Introduction
Post-traumatic stress disorder (PTSD) and anxiety are mental health disorders that are difficult to treat, particularly among military patients (Spinhoven et al., Reference Spinhoven, Batelaan, Rhebergen, van Balkom, Schoevers and Penninx2016; Straud, Siev, Messer, & Zalta, Reference Straud, Siev, Messer and Zalta2019). New treatment targets may be provided by finding ways to restore deficits in neurocognitive processes. Across patients with PTSD, anxiety, and impulsive aggression, dysregulated neurocognitive processes center around hyperresponsive limbic regions including the amygdala and (dorsal) anterior cingulate cortex (ACC) (Craske et al., Reference Craske, Stein, Eley, Milad, Holmes, Rapee and Wittchen2017; Davidson, Putnam, & Larson, Reference Davidson, Putnam and Larson2000; Hayes, Hayes, & Mikedis, Reference Hayes, Hayes and Mikedis2012) and hyporesponsive regions in the lateral and medial prefrontal cortex (PFC), accompanied by impairments in cognitive functions like working memory, cognitive flexibility, and inhibitory control (Etkin, Gyurak, & O'Hara, Reference Etkin, Gyurak and O'Hara2013).
Of these cognitive functions, inhibitory control particularly may play a vital role. Inhibitory control comprises the ability to withhold automatic or context-inappropriate responses in order to maintain goal-directed behavior. PTSD patients display impairments specifically on inhibitory control tasks (DeGutis et al., Reference DeGutis, Esterman, McCulloch, Rosenblatt, Milberg and McGlinchey2015) and hypoactivation in the brain's hub of inhibitory control: the right inferior frontal gyrus (IFG) (Aron, Robbins, & Poldrack, Reference Aron, Robbins and Poldrack2014; Hayes et al., Reference Hayes, Hayes and Mikedis2012). It is proposed that failing inhibition of inappropriate stress responses, memories, and motor reactions to fear-evoking stimuli contributes to symptoms of hyperarousal and irritability, and in turn, avoidance of fear- or trauma-related triggers and defensive aggression (Aupperle, Melrose, Stein, & Paulus, Reference Aupperle, Melrose, Stein and Paulus2012; van Rooij & Jovanovic, Reference van Rooij and Jovanovic2019). Moreover, impairments in the prefrontal inhibitory control circuit may impede therapy response (Marwood, Wise, Perkins, & Cleare, Reference Marwood, Wise, Perkins and Cleare2018). An appealing question is therefore whether the dysregulated inhibitory control circuit poses a potential therapeutic target.
To restore dysregulated brain circuits, transcranial direct current stimulation (tDCS) may play a role by promoting neural plasticity (Yavari, Jamil, Mosayebi Samani, Vidor, & Nitsche, Reference Yavari, Jamil, Mosayebi Samani, Vidor and Nitsche2018). While tDCS alone may not effectively modulate emotional distress (Smits, Schutter, van Honk, & Geuze, Reference Smits, Schutter, van Honk and Geuze2020), deficient cognitive processes underlying stress-related disorders – such as inhibitory control – could comprise convenient tDCS targets in this context. For example, single-session tDCS over the right IFG has shown to increase inhibitory control task performance (Mayer et al., Reference Mayer, Chopard, Nicolier, Gabriel, Masse, Giustiniani and Bennabi2020; Schroeder, Schwippel, Wolz, & Svaldi, Reference Schroeder, Schwippel, Wolz and Svaldi2020). Inhibitory control can also be enhanced with other techniques used to modulate right IFG functioning (e.g. transcranial magnetic stimulation or neurofeedback by functional magnetic resonance imaging) (Alegria et al., Reference Alegria, Wulff, Brinson, Barker, Norman, Brandeis and Rubia2017; Zandbelt, Bloemendaal, Hoogendam, Kahn, & Vink, Reference Zandbelt, Bloemendaal, Hoogendam, Kahn and Vink2013). Interestingly, multiple-session tDCS combined with response inhibition training has demonstrated cumulative effects on inhibitory control performance in healthy volunteers (Ditye, Jacobson, Walsh, & Lavidor, Reference Ditye, Jacobson, Walsh and Lavidor2012). Increasing evidence now suggests that combining multiple tDCS sessions with cognitive training may produce stronger, more consistent, and longer-lasting effects on and beyond the trained function (Berryhill & Martin, Reference Berryhill and Martin2018). Combining multiple-session tDCS with inhibitory control training may thus provide opportunities to target impairments in the prefrontal inhibitory control function. The next step in exploring the potential of tDCS-enhanced inhibitory control training in treating stress-related disorders is to replicate these effects in a clinical sample and test whether this beneficially affects clinically relevant outcomes.
In this randomized-controlled trial (RCT), we applied a 5-session inhibitory control training with anodal tDCS over the right IFG in military veterans and active-duty personnel with PTSD, anxiety, or impulsive aggression. As a primary outcome, we tested whether tDCS enhanced inhibitory control during training. As secondary outcomes, we tested tDCS-related changes in inhibitory control performance and stress-related symptoms over the intervention period.
