The Use of Combined Anodal Transcranial Direct Current Stimulation (tDCS) and Cognitive Training to Modulate Decision-making in Healthy People
Phase: NA
Conditions: Impulsivity, Decision Making
Sponsor: Dr. Najat Khalifa

 
 
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Queen’s University  
Centre for Neuroscience Studies and Department of Psychiatry  
Research Protocol 
 
Version 2 
Date: January 20, 2019 
 
 
 
Study Title 
The use of combined Anodal transcranial Direct Current Stimulation (tDCS) and cognitive training 
to modulate decision-making in healthy people  
 
 
Principal Investigator 
Dr. Najat Khalifa, MBChB, MRCPsych, DM 
Associate Professor in Forensic Psychiatry 
Division of Forensic Psychiatry  
Department of Psychiatry, Queen’s University 
c/o Providence Care Hospital  
752 King Street West, Kingston, ON, K7L 4X3. Tel: 616-770-2434 
Email: nrk2@queensu.ca 
 
Co-Investigators  
Dr. Tariq M. Hassan, MBBS, MRCPsych, FRCPC 
Associate Professor 
Divisional Chair and Clinical Director 
Division of Forensic Psychiatry  
Department of Psychiatry  
Queen's University  
Email:   hassant@providencecare.ca  
 
Dr. Katy Jones, PhD 
Assistant Professor of Applied Psychology 
Division of Psychiatry and Applied Psychology  
School of Medicine 
University of Nottingham, UK 
Email: katy.jones@nottingham.ac.uk 
 
Professor Peter Liddle, PhD 
Professor of Psychiatry 
Division of Psychiatry and Applied Psychology  
School of Medicine 
University of Nottingham, UK 

 
 
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Email: peter.liddle@nottingham.ac.uk 
 
Dr. Roumen Milev, MD, PhD, FRCPsych, FRCPC 
Professor of Psychiatry and Psychology 
Director of Centre for Neuroscience Studies 
Division of Community Psychiatry 
Department of Psychiatry, Queen’s University  
Email: milevr@providencecare.ca 
 
Funding and Duration 
Funding Body:  
Department of Psychiatry, Queen’s University 
Duration:  
 
18 months 
Start date:  
 
February 4, 2019 
 
Background 
Decision-making is regarded as a form of goal-directed behaviour that entails forming preferences, 
selecting and performing actions, and evaluating outcomes on choices (Ernst & Paulus, 2005). It is 
underpinned by a complex interaction between affective processing and behavioural regulation 
(Hughes et al., 2016), and this interaction is influenced by the activation of a neuronal circuit 
encompassing several cortical (e.g. ventromedial frontal cortex (vmPFC), dorsolateral prefrontal 
cortex (DLPFC)) and subcortical areas (e.g. amygdala, hippocampus, anterior cingulate cortex) 
(Bechara et al., 1994; Beszterczey et al., 2013). Decision-making overlaps significantly with 
impulsivity, which in turn reflects a failure to plan ahead and inability to control or regulate 
emotions and behaviours, often with negative consequences for the individuals concerned and 
others (Farrington, 2010; Castellanos-Ryan & Séguin, 2015). Deficits in decision-making may 
result in an elevated risk of violent and antisocial behaviour (Howard, 2006;). Therefore, and in 
order to reduce the harm caused by impaired decision-making capacity, the importance of 
developing specific interventions to enhance decision making is paramount.  
 
Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique that 
has been used to modulate brain activity through a weak direct electric current which stimulates 
the brain area beneath the stimulation site and deeper structures through connected neuronal 
networks. tDCS has been used to treat various psychiatric disorders, such as depression (Palm, et 
al., 2016) and Obsessive Compulsive Disorder (Brunelin, et al., 2018). It has been also used to 
modulate decision-making with some promising results (e.g. Ouellet et al., 2015; Casula et al., 
2017).  
 
