Tuning the brakes − Modulatory role of transcranial random noise stimulation on inhibition

Background Everyday decision-making requires the ability to flexibly modify and sometimes terminate our actions, such as avoiding a tempting slice of cake to hitting the brakes in an emergency. Neural oscillations, such as beta-band rhythms observed over the medial prefrontal cortex(mPFC), help regulate these context-dependent behaviours. However, how random noise stimulation would modulate neural rhythms and corresponding inhibitory behaviors remain understudied. Objectives To target the mPFC using random noise stimulation and modulate neural activity underlying inhibitory behaviours. Methods Using a single-blinded within-subject design, fifteen participants received random noise or sham stimulation in a pseudo-randomized order while performing a Go/Conflict/No-Go task. We measured neural activity and behavior before and after stimulation. Results We show that random noise stimulation significantly improved inhibitory behaviors (4.6±4.42percent) by reducing the number of errors in No-Go trials. This improvement was a function of participants’ impulsivity-levels and baseline performance, i.e., impulsive individuals who made more baseline errors improved more after receiving stimulation. At the neural level, we show that random noise stimulation increases low-beta power at stimulation site, mediated by an increase in the duration of intermittent beta-bursts. Conclusion We show for the first time that random noise stimulation improves the ability to withhold response to unexpected inhibitory cues as a function of an individual’s impulsivity level. This improvement could be attributed to increased low-beta band power and intermittent-burst duration. These results suggest that random noise stimulation of the mPFC could potentially be used as a neuromodulatory intervention to target maladaptive behaviors in impulse control disorders.

We recruited 16 participants (one participant dropped due to time constraints) from the general population, who were screened for contra-indications of non-invasive brain stimulation.All participants had normal/corrected vision and were right-handed.The Central University Research Ethics Committee of the University of Oxford approved the study (CUREC-R77362/RE003).The study was undertaken in accordance with the Declaration of Helsinki, and informed written consent was obtained from all participants.
The study followed a within-subject single blinded design, during which participants received either active or sham TRNS in a given session.The participants completed a modified Go/No-Go task (Figure -1B) with a conflict component [6].We recorded participant's EEG using a TMSi-Porti amplifier (TMS-International, Netherlands), synchronised to the paradigm via Psychtoolbox.TRNS was delivered using a batterypowered stimulator (DC-Stimulator-PLUS, NeuroConn, GmbH, Germany) via rubber electrodes positioned over F z (Active: outer-ring-4.8cm;inner-ring-2.4cm-diameter) and P z (Return:Rectangular-5x7cm 2 ) Figure -1A (supplementary information).The participants were aged 25.8±6.04yearsand had an impulsivity score of 38.5±7.8 [7].The Bang-blindingindex for active (0.2) and sham (-0.13) sessions indicated a sufficient level of blinding.The participants reported the presence of expected sensations, such as itching and fatigue at moderate levels.
TRNS stimulation improved inhibitory behaviours, observed as an increase in accuracy in the No-Go condition.Using a two-way Friedman's non-parametric test (Figure -1C) we compared accuracies at baseline (TRNS:0.95±0.04,sham:0.97±0.04)and after-stimulation (TRNS:1, sham:0.99±0.02),which showed significant differences between the distributions (χ2(3)=15.8,p=0.001)and a significant increase in accuracy for TRNS condition alone (p=0.035)following pairwise comparisons across conditions.A non-parametric Spearman's correlation showed an inverse relationship between the baseline No-Go accuracy and impulsivity scores (ρ=-0.5, p=0.02), i.e., individuals with higher impulsivity scores made more errors in the baseline-TRNS condition.Furthermore, a Spearman's correlation showed a positive correlation (Figure -1D) between the impulsivity scores and percentage improvement after TRNS (ρ=0.57,p=0.03), i.e., individuals with higher impulsivity scores had better improvement in their accuracy scores after TRNS but not after sham (ρ=-0.43,p=0.1).There was no effect of stimulation on behaviours concerning Go and Conflict conditions.
To further explore neural signatures driving this improvement in No-Go accuracy, we compared the spectral power over the F z corresponding to the No-Go trials (baseline and after-stimulation) after cue-onset.TRNS increased the spectral power in the beta band(p=0.022)over F z (cluster highlighted with an outline in Figure -1E) between 0.5 and 1 seconds after cue onset (time=0) compared to baseline.This increase in spectral power was absent in the sham condition.We then extracted intermittent beta-burst average duration at baseline and after-stimulation for both TRNS and sham conditions.There was a main effect of state (baseline vs after-stimulation: (F(1,13)=6.36,p=0.025)) and interaction (F(1,13)=8.91,p=0.011) but not condition (TRNS vs sham: (F(1,13)=0.16,p=0.69)).A paired sample t-test showed a significant increase in burst duration after TRNS (t(13)=-4.5,p<0.001)but not sham (t(13)=0.32,p=0.75)(Figure-1F).

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Here, we show for the first time that the TRNS induced improvement in stopping behaviours is a function of participants' baseline impulsivity levels.TRNS had a differential effect on inhibitory control, i.e., participants with higher impulsivity improved more after receiving stimulation.This result supports the notion that the impact of stimulation on behaviour could be a function of baseline performance [8], as observed in other stimulation techniques.
Critically, we show for the first time that this improvement in stopping behaviours after TRNS is mediated through an increase in the low-beta band power (up to 20Hz) (Figure -1E) over the mPFC during No-Go trials.This increase in spectral power coincides with the approximate reaction time during Go and Conflict trials(supplementary) (i.e., expecting a movement).We therefore argue that the observed rise in spectral power after TRNS, specifically in this time window when a movement was observed in Go and Conflict trials, maybe a potential counteractive mechanism to improve inhibition during No-Go trials.Beta was one of the two prominent bands that has been observed over the mPFC, with an ascending oscillatory power across Go, Conflict and No-Go trials [6].While the precise mechanism through which TRNS modulates beta rhythms remains unknown, taking into account the findings from previous work [4], one could argue that GABA A could drive this modulatory effect.It has recently been shown that oscillatory activity exists as 'bursts', i.e., short transient cycles of activity in sensorimotor cortex [9,10].Here, we observed beta burst profiles over the mPFC: duration of these temporally localized intermittent bursts was increased by TRNS (Figure -1F).Previously, our research group has shown that burst features in the motor cortex could be modulated by the strength of GABAergic inhibition which inversely correlated with beta burst duration [5].Therefore, we posit that TRNS may increase the overall burst duration and power by modulating the complex excitatoryinhibitory connectivity of the mPFC via interneurons and GABAergic signalling.However, this requires further confirmation, either using Magnetic Resonance Spectroscopy or pairedpulse protocols.

Figure 1 .
Figure 1.shows a summary of the experimental set up and the cognitive paradigm.(A) shows the sequence of steps in a given session measuring EEGs and behavior at baseline, during and after-stimulation (roughly within 5 minutes of completing the stimulation).TRNS was delivered with the active electrode over F z and the return at P z .(B) shows the sequence of events during the cognitive paradigm for Go, Conflict and No-Go trials with feedback for correct, slow-correct and incorrect responses, respectively.(C) shows the No-Go accuracy levels at baseline and after-stimulation for sham and TRNS conditions.(D) shows the improvement in the individual No-Go accuracies as a function of their impulsivity scores after TRNS and (E) shows the F z spectral power after TRNS.The outline shows the increased power in the time-frequency domain when comparing baseline with after TRNS and (F) shows the average burst duration changes across F z .The outline in Plot E indicates the significant cluster (p<0.025) and the dotted line indicates the onset of the No-Go cue.* indicates p<0.05