Methods
This double-blind RCT was preregistered at the Netherlands Trial Register (www.trialregister.nl, ID: NL5709).
Participants
Military veterans and active-duty personnel of the Dutch Ministry of Defence were recruited between May 2016 and October 2019 through advertisements in mental healthcare outpatient clinics. The following inclusion criteria were applied: 18–60 years of age, fulfilling diagnostic criteria and receiving treatment for PTSD, an anxiety disorder or impulsive aggression problems. Exclusion criteria: primary diagnosis for major depressive disorder (comorbid depression was not a reason for exclusion), substance addiction, severe neurological or psychotic disorder, serious head trauma or surgery, large metal or ferromagnetic parts in the head, implanted pacemaker or neurostimulator, pregnancy, skin damage on the scalp, and neurostimulation in the past month. Psychoactive medication use was assessed. Patients were asked to keep stable doses during the tDCS intervention, starting two weeks in advance. The a priori computed sample size was 96 [48 per group; computed in G*Power 3.1 (Faul, Erdfelder, Lang, and Buchner, Reference Faul, Erdfelder, Lang and Buchner2007) with α = 0.05, β = 90%, and Cohen's f = 0.34 based on results from Ditye and coworkers (Ditye et al., Reference Ditye, Jacobson, Walsh and Lavidor2012) lowered by 10%]. The medical ethical committee of the University Medical Center Utrecht approved the study. All participants provided written informed consent. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008.
Procedure and randomization
Figure 1b depicts the study procedure. First, a clinical diagnostic interview was done, including the SCID-I for DSM-IV-R Axis-I disorders (First, Spitzer, Gibbon, & Williams, Reference First, Spitzer, Gibbon and Williams2002), DSM-5 intermittent explosive disorder criteria (Coccaro, Reference Coccaro2012), and M.I.N.I. ADHD criteria (Sheehan et al., Reference Sheehan, Lecrubier, Sheehan, Amorim, Janavs, Weiller and Dunbar1998). Patients were then allocated to active or sham tDCS (1:1) by the next available stimulator-activating code from a randomized list (Matlab ‘rand’ function; 20 codes for active tDCS, 20 codes for sham), stratified by eye movement desensitization and reprocessing (EMDR) therapy v. cognitive behavioral therapy (CBT) to avoid confounding with psychotherapy effects. Experimenters were blind for code-to-condition correspondence, and, although not formally tested, patients were not expected to know whether they received sham or active tDCS (Ambrus et al., Reference Ambrus, Al-Moyed, Chaieb, Sarp, Antal and Paulus2012). The interview and tDCS sessions were carried out in test rooms at the University Medical Center Utrecht. Pre- and post-assessments took place online through a weblink.
Fig. 1. (a) CONSORT study flow diagram. FU-3m = 3-months follow-up assessment. FU-1yr = 1-year follow-up assessment. (i) Reasons: delayed discovery of tDCS safety contraindication (n = 1), time conflict with other treatment/work (n = 1). (ii) Reasons: panic symptoms at tDCS work-up session 1 (n = 1), time conflict with other treatment (n = 1). (iii) Reasons: time conflict with other treatment/work (n = 2). (iv) Reasons: psychoactive drug changes during intervention (n = 1), >5 days between tDCS sessions (n = 1), tDCS applied at <1.25 mA on request of participant (n = 1); (v) Reasons: inadequate performance of the stop-signal task (n = 1); (b) Overview of study procedure.
tDCS
Participants received five tDCS sessions, with 1–5 days between sessions depending on the participant's availability. TDCS was applied for 20 min over two 5 × 7 cm electrodes by a neuroConn DC-stimulator Plus with settings based on Ditye's study (Ditye et al., Reference Ditye, Jacobson, Walsh and Lavidor2012): 1.25 mA (fade-in: 8 s), anode on the crossing point between 10-20 system EEG positions T4-Fz and F8-Cz, cathode over the left orbital region (see Fig. 1b). Sham tDCS was applied by a 16-s fade-in fade-out stimulation at the start and end of the stimulation period, interleaved by occasional 15 ms pulses of 0.11 mA. The emotional state was assessed before and after each session by the STAI-6 (Marteau & Bekker, Reference Marteau and Bekker1992), together with possible tDCS side effects scored from 1 (‘absent’) to 4 (‘severe’) (Brunoni et al., Reference Brunoni, Amadera, Berbel, Volz, Rizzerio and Fregni2011).