In recent years, research interest has grown in combining tDCS with cognitive training paradigms 
in the hope of maximizing training benefits, leading to task-specific cognitive enhancement (Filmer 
et al., 2017). Earlier meta-analyses of cognitive training research revealed mixed evidence for 
training effects and generalizability of effects to other tasks (Owen et al., 2010; Shipstead et al., 
2012). However, more recent evidence suggests that combined tDCS and cognitive training can 
enhance performance on tasks designed to assess motor functioning (Stagg et al., 2011), language 
(Flöel et al. 2008), numeracy (Kadosh et al., 2010), decision making (Filmer et al., 2017) and 
inhibitory control (Berkman et al., 2014). Furthermore, Filmer and colleagues reported that 

 
 
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combined tDCS and cognitive training can enhance decision-making and these effects are 
generalizable to both trained and untrained tasks (Filmer et al., 2017).  
 
The proposed study 
Deficits in decision-making under conditions of uncertainty and risk has been implicated in 
maladaptive personality development and violent behaviour (Howard, 2006; Hughes et al; 2016). 
To our knowledge, no studies have examined the effects of combined tDCS and cognitive training 
on decision-making under conditions of uncertainty and risk. It is also unclear if these effects are 
generalizable to tasks in other domains such as response inhibition (also known as motor 
impulsivity).  
 
To examine these issues further, we propose to apply either active or sham tDCS over the anterior 
frontal cortex (including the vm-PFC) while participants undertake decision-making training using 
the Iowa Gambling Task (IGT; Bechara, 2007). Decision-making will be assessed using the IGT, 
which is a computerized gambling task used to assess decision-making under conditions of 
uncertainty and risk. IGT is sensitive to damage to the vmPFC (Bechara et al., 1994), which is 
considered to play a key role in decision-making. Motor impulsivity will be measured using the 
Stop Signal Task (SST). A self-report measure of impulsivity will be used to assess the effects of 
individual differences in trait impulsivity on test results. The UPPS+P Impulsive Behaviour Scale 
(Cyders et al., 2007) will be used to index trait impulsivity.  The Profile of Mood States (POMS; 
Grove & Prapavessis,1992) will be used to measure state emotion before and after tDCS. 
 
Study Aims and Hypothesis 
We aim to (i) assess the effects of combined tDCS and cognitive training on decision-making on the 
trained task (in this case, IGT); and (ii) test generalization to a closely related cognitive domain, 
namely motor impulsivity). Based on the work of others (e.g., Casula et al., 2017; Filmer et al, 
2017; Quellet et al., 2015), we hypothesize that combined anodal tDCS and cognitive training will 
result in more advantageous decisions and better impulse control than sham tDCS.  
 
Methods 
Study Design and Sample 
A single blind parallel arms randomized controlled trial will be conducted, involving a sample of 
healthy volunteers aged between 18 and 40. Eligible participants will be identified using a tDCS 
safety questionnaire (Appendix 1) such that individuals with epilepsy, other neurological 
conditions and history of significant head injury will be excluded. Individuals with a history of 
substance misuse, major mental disorder and those receiving psychotropic medication will be also 
excluded. Participants will be recruited though adverts displayed on notice boards at Queen’s 
University including sports clubs and student societies.  
 
Psychometric tools  
UPPS+P 
The UPPS+P Impulsive Behavior Scale (Cyders et al, 2007) will be used to index impulsivity. 
UPPS+P is a 59 item self-report measure of trait impulsivity with 5 subscales; Negative Urgency, 
(Lack of) Premeditation, (Lack of) Perseverance, Sensation seeking and Positive Urgency. Each 

 
 
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item is rated on a scale of 1-4 (1= totally disagree, 4=totally agree). Higher scores indicate stronger 
presence of these traits. 
 
Profile of Mood States (POMS) 
POMS (Grove & Prapavessis,1992) is a 40-items self-report questionnaire that captures transient, 
distinct mood states. It measures 7 distinct mood states; tension, anger, fatigue, depression, 
esteem related effect, vigour, and confusion. Each item is rated on a scale of 0-4 (0=not at all; 
4=extremely), yielding a Total Mood Disturbance score and scores for 7 mood states. POMS takes 
approximately 5 minutes to complete.  
 
