not ‘just cancelled out’, but may even be amplified and result in a net depolarization.

Further differences from transcranial magnetic or direct current stimulation results can also be observed. Excitability increase under motor activation was reduced with 140 Hz tACS but not inverted such as seen in both anodal and cathodal tDCS (Antal et al. 2007). In contrast to anodal tDCS implicit motor learning was not significantly facilitated with tACS at any of the three frequencies used here. Obviously 140 Hz tACS is less effective for facilitating implicit learning than both tRNS (Terney et al. 2008) or anodal tDCS (Nitsche et al. 2003) since in the present study there was only a tendency for a improvement in reaction times in the late blocks 7 and 8, for 250 Hz. The non-significant changes concerning implicit learning were probably caused by a too low number of subjects; larger sample sizes would have been necessary to prove the significant effect of stimulation if there is any.

In our previous study applying high frequency tRNS, we have found an increased ICF after tRNS over M1 using the paired-pulse protocol (Terney et al. 2008). TRNS application had no effect on SICI, LICI, CSP or motor-evoked recruitment curves. In the present study, interestingly 140 Hz stimulation reduced SICI. This suggests that the excitability of the interneurones involved is affected by this frequency of stimulation. Pharmacological studies have suggested that SICI at lower conditioning stimulation intensities as used here is mediated through the activation of GABAA receptors (Ziemann et al. 1996; Di Lazzaro et al. 2005; Paulus et al. 2008) whereas LICI is mediated by GABAB receptors (McDonnell et al. 2006). This apparent result seems to be at odds with the classical inhibitory action of GABA, but can be explained by the paradoxical excitatory effects of GABA published in this context recently: in human neocortical slices high frequency stimulation with 130 Hz at 1 mA evoked the release of endogenous GABA via subthreshold activation of voltage-gated sodium channels (Mantovani et al. 2006). More recently, it was shown that the effects of 130 Hz stimulation in this model are mediated by paradoxically facilitatory autoreceptors located on soma, dendrites and axon terminals of GABAergic neurons (Mantovani et al. 2009) well in line with findings of excitatory GABAergic axo-axonic cells (Szabadics et al. 2006). Axo-axonic cells can depolarize pyramidal cells and can initiate stereotyped series of synaptic events in cortical networks because of a depolarized reversal potential for axonal relative to perisomatic GABAergic inputs. As summarized recently, during ripple oscillations basket and bistratified cells increase their firing rate strongly and discharge, whereas in contrast, both axo-axonic and oriens–lacunosum-moleculare (O-LM) cells are silenced during and after it, and O-LM cell firing is suppressed during ripples. Since these different interneurons innervate distinct domains of pyramidal cells, they concurrently imprint a spatiotemporal GABAergic conductance matrix onto these cells (Klausberger & Somogyi, 2008).

In vivo fast IPSPs on the somata of pyramidal cells have been proposed as a potential mechanism of high-frequency oscillation generation mainly in the hippocampus (Buzsaki et al. 1992; Ylinen et al. 1995). In vitro slice recordings suggest an important synchronizing role for spikelets during spontaneous high-frequency oscillations (Draguhn et al. 1998). Epsztein et al. (2010) have shown that a high incidence of spikelets that occur either in isolation or in bursts could drive spiking as fast as prepotentials of action potentials with the burst firing rate peaking at 138 Hz.

A recent study observed that externally induced neuronal plasticity is highly dependent on the physiological state of the subject during stimulation. The average MEP decreases after mental effort and motor activation using tDCS (Antal et al. 2007), paired associative stimulation (PAS) (Stefan et al. 2004), theta burst stimulation (TBS) (Huang et al. 2008b) and tRNS (Terney et al. 2008). It was suggested that contraction may have changed the membrane potential or Ca2+ concentration of postsynaptic neurons, and these affected the response to the conditioning protocol (Huang et al. 2008b). Recent findings also suggest that Ca2+ dynamics determine the polarity of LTP/LTD-like changes in vivo (Wankerl et al. 2010). Here we show for the first time that high frequency tACS in the ripple range is also affected by this mechanism. Stimulation at 140 Hz is, however, able to override this inhibition to some extent, underscoring further the particular excitatory efficacy of this frequency. Obviously the 140 Hz stimulation induces more powerful excitatory after-effects than the control conditions, compensating partially and better for the activity induced loss of MEP size than, for example, iTBS or anodal tDCS.