Inhibitory control training
TDCS was combined with a 30-min training on the stop-signal task, see Fig. 1b (Logan, Cowan, & Davis, Reference Logan, Cowan and Davis1984). Participants were instructed to quickly press the left or right arrow button upon stimulus presentation (circle or square), but to withhold their response when a stop-signal was heard: an auditory ‘beep’ (25% of trials, 0–400 ms stop-signal onset delay). To titrate successful stop-signal response inhibition to ~50%, stop-signal delays increased or decreased with 50 ms after successful or unsuccessful stopping, respectively. Six blocks of 100 trials were interleaved by 1-min breaks. One extra block with 20 no-signal trials to prevent response slowing was excluded from data analysis. The stop-signal response time (SSRT), the time it takes to stop an already initiated response which reflects inhibitory control, was computed by the independent horse-race model (Logan et al., Reference Logan, Cowan and Davis1984) and constituted our primary outcome measure. Response speed (RT on no-signal trials) was taken as a control measure.
Secondary outcome measures of inhibitory control
Prolonged effects of training combined with active v. sham tDCS on inhibitory control were tested by comparing performance at pre- v. post-assessment on the emotional go/no-go task and the implicit association task (IAT).
The go/no-go task was used to measure the inhibition of prepotent responses driven by a high frequency of go-stimuli. Participants were instructed to rapidly tap on the space bar when a go-stimulus appeared (80% of trials), and to withhold their response to a no-go-stimulus (20% of trials). On 50% of all trials, ‘go’- and ‘no-go’-stimuli (‘[]’ and ‘][’) were superimposed on male face images with a neutral or angry expression [Bochum Emotional Stimulus Set, BESST (Thoma, Soria Bauser, and Suchan, Reference Thoma, Soria Bauser and Suchan2013)], to assess threat-related distraction on inhibition performance (Gladwin, Möbius, & Vink, Reference Gladwin, Möbius and Vink2019). Stimuli were presented for 600 ms with a 250–350 ms inter-trial interval in 7 blocks of 40 trials. The median reaction time (RT) over go-trials was used to assess effects on response speed, and accuracy represented the ability to correctly execute or inhibit responses. The first (practice) block, the first four trials of each block, post-error trials, sequences of ⩾ 5 consecutive no-response go-trials, and trials with an RT<170 ms were excluded from analysis (on average, 18.5% of trials were excluded).
The IAT was used to measure inhibition of prepotent responses driven by automatic associations. We used the standard IAT with flower and insect names as target words and pleasant and unpleasant words as attributes (Greenwald, McGhee, & Schwartz, Reference Greenwald, McGhee and Schwartz1998). Participants were instructed to classify target and attribute words as quickly as possible by pressing the ‘F’ or ‘J’ button. Each category contained 15 practice trials and 60 test trials. Better inhibition of the automatic response attenuates the increase in response latency and error rate on incongruent trials (the IAT effect). The D600 IAT effect was computed by adding 600 ms to incorrect response RTs, and dividing the difference in congruent v. incongruent trial RTs by the RT standard deviation. In addition, a Quad model (Conrey, Sherman, Gawronski, Hugenberg, & Groom, Reference Conrey, Sherman, Gawronski, Hugenberg and Groom2005) was estimated based on trial-level classification errors using a multinomial tree processing model in R (Singmann & Kellen, Reference Singmann and Kellen2013), to quantify the ‘overcoming bias’ (the likelihood that the automatic association is overcome), representing the unique contribution of inhibitory control on IAT performance.
At post-assessment, participants additionally performed a dot-probe task. Unlike the inhibitory control tasks, this task assesses attentional biases for threat. The main outcomes of this task are described in the online Supplementary Materials.
Symptoms
Beside baseline symptom assessment by the diagnostic interview, symptom levels were assessed at pre-, post-, and follow-up-assessments by self-report scales including the PTSD Checklist for DSM-5 (PCL-5) (Weathers et al., Reference Weathers, Litz, Keane, Palmieri, Marx and Schnurr2013), the trait version of the positive and negative affect schedule (PANAS) (Watson, Clark, & Tellegen, Reference Watson, Clark and Tellegen1988), and the STAXI-2 (Spielberger, Reference Spielberger1999). TDCS effects on disorder-specific symptoms of PTSD, anxiety, and impulsive aggression were tested only within subgroups of participants who fulfilled the criteria for the corresponding diagnosis. Depressive symptoms and general mental well-being were assessed using the Beck Depression Inventory 2nd edition (BDI-II) (Beck, Steer, & Brown, Reference Beck, Steer and Brown1996) and the Outcome Questionnaire 45 (OQ45) (Lambert, Finch, & Maruish, Reference Lambert, Finch and Maruish2004). At baseline, childhood trauma and impulsivity traits were assessed by the Dutch version of the childhood trauma questionnaire short form (CTQ-SF) (Bernstein et al., Reference Bernstein, Stein, Newcomb, Walker, Pogge, Ahluvalia and Zule2003) and Barrett's Impulsivity Scale (BIS-11) (Patton, Stanford, & Barratt, Reference Patton, Stanford and Barratt1995).