IGT 
The IGT (Bechara, 2007) is a computerized gambling task. Individuals choose from four decks of 
cards (A, B, C, D) which differ in terms of their reward-punishment profiles. Repeated selection 
from decks C and D (advantageous decks) results in an overall net profit; whilst repeated selection 
from the decks A and B (disadvantageous decks) results in greater losses. The main measure of 
performance is the difference between the numbers of choices from the advantageous decks minus 
the number of choices from the disadvantageous decks, giving an overall ‘net’ score.  The IGT takes 
approximately 20 minutes to complete.  
 
SST 
SST is a measure of inhibitory control. SST entails presenting a circle on the computer screen with 
an arrow inside pointing either to the right or left of the screen (the go signal). The participant is 
instructed to use a pad to register their responses by pressing the left hand button on the pad for 
arrows pointing to the left or the right hand button for arrows pointing to the right. The 
participant is instructed to withhold response upon hearing a beeping sound (the auditory stop 
signal) which is randomly generated shortly after the presentation of the arrows in 25% of the 
trials. The task consists of five blocks with 64 trials in each block. The difficulty of the task is 
manipulated by changing the stop signal delay (SSD), which refers to the time interval between the 
go signal and the onset of the stop signal, such that the sooner the stop signal occurs after the 
onset of the go signal, the easier it becomes for the participants to inhibit their responses. Four 
interleaved stepwise functions will be used (100, 200, 400, and 500ms) to make it difficult for the 
participant to predict the onset of the stop signal. The test is calibrated such that the difficulty of 
the next trial is increased following a successful withhold response by increasing the SSD by 50ms. 
Conversely, failure to inhibiting a response reduces the difficulty of the next trial by reducing the 
SSD by 50ms. Stop Signal Reaction Time (SSRT) is the primary outcome measure for SST. It is 
defined as the mean reaction time on go trials minus the mean SSD at which the participant 
successfully withholds a response on 50% of the trials. Lower SSRT values corresponds to poorer 
response inhibition. The task takes approximately 15 minutes to complete. 
 
tDCS 
Soterix tDCS kit will be used to deliver the stimulation using two sponge electrodes soaked in 
saline. The stimulation montage will comprise of anterior PFC anodal or sham stimulation. The 
anodal electrode will be placed over the area corresponding to the anterior PFC (FpZ of the 
EEG10–20 international system) and the reference (cathodal) electrode over the posterior 
occipital area (OZ of the EEG10–20 international system). This montage has been utilized in other 

 
 
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studies to stimulate the anterior OFC (Casula et al., 2016; Fumagalli et al., 2010). It is considered to 
enhance the anterior-posterior current flow via the vmPFC region of the anterior PFC and to 
reduce the lateral shunting along the skin (Casula et al., 20; Fumagalli et al., 2010). 
 
The active stimulation condition will use a constant current of 2mA, delivered via gradual increase 
and decrease over 10 seconds at the onset and offset of stimulation (current ramps), respectively. 
For sham stimulation, the current will be delivered only in the first 10 seconds, after which the 
stimulation will cease but with the electrodes still in place throughout the session. The duration of 
each tDCS session will be 20 minutes.   
 
Procedure 
A brief overview of the experiment is provided in figure 1 below. The experiment is divided into 
three phases (baseline, cognitive training, endpoint). In the first phase, participants will be asked 
to complete the UPPS+P Impulsive Behaviour Scale, POMS, SST and IGT.  In the second phase, 
participants will undertake cognitive training by repeating the IGT with either anodal or sham 
tDCS applied over the anterior PFC.  In the third phase, the participant will repeat the POMS, IGT 
and SST. Additionally, a tDCS adverse effects questionnaire (Appendix 2) will be administered at 
the end of the experiment to detect adverse effects.   
   
 
Figure 1: Experiment Overview 
 
 
Statistical Analysis 
A power calculation conducted using an independent-samples t-test (G*Power) yielded a total 
sample size of 60 participants (effect size=0.65, power=80%, α = 0.05, one tailed testing). Data will 
be analyzed using the Statistical Package for Social Sciences (SPSS). A Repeated Measures ANOVA 
will be performed with group allocation (active tDCS vs. sham) and time (pre- vs. post-tDCS 
stimulation). Mean scores on UPPS+P will be entered into the model as co-variates. Within-subject 
factors will be used to compare changes in outcome variables between the groups over time. A p 
value of < 0.05 will be considered as statistically significant. 
 