Another possible explanation of our findings is that the external stimulation of the cortical network leads to modifications in the vascular system that might result in secondary changes in cortical excitability. Indeed, a synchronous activation of large number of neurons may also have metabolic consequences, changing the perineuronal milieu and triggering vascular responses as it has been documented for rTMS (Paus et al. 1998; Pecuch et al. 2000). Because we did not measure metabolic changes, further studies are required to clarify this question.

We cannot exclude a minor modification of tACS after-effects by TMS during tACS application. However, so far in general an influence on cortical excitability with very low stimulation frequencies has only been proven when additional measures were introduced such as ischaemic deafferentation (Ziemann et al. 1998). Furthermore, the after-effects seen here are concordant to those observed in many studies using anodal tDCS (overview in: Ziemann et al. 1998; Nitsche et al. 2008) and one concerning tRNS results (Terney et al. 2008).

We are aware of the fact that spontaneous ripple oscillations in the human brain are short-lived in the hippocampus and that the present stimulation protocol only mimics the frequency, not the duration, of ripples in man. Nevertheless here we provide the proof of principle and further studies may be even more efficient when using intermittent ripple stimulation in analogy to, for example, iTBS. A similar approach was recently pursued by Groppa et al. (2010) showing that intermittent sinusoidally modulated tDCS provided similar excitatory or inhibitory after-effects when the amplitude was accordingly increased.

Transcranial application of high oscillatory frequencies is of great interest in movement disorders as well. Skull thickness and the related distance between the stimulation electrode and cortex is probably not a problem: according to Gabriel et al. (1996) in the frequency range employed here a linear resistance can be assumed for the tissues between the skin and the brain without an attenuation of the effects of higher frequencies. From a therapeutic viewpoint, our findings might lead to an implementation of tACS as a therapeutic tool, e.g. positively influencing cognition and motor performance of patients with aphasia, neglect or dementia, as has already been seen using repetitive TMS (for a review see Thut & Miniussi, 2009).

The results represent a further step to more targeted plasticity modulating protocols and also may have important implications for psychiatric diseases accompanied by pathological oscillations. A main difference from deep brain stimulation is the type of current used. Whereas tACS stimulates with sinusoidal electric fields, deep brain stimulation uses short pulses, which according to Gradinaru et al. (2009) works via direct stimulation of afferent axons projecting to the subthalamic nucleus. To our knowledge it is unclear if sinusoidal deep brain stimulation in this frequency range is able to induce spikes in fibre tracts. Just as assumed for tDCS, it may execute its effects via modulation of nerve membranes instead of inducing spikes. An interesting control experiment would be applying rTMS with 80, 140 and 250 Hz. Quite apart from the safety concerns, to our knowledge no stimulators are available with this high repetition rate. Also it will be interesting to investigate the effects of even higher tACS frequencies in future.

Some of the results of our study may be vulnerable to Type II statistical error. Therefore additional studies with larger sample sizes, focusing on as yet non-significant results presented here are warranted.

In summary, the modification of cortical activity through the application of high-frequency transcranial oscillations may adjust behaviourally maladaptive brain states and induce a new balance, pushing the network toward restoring adequate synchronisation and excitation.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

Appendix

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. References
  8. Appendix

Author contributions

All of the authors contributed substantially to conception, design and execution of the study, and analysis and interpretation of the data. The final version of the manuscript was approved by all of the authors. The authors have no financial or personal conflicts of interest.

Acknowledgements

This work was supported by the Bernstein Centre for Computational Neuroscience Göttingen (BMBF 01GQ 0782 to V.M., 01GQ0432 to A.A./W.P.) and the Rose Foundation (T298/14375/2004 and T298/14376/2004) (W.P.). We wish to thank Prof. Michael Nitsche for critical comments.