Statistical analysis
Continuous outcomes were analyzed in mixed-design ANOVAs in R (R Foundation for Statistical Computing, 2016) with the ‘rstatix’ package (Kassambara, Reference Kassambara2020). Trial-level accuracy data were, as recommended (Jaeger, Reference Jaeger2008), analyzed in binary logistic mixed-effects models with the ‘lme4’ package (Bates, Mächler, Bolker, & Walker, Reference Bates, Mächler, Bolker and Walker2015) with a random intercept for the participant, where p values were obtained in likelihood ratio tests of the full model v. a model without the effect. Stimulation group (active v. sham tDCS) was treated as between-subjects factor, Time (tDCS sessions 1–5, or pre-assessment, post-assessment and follow-ups) as within-subjects factor, and their interaction would reflect whether the active tDCS intervention induced different time effects than the sham intervention. Age and Use of psychoactive medication (yes/no) were included as covariates. Where the assumption of sphericity was violated, Greenhouse-Geisser-corrected results are reported. Effects are reported as significant at p < 0.05. Effect sizes are reported as generalized eta-squared (η 2G).
Additionally, to provide possibly useful information for neurocognitive models about the relationship between inhibitory control and stress-related symptoms, we computed baseline correlations between the inhibitory control tasks and symptom scores at pre-assessment. Also, to explore if improved inhibitory control could drive symptom relief, we tested in a regression model if (i) SSRT improvement (ΔSSRT = SSRT session 5 − SSRT session 1) or (ii) the achieved SSRT level on session 5 predicted reductions in PTSD, anxiety, or anger symptoms (Δsymptom score = post-score − pre-score). Here, Stimulation group was always entered as a first predictor to control for effects attributable to tDCS.
Results
Figure 1a shows the study flow. As can be seen in Table 1, the active tDCS and sham groups matched on most factors. Yet, despite random group allocation, females and post-active veterans were overrepresented in the active tDCS group, while patients with an anxiety diagnosis were overrepresented in the sham group. Because prefrontal tDCS outcomes may depend on gender (Dedoncker, Brunoni, Baeken, & Vanderhasselt, Reference Dedoncker, Brunoni, Baeken and Vanderhasselt2016), we repeated analyses without the female participants. This did not significantly change results.
Table 1. Demographical and clinical participant characteristics with mean and standard deviation values or count
a Age was entered as a covariate in the statistical analyses. Excluding the Age covariate from the models did not significantly change the results.
b Education level: low = high school education only, moderate = vocational degree, high = higher education degree.
c EMDR, eye movement desensitization and reprocessing therapy; CBT, cognitive behavioral therapy. Other treatments included: aggression regulation training, mindfulness-based therapy, couples therapy, maintenance therapy by social workers, and pharmacological treatment.
d The majority of psychoactive drugs used in our sample comprised selective serotonin or serotonin-norepinephrine reuptake inhibitors (SSRI's and SNRI's), benzodiazepines, atypical antipsychotic drugs, norepinephrine-dopamine reuptake inhibitors (NDRI's), and anticonvulsants. Analysis of the primary outcome measure (SST training scores) showed similar results across medicated and unmedicated patients. Also, excluding Use of psychoactive medication (yes/no) as a covariate from the models did not significantly change the results of any other measure.
e While most participants fulfilled criteria for either PTSD or anxiety or impulsive aggression, some participants fulfilled criteria for multiple stress-related diagnoses: PTSD and anxiety (n = 10), PTSD and impulsive aggression (n = 14), anxiety and impulsive aggression (n = 6), or all three diagnoses (n = 5).
Safety
The intervention was well tolerated and no serious adverse events were reported. The only tDCS-related side effects were mild itching and burning sensations on the scalp (mean severity scores ± s.d. itching – active tDCS: 1.7 ± 0.7 v. sham: 1.4 ± 0.6; burning – active tDCS: 1.6 ± 0.7 v. sham: 1.3 ± 0.6; p's < 0.001), and some tDCS participants noticed light skin redness that was absent in the sham group (active tDCS: 1.1 ± 0.6 v. sham: 1.0 ± 0.1; p = 0.010). Emotional state fluctuations during tDCS sessions were negligible and did not significantly differ between stimulation groups (mean STAI-6 item absolute change score: 0.26 ± 0.48; effects of Stimulation group and Stimulation group × STAI-6 item on change scores: p's > 0.18).
Primary outcome: inhibitory control training on the stop-signal task
Three participants showed very slow response times on session 1, preventing reliable SSRT computations. As this comprised <5% of the data, the a priori defined analyses were performed on the remaining sample (46 tDCS and 47 sham) (Jakobsen, Gluud, Wetterslev, & Winkel, Reference Jakobsen, Gluud, Wetterslev and Winkel2017). A mean stop-signal response accuracy of 51.5% ± 7% confirmed successful stop-signal delay titration.