 
Baseline
- POMS (5 min) 
- UPPS+P (10 min)
- SST (15 min)
- IGT (20 min) 
Combined tDCS + 
cognitive Training
- IGT 
- Anodal or sham tDCS 
Endpoint
- POMS (5 min)
- SST (15 min)
- IGT  (20 min)
- tDCS adverse effects   
questionnaire (5 min)

 
 
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Research ethics approval and informed consent 
Research ethics approval will be obtained from the Health Sciences and Affiliated Teaching 
Hospitals Research Ethics Board (HSREB) at Queen’s University. Written informed consent will be 
obtained from all participants.  Eligible participants will be selected carefully using a tDCS safety 
questionnaire (Appendix 1). Each participant will be assigned a unique identity code, and no 
participant identifiable information will appear on paper or electronic data formats. A code 
breaker will be saved on a secure University computer that is only accessible to the research team 
and other authorized individuals within Queen’s University.  
 
Research management  
A Research Management Group comprising study investigators will be established to manage the 
overall governance of the project and day-to-day operations. The group will meet monthly to 
discuss progress and to ensure that the study is conducted in accordance with the requirements of 
the research ethics approval. 
 
Expected Impact of Research Proposal 
There currently exist no specific interventions to target impaired decision making. The proposed 
study will assess whether combined tDCS (applied over the anterior PFC) and cognitive training 
can enhance decision making and impulse control. Further funding will be sought to develop the 
concept on a wider scale to examine the neurobiological underpinning of decision making, for 
instance, by combing tDCS and cognitive training with neuroimaging techniques such as fMRI or 
MEG.  
 
Resources and the Research Team 
The study will be conducted under the auspices of the Centre for Neuroscience and Department of 
Psychiatry at Queen’s University. The Neuroconn tDCS or Soterix kit will be purchased via the 
relevant supplier.  
 
Dr. Khalifa, Dr. Jones and Professor Liddle have expertise in brain stimulation, impulsivity and 
decision-making research. Professor Liddle is a world-renowned expert in neuroimaging and 
psychiatry research. Together, they are currently conducting a concurrent tDCS - 
Magnetoencephalography (MEG) study, examining the cortical correlates of impulsivity. Dr. Tariq 
Hasan is an established senior clinical academic with a track record of academic achievements. 
Professor Milev is the Director of Centre for Neuroscience Studies, Queen’s University. Between 
2007 and 2017 he was the Head of Department of Psychiatry at Queen’s University between. He is 
actively involved in research with patients with Depression, Bipolar Disorder, Anxiety Disorders, 
and other Affective Disorders. Main areas of his research include issues of Stigma and ways of 
dealing with it, Sleep architecture, psychopharmacological and rTMS treatments.  
 
 
 
 
 
 
 
 

 
 