The active v. sham tDCS groups did not significantly differ in overall SSRT scores or in SSRT improvement over sessions, as indicated by the non-significant effects of Stimulation group and the Stimulation group × Time interaction (respectively: p = 0.239, η 2G = 0.011; p = 0.582, η 2G = 0.002). Only the main effect of Time was significant (p < 0.001, η 2G = 0.019). SSRT changes between sessions were tested with post-hoc Bonferroni-corrected pairwise t tests; the SSRT significantly decreased from session 1 to session 2 and all following sessions, from session 2 to session 3 and all following sessions, and from session 3 to session 5 (p's < 0.01), see Fig. 2. When Diagnosis was entered as an additional between-subjects factor to explore possible differences between patient subgroups, the tDCS related effects remained non-significant (Stimulation group: p = 0.255, η 2G = 0.011; Stimulation group × Time: p = 0.905, η 2G < 0.001; Stimulation group × Time × Diagnosis: p = 0.201, η 2G = 0.009). However, beside a main effect of Time (p < 0.001, η 2G = 0.018), a significant Time × Diagnosis interaction appeared (p = 0.005, η 2G = 0.020). Based on visual inspection of the SSRTs per subgroup, the interaction seemed to reflect a relatively strong SSRT decrease in the PTSD subgroup compared to the anxiety and aggression subgroups (see online Supplementary Fig. S2). Next, despite the underpowered 2 × 5 mixed design for the diagnosis subgroups, the subgroups were analyzed separately. The main effect of Time remained significant among PTSD patients (p = 0.014, η 2G = 0.028), and was non-significant in the anxiety and aggression subgroups (respectively: p = 0.094, η 2G = 0.019; p = 0.083, η 2G = 0.036).
Fig. 2. Mean SSRT (a) and mean item scores on symptom scales (b ) ± s.d. per stimulation group. n.s., non-significant. Please note that symptom scales were analyzed per subgroup of patients with the corresponding diagnosis, and that drop-out at follow-up reduced the sample sizes for FU-3m and FU-1yr assessments, see also Table 2.
Table 2. Statistical outcomes of non-trained inhibitory control and symptom measures
FU3m = 3-months follow-up assessment. FU1yr = 1-year follow-up assessment.
Concerning the no-signal RT, no significant effects of active v. sham tDCS appeared either (Stimulation group main effect: p = 0.338, η 2G = 0.012; Stimulation group × Time interaction: p = 0.309, η 2G = 0.003), although participants did become faster over sessions (main effect of Time: p < 0.001, η 2G = 0.024). For further details on the no-signal RT, see online Supplementary Fig. S2.
In an additional analysis, we explored if tDCS effects on inhibitory control training would depend on baseline levels of inhibitory control, which was assessed by the go/no-go task. To that end, we regressed the total SSRT improvement from sessions 1 to 5 on the predictors pre-assessment Go/no-go scores (RT and accuracy) and Stimulation group. Results showed no evidence for a dependence of tDCS effects on baseline inhibitory control performance (Stimulation group × Go/NoGo scores interaction effects: p's > 0.418). Analysis details can be found in the online Supplementary materials.
Secondary outcomes of inhibitory control
Means and standard deviations per group are reported in Table 2, together with the outcomes of the Stimulation group × Time interaction effects of interest.
Go/no-go task
Go/no-go data from 80 participants were available for analysis (40 tDCS, 40 sham; missings due to insufficient (<100) completed trials, n = 5; post-assessment unavailable or completed >1 week after tDCS intervention, n = 11). TDCS did not influence response speed or response inhibition accuracy: pre-to-post intervention changes in RT or no-go accuracy were not significantly different between active and sham tDCS groups (see Table 2). Response speed did not significantly change over time or differ between groups at all (main effect Time: p = 0.273, Stimulation group: p = 0.374). For accuracy, a significant Go/no-go × Time interaction (p = 0.005; β = 0.41, std. error = 0.15) and a significant Stimulation group × Time interaction appeared (p = 0.008; β = −0.17, std. error = 0.06). Bonferroni-corrected pairwise t tests showed that go-trial accuracy increased from pre- to post-assessment in both stimulation groups (go-trials – pre v. post: p < 0.001). Such effects were not found for no-go accuracy (i.e. response inhibition accuracy – pre v. post: p > 0.999). Moreover, the stimulation groups differed in overall performance accuracy at post-assessment, where the sham group made significantly less errors than the active tDCS group (pre-assessment – active tDCS v. sham: p = 0.898; post-assessment – active tDCS v. sham: p = 0.011), suggesting a lack of improvement in overall performance accuracy over time in the active tDCS group. Again, no group differences were found specifically in no-go accuracy (response inhibition). Furthermore, the face distractors significantly impaired task performance: Distractor condition showed a significant main effect on both RT and accuracy (p's < 0.001). Follow-up t tests and χ2 tests showed that RTs were faster on trials with face distractors (distractor v. no-distractor: p < 0.001, neutral v. angry distractor: p = 0.690). This distractor-induced RT acceleration also yielded a Stimulation group × Distractor condition interaction (p = 0.047), showing it was more pronounced in the active v. sham tDCS group (p = 0.034). Error rates increased from no-distractor- to neutral face distractor- to angry face distractor-trials (p's < 0.045).
IAT
IAT data from 84 participants were available for analysis (43 tDCS, 41 sham; missings due to post-assessment unavailable or completed >1 week after tDCS intervention, n = 12). Pre-to-post intervention changes in the D600 IAT effect did not significantly differ between the active tDCS and sham group (see Table 2). The IAT effect significantly increased from pre- to post-assessment (p = 0.042, η 2G = 0.021), indicating a possible reduction in inhibitory control over biases due to automatic associations. The Quad model ‘overcoming bias’ parameter did not appear significantly affected by Stimulation group, but the overall model fit was very low suggesting the Quad model results were not reliable (model fit for post-assessment IAT data – tDCS group: G2(6) = 11.33, p = 0.079, AIC = 23.33; sham: group G2(6) = 13.00, p = 0.043, AIC = 25.00). The full analysis is reported in the online Supplementary materials.
Symptoms
The analysis of PTSD symptoms was only carried out within the subgroup of PTSD patients, the analysis on anxiety symptoms only within the subgroup of anxiety patients, and likewise for the impulsive aggression patients. Data were available for analysis per diagnosis subgroup as indicated in Table 2 (missings due to unavailable post-assessment or completed >1 week after tDCS intervention: PTSD: n = 5; anxiety: n = 2; aggression: n = 3). Beside an overall significant reduction in symptom levels over time (main effect of Time: p's < 0.001, η 2G's > 0.008), the active tDCS v. sham groups did not significantly differ in symptom levels reductions, except for a slightly stronger reduction in PCL-5 scores in the active tDCS v. sham group due to higher baseline PTSD symptoms levels in the active tDCS group (see Table 2 and Fig. 2). When the 3-months and 1-year follow-ups were taken into account, these results did not substantively change, see Table 2. PANAS Positive Affect and STAXI-2 Anger Expression and Control scales did not show significant effects of tDCS v. sham (statistical results are reported in the online Supplementary material).
Exploratory analyses on the relation between inhibitory control and symptom severity
At baseline, higher symptom severity on all scales significantly correlated with worse stop-signal task inhibitory control performance, see Table 3. Baseline no-go-accuracy significantly correlated with PCL-5 and BDI-II scores. No other baseline inhibitory control measure correlated significantly with symptom levels.
Table 3. Correlation matrix with baseline measures of symptom severity and inhibitory control.
Higher symptom scores reflect higher symptom severity, lower (reversed) inhibitory control scores reflect worse inhibitory control performance. Note that the SSRT used for the baseline correlations was measured during the first tDCS session.
* p < 0.05, **p < 0.001.
The overall improvement in SSRT or the achieved level of SSRT on session 5 did not significantly predict symptom reductions (all p's > 0.28, full statistical outcomes are reported in the online Supplementary material). These results suggest no link between short-term inhibitory control improvements and symptom relief.
Discussion
Inhibitory control is thought to play a role in symptoms of PTSD, anxiety, and impulsive aggression. Here, the effects of a tDCS-combined inhibitory control training on pre–post measures of inhibitory control and symptoms were for the first time investigated in a preregistered RCT with a large clinical sample of military patients with these stress-related disorders. Contrary to previous findings (Ditye et al., Reference Ditye, Jacobson, Walsh and Lavidor2012), we failed to find an effect of anodal tDCS over the right IFG v. sham on performance during the stop-signal task inhibitory control training. No support was found either for tDCS effects on post-intervention non-trained inhibitory control nor on symptom levels of PTSD, anxiety, or impulsive aggression. Hence, despite positive effects of tDCS on inhibitory control in healthy individuals (Mayer et al., Reference Mayer, Chopard, Nicolier, Gabriel, Masse, Giustiniani and Bennabi2020) and on symptoms of PTSD and anxiety in patients (Ahmadizadeh, Rezaei, & Fitzgerald, Reference Ahmadizadeh, Rezaei and Fitzgerald2019; van ’t Wout-Frank, Shea, Larson, Greenberg, & Philip, Reference van ’t Wout-Frank, Shea, Larson, Greenberg and Philip2019; Vicario, Salehinejad, Felmingham, Martino, & Nitsche, Reference Vicario, Salehinejad, Felmingham, Martino and Nitsche2019), we found no evidence to support that right IFG tDCS combined with inhibitory control training with our experimental set-up can effectively improve inhibitory control or stress-related symptoms in these patients. These results raise questions on why the tDCS effects on inhibitory control did not replicate in our clinical sample, and, subsequently, what may be more effective ways to modulate clinically relevant cognitive processes and stress-related symptoms with non-invasive brain stimulation.