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References 
1. Bechara, A., Damasio, A.R., Damasio, H. & Anderson, S.W. (1994). Insensitivity to future 
consequences following damage to human prefrontal cortex. Cognition, 50, 7-15. 
2. Bechara, A. (2007). Iowa Gambling Task. Psychological Assessment Resources, Inc. USA. 
3. Berkman, E.T., Kahn, L.E., & Merchant, J.S. (2014). Training-Induced Changes in Inhibitory 
Control Network Activity. The Journal of Neuroscience, 34(1):149 –157. 
4. Beszterczey, S., Nestor, P. G., Shirai, A., & Harding, S. (2013). Neuropsychology of decision 
making and psychopathy in high-risk ex-offenders. Neuropsychology, 27(4), 491. 
5. Brunelin, J., Mondino, M., Bation, R., Palm, U., Saoud, M., & Poulet, E. (2018). Transcranial 
Direct Current Stimulation for Obsessive-Compulsive Disorder: A Systematic Review. Brain 
Science, 8(2): 37. doi:  10.3390/brainsci8020037 
6. Cambridge Cognition. (2016). CANTAB® [Cognitive assessment software]: CANTAB 
Technology. 
7. Castellanos-Ryan, N., & Séguin, J. R. (2015). Prefrontal and Anterior Cingulate Cortex 
Mechanisms of Impulsivity. Beauchaine, T. P. & Stephen P. Hinshaw, S. P. (editors). The 
Oxford Handbook of Externalizing Spectrum Disorders. Oxford University Press – New 
York. DOI: 10.1093/oxfordhb/9780199324675.013.13 
8. Casula, E.P., Testa, G., Bisiacchi, P.S. et al. (2017).  Journal Cognitive Enhancement, 1:318. 
doi.org/10.1007/s41465-017-0030-7. 
9. Cyders, M. A., Smith, G. T., Spillane, N. S., Fischer, S., Annus, A. M., & Peterson, C. (2007). 
Integration of impulsivity and positive mood to predict risky behavior: Development and 
validation of a measure of positive urgency. Psychological Assessment, 19(1), 107-118. 
doi:10.1037/1040-3590.19.1.107 
10. Ernst, M., & Paulus, M. P. (2005). Neurobiology of decision making: a selective review from 
a neurocognitive and clinical perspective. Biological Psychiatry, 58(8), 597-604. 
11. Farrington, D. P. (2010). The developmental evidence base: psychosocial research. In Towl. 
G. J. & Crighton, D. A. (eds). Forensic Psychology. BPS Blackwell. Blackwell Publishing Ltd.  
12. Filmer, H.L., Varghese, E., Hawkins, G.E., Mattingley, J.B. & Dux, P. E. (2017). Improvements 
in Attention and Decision-Making Following Combined Behavioral Training and Brain 
Stimulation. Cerebral Cortex, 27: 3675–3682. 
13. Fumagalli, M., Vergari, M., Pasqualetti, P., Marceglia, S., Mameli, F., Ferrucci, R., Mrakic-
Sposta, S., Zago, S., Sartori, G., Pravettoni, G., Barbieri, S., Cappa, S., & Priori, A. (2010). Brain 
switches utilitarian behavior: does gender make the difference? PloS One, 5(1), e8865. 
14. Flöel, A., Rösser, N., Michka, O., Knecht, S., & Breitenstein, C. (2008). Noninvasive brain 
stimulation improves language learning. Journal of Cognitive Neuroscience, 20(8):1415–
1422. 
15. Grove, J.R., & Prapavessis, H.  (1992). Preliminary evidence for the reliability and validity of 
an abbreviated Profile of Mood States. International Journal of Sport Psychology, 23, 93-109. 
16. Howard, R. (2006). How is personality disorder linked to dangerousness? A putative role 
for early-onset alcohol abuse. Medical Hypotheses, 67, 702–708. 
17. Hughes, M. A., Dolan, M. C., & Stout, J. C. (2016). Decision-making in Psychopathy. Psychiatry, 
Psychology and Law, 23(4), 521-537. 

 
 
tDCS for Decision Making 
Page 8 
 
18. Kadosh, R.C., Soskic, S., Iuculano, T., Kanai, R., & Walsh, V. (2010). Modulating neuronal 
activity produces specific and long-lasting changes in numerical competence. Current 
Biology, 20 (22):2016–2020. 
19. Palm, U., Hasan, A., Strube, W., Padberg, F. (2016). tDCS for the treatment of depression: a 
comprehensive review. European Archives of Psychiatry and Clinical Neuroscience, 
266(8):681-694.  
20. Ouellet, J., McGirr, A., Van den Eynde, F., Jollant, F., Lepage, M., & Berlim, M.T. (2015). 
Enhancing decision-making and cognitive impulse control with transcranial direct current 
stimulation (tDCS) applied over the orbitofrontal cortex (OFC): A randomized and sham-
controlled exploratory study. Journal of Psychiatric Research, 69, 27-34. 
21. Owen, A.M., Hampshire, A., Grahn, J.A., Stenton, R., Dajani, S., Burns, A.S., Howard, R.J., & 
Ballard, C.G. (2010) Putting brain training to the test. Nature, 465: 775–778. 
22. Shipstead, Z, Hicks, K.L., & Engle, R.W. (2012) Cogmed working memory training: does the 
evidence support the claims? Journal of Applied Research in Memory and Cognition 1:185–
193.