Effects of tDCS-combined training on inhibitory control
A substantial body of single-session tDCS research (Mayer et al., Reference Mayer, Chopard, Nicolier, Gabriel, Masse, Giustiniani and Bennabi2020; Schroeder et al., Reference Schroeder, Schwippel, Wolz and Svaldi2020) and a multiple-session tDCS-training intervention study (Ditye et al., Reference Ditye, Jacobson, Walsh and Lavidor2012) in healthy participants showed successful improvements in inhibitory control performance with tDCS settings not so different from ours (current intensity: 1–1.5 mA; anode over the right IFG; cathode on left orbital area or left cheek; duration: 10–30 min). Compared to the study of Ditye and coworkers, we extended the training and stimulation duration per session. Yet, the effects of tDCS were not replicated. Perhaps by using a current density on the low end (0.036 mA/cm2) of the range used for successful tDCS-enhanced stop-signal task performance in other studies (0.028–0.125 mA/cm2) (Mayer et al., Reference Mayer, Chopard, Nicolier, Gabriel, Masse, Giustiniani and Bennabi2020), the induced electrical field was too weak to modulate right IFG activity to an extent that would produce measurable behavioral changes [see, e.g. Li et al. (Reference Li, Violante, Leech, Ross, Hampshire, Opitz and Sharp2019)]. On the other hand, higher current densities do not necessarily follow a linear increase of tDCS effectivity (Yavari et al., Reference Yavari, Jamil, Mosayebi Samani, Vidor and Nitsche2018).
Secondly, although we used a montage as applied by other studies stimulating the IFG, there is uncertainty about the anode placement relative to the IFG. Simulations of the electrical field on one example brain showed a peak intensity located slightly above the IFG (see online Supplementary Fig. S1). Although inconclusive, the target region may have received suboptimal stimulation. To more effectively target inhibitory control, the anode could be placed somewhat lower to better focus the electrical field on the right IFG, e.g. on 10-20 system EEG positions F8 or F10 (Coffman et al., Reference Coffman, Trumbo, Flores, Garcia, van der Merwe, Wassermann and Clark2012; Schroeder et al., Reference Schroeder, Schwippel, Wolz and Svaldi2020), or higher, e.g. on position F4 to focus the field on the dorsolateral PFC (Dousset et al., Reference Dousset, Ingels, Schröder, Angioletti, Balconi, Kornreich and Campanella2020; Salehinejad, Wischnewski, Nejati, Vicario, & Nitsche, Reference Salehinejad, Wischnewski, Nejati, Vicario and Nitsche2019). However, tDCS with the anode placed on the F8-Cz Fz-T4 crossing, as in our study, has also shown successful response inhibition enhancement (Mayer et al., Reference Mayer, Chopard, Nicolier, Gabriel, Masse, Giustiniani and Bennabi2020; Schroeder et al., Reference Schroeder, Schwippel, Wolz and Svaldi2020). Technical tDCS parameter settings therefore do not seem to fully explain our null results.
Alternatively, we possibly over-trained a relatively simple inhibitory control task. As the primary physiological effects of tDCS act upon ongoing neuronal and synaptic activity (Kronberg, Bridi, Abel, Bikson, & Parra, Reference Kronberg, Bridi, Abel, Bikson and Parra2017; Liebetanz, Reference Liebetanz2002; Nitsche & Paulus, Reference Nitsche and Paulus2000), tDCS appears suitable to enhance processes that depend on synaptic plasticity, like learning and memory processes. Correspondingly, in Ditye's study (Ditye et al., Reference Ditye, Jacobson, Walsh and Lavidor2012), tDCS seemed to act as a necessary condition for an inhibitory control learning effect to occur. However, our extended training sessions produced clear learning curves in both stimulation groups, and we found no support for baseline inhibitory control performance to predict tDCS effectivity. Together with indications that tDCS-enhancement can supersede after experience-dependent learning [see, e.g. Fehring et al. (Reference Fehring, Illipparampil, Acevedo, Jaberzadeh, Fitzgerald and Mansouri2019)], this suggests that tDCS might have had little opportunity to further enhance training processes in our study. Moreover, patients with stress-related disorders may specifically show impulsivity in the emotional domain (Johnson, Carver, & Joormann, Reference Johnson, Carver and Joormann2013), and tDCS effects on cognitive and emotional outcomes seem to depend on active emotion regulation, cognitive effort and neural activity in the targeted area (Gill, Shah-basak, & Hamilton, Reference Gill, Shah-basak and Hamilton2015; Nord et al., Reference Nord, Halahakoon, Limbachya, Charpentier, Lally, Walsh and Roiser2019; Smits et al., Reference Smits, Schutter, van Honk and Geuze2020). Our response inhibition training may have failed to adequately incorporate these factors due to its non-emotional nature and low cognitive load. Also, non-trained inhibitory control tasks (go/no-go task and IAT) showed no evidence for tDCS effects, in line with expectations that effects do not transfer in the absence of tDCS effects on trained tasks (Berryhill & Martin, Reference Berryhill and Martin2018). Altogether, conditions for tDCS efficacy in these patients may crucially include emotionally challenging tasks during stimulation.
Effects of tDCS-combined training on symptoms
In light of the null-effects on inhibitory control, the tDCS intervention would not affect symptom levels of PTSD, anxiety, and aggression via such mediating cognitive processes. On the other hand, tDCS effects on symptoms without concurrent cognitive improvement have previously been shown in depression (Martin et al., Reference Martin, Teng, Lo, Alonzo, Goh, Iacoviello and Loo2018) and PTSD patients (Ahmadizadeh et al., Reference Ahmadizadeh, Rezaei and Fitzgerald2019), suggesting that prefrontal tDCS may also affect symptoms via other mechanisms. However, on stress-related as well as mood symptoms and general mental well-being, no evidence for tDCS effects was found. Possibly, such non-specific tDCS effects require more sessions and a shorter between-session-interval (max. 1 day) (Alonzo, Brassil, Taylor, Martin, & Loo, Reference Alonzo, Brassil, Taylor, Martin and Loo2012). Patients in both stimulation groups did show significant symptom reduction over the course of the intervention, presumably as a result primarily of ongoing therapeutic processes of regular treatment.
Future directions
To find more effective ways to target stress-related symptoms with tDCS, the next steps should be to identify what are the relevant brain processes that facilitate recovery, and to determine under what conditions tDCS effectively modulates those brain processes. Brain state may constitute one of the most important but also unresolved factors of influence on tDCS effectivity. Whereas we intended to attune brain states during the intervention across participants by applying a concurrent cognitive task, the combination with neuroimaging methods can help to better study brain state in parallel to the behavioral and clinical effects of tDCS [see, e.g. Nord et al. (Reference Nord, Halahakoon, Limbachya, Charpentier, Lally, Walsh and Roiser2019)]. Regarding inhibitory control as a cognitive target, exploratory analyses confirmed the association with stress-related symptoms, but not with symptom relief. An alternative target may be tDCS over the dorsolateral PFC (Brunoni & Vanderhasselt, Reference Brunoni and Vanderhasselt2014) to modulate working memory deficits in stress-related disorders [see e.g. Scott et al. (Reference Scott, Matt, Wrocklage, Crnich, Jordan, Southwick and Schweinsburg2015)] which can contribute to symptom relief (Schweizer et al., Reference Schweizer, Samimi, Hasani, Moradi, Mirdoraghi and Khaleghi2017). Successful attempts to enhance effects of cognitive behavioral or exposure psychotherapy with prefrontal stimulation (Herrmann et al., Reference Herrmann, Katzorke, Busch, Gromer, Polak, Pauli and Deckert2017; Nord et al., Reference Nord, Halahakoon, Limbachya, Charpentier, Lally, Walsh and Roiser2019; van ’t Wout-Frank et al., Reference van ’t Wout-Frank, Shea, Larson, Greenberg and Philip2019) also suggest that tDCS interventions might be further developed in existing clinical applications. More placebo-controlled clinical trials are encouraged to examine whether this is a viable option.
Limitations
Limitations in our study may restrict the generalization of our results. First, pre- and post-intervention measures were assessed online. As a trade-off for a lower travel burden for patients (Smits, de Kort, & Geuze, Reference Smits, de Kort and Geuze2021), this could have reduced the measurement sensitivity to detect (possibly weak) tDCS effects. On the other hand, cognitive assessment through online experiments appear reliable (Gladwin & Vink, Reference Gladwin and Vink2020). Also, we carried out this study in an (ex-)military, predominantly male sample. Excluding data from female participants did not essentially change the results, and our sample represented a broad and heterogeneous group, but military personnel in general may represent a relatively homogenous population due to rigid selection and training procedures. Our outcomes may therefore not directly translate to other populations.
Conclusion
The current RCT in military patients with stress-related symptoms provides no evidence for short-term or long-term benefits of 5 sessions of 20-min tDCS targeting the right IFG at an intensity of 1.25 mA combined with response inhibition training, on inhibitory control or PTSD, anxiety, and impulsive aggression symptoms. For these patients, tDCS may be more effective in higher doses (e.g. higher current density, more sessions) or when combined with emotionally challenging tasks or psychotherapy. Gaining insight in determinants of tDCS efficacy and convenient brain targets for neuromodulation in stress-related disorders will allow the tailoring of future tDCS interventions.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0033291721000817
Acknowledgements
We are very thankful to all participants for their valuable contribution to this study, and our coworkers from the Dutch Military Mental Healthcare Organization and from the Brain Research & Innovation Centre for their help in participant recruitment and data acquisition. We also thank the anonymous reviewers for their constructive feedback on this manuscript.
Financial support
This work was supported by the Dutch Ministry of Defence.
Conflict of interest
None.
Data availability statement
The data that support the findings of this study are available from the corresponding author, FS, upon reasonable request.
Open access
