Influence of tDCS on the Brain Activation Measured During the Decision Not to Smoke in High-risk Situations

Investigation of the Influence of Transcranial Direct Current Stimulation (tDCS) on the Brain Activation Measured by fNIRS During the Decision Not to Smoke in High-risk Situations

Substance use disorders (SUD) are characterized by increased automatized responses to drug-related cues (cue-reactivity) and deficient cognitive control. Cue-reactivity (CR) can be elicited by internal (e.g. mood) or external (e.g. situations) cues closely related to consumption. Therefore, one aim for relapse prevention is to control CR by the enhancement of cognitive control, e.g., via noninvasive brain stimulation (NIBS) of cortical areas involved in inhibitory control. However, thus far, treatment effects of NIBS for relapse prevention in SUD are only moderate, despite clear neurophysiological targets. Critically, NIBS is commonly applied in highly standardized laboratory situation, not related to CR, neglecting the current individual (brain-) state. In the current study, relapse-relevant (brain-) states will be evoked in individual, naturalistic settings outside the laboratory and monitored by functional near-infrared spectroscopy (fNIRS; assessing cortical activation patterns) and heartrate variability (HRV; as a periphery physiological measure) to capture the optimal (cortical) state for subsequent NIBS by means of transcranial direct current stimulation (tDCS). The aim of this highly innovative approach is increasing the efficiency of relapse prevention in SUD. At its heart, multimodal measurements during real-world (substance-related) choices with high ecological validity will be used to identify markers for individual optimal target states for tDCS. In contrast to current approaches, the target brain state of the individual adaptively controls the tDCS to maximize therapeutic outcome. One obstacle is to clear the data from artefacts to interpret data at a single-trial level, which requires this proof-of-concept study. This data is prerequisite for further clinical randomized-controlled studies in patients with SUD.

Dependent smokers will be measured in the morning, adjusted to the usual time of getting up or a minimum 4-hour abstinence period. All participants will be measured on two days:

Day 1: First, after written consent to participate in the study, all inclusion and exclusion criteria are checked and standardized questionnaires are collected. To validate the activity in the dorsolateral prefrontal cortex (dlPFC) and in the orbitofrontal cortex (OFC) individually, two "localizer measurements" are performed. For the dlPFC, a go/nogo task will be used with smoke-associated and positive images; for the OFC, the same images from the dlPFC localizer will be used and viewed in a "passive viewing task" that will be pushed away by keypress.

Next, a modified version of a cue exposure follows for 5 min that has already been implemented in preliminary studies (Kroczek et al., 2016, 2017). All smokers have their own cigarettes, a lighter, and an ashtray on a table in front of them. The cue-exposure is done twice, once in a laboratory room and once in a naturalistic smoking setting. This condition is used as training for the Support Vector Machine (SVM).

This is followed by a cue exposure in which smokers are allowed to actually decide whether to smoke a cigarette or to resist. This condition occurs only outside, after the first part of the experiment has taken place. In this "50% condition", participants receive the instruction that they are allowed to take a drag on their cigarette after each prompt and they should take a drag in about half of the trials. Smoking behavior (puff on the cigarette/no puff on the cigarette) and also craving is noted by the experimenter.The goal of the first day is to train the SVM to detect maximum cue-reactivity concurrent to its cognitive control by response inhibition

Day 2: At most one week after time point 1, the SVM will be used to promote the cortical activity state that enables effective cue exposure therapy during the exposure condition in the smoking risk situation. With the aid of SVM, a tDCS intervention should be triggered at the optimal moment to further solidify extinction learning. This cue exposure measurement is used to classify successful inhibition of smoking. The measurement will take place in the naturalistic setting outside and the participants are NOT allowed to smoke but should increase their craving. As soon as the desired activity state is reached, indicated by the SVM, but at the latest after 5 minutes, tDCS is applied.

At the end of the experiment, the subjects will receive an information sheet on the consequences of smoking and information on the services offered by the Smoking Cessation Working Group at the University Hospital of Tübingen. In addition, the participants are psychoeducated that any exposure during the decision not to smoke helps to weaken the addiction memory. Information is provided that accordingly the follow-up survey on the cell phone will also record whether there were situations in which the smokers did not give in to craving in everyday life. This daily query is to take place in the evening over a period of 2 weeks by means of "Ecological Momentary Assessment" (EMA) on the smoker's own cell phone. EMA will be used to assess smoking behavior and potential situations on the current day in which the desire to smoke was triggered without giving in to this desire.

Total time expenditure for the participants will be approximately 3.5 hours, for which they will receive an expense allowance of 10€/hour.

All measurements will take place at the Department of Psychiatry and Psychotherapy of the University Hospital Tübingen in the Laboratory of Psycho-physiology and Optical Imaging (room U81, Osianderstr. 24, 72076 Tübingen) or on a bench close to the hospital.

Sample size:

The sample size is based on a preliminary study by the working group investigating cue exposure and tDCS interventions (Kroczek et al., 2017) with an effect size of d=0.66. Calculating the sample size in a within-subject design, with an alpha of 0.05 and a beta of 0.90 results in a required N of 28. Since the methodology differs from the previous experimental procedure by leaving the laboratory (with additional sources of interference by daylight and movement), additional participants shall be collected to a total sample of N=60.

Demographic data and questionnaires:

Participants' demographic data and information on current medication and handedness (Edinburgh Handedness Inventory (EHI)) will be collected in addition to smoking-related questionnaires including the FTND and Questionnaire on Smoking Urges (QSU-b). Smoking-related self-efficacy and abstinence motivation will also be assessed, in addition to the Positive and Negative Affect Schedule (PANAS), depressed mood (via the BDI-II), the State-Trait Anxiety Inventory, the level of general worry (via the WDQ), impulsivity (BIS-15,UPPS), general self-efficacy (via the SWE) and control beliefs (IE4).

A written follow-up survey about the tDCS will also be conducted to allow for a blinding check.

In addition, visual analog scales for the questions "how strong is your desire to smoke a cigarette" and "how strong is your stress experience" will be completed before and after each measurement.

Hypotheses:

The primary study goal is to quantify context effects. Here, we will examine the influence of context on different levels of cue reactivity.

The second primary study objective is to demonstrate the feasibility of SVM for identifying extinction processes and the feasibility that this SVM-based trigger can be used for tDCS. And lastly, we test the hypothesis that tDCS will have an impact on smoking behavior two weeks after the study.

Another secondary study objective concerns individual factors in the prediction of cue reactivity, immediate smoking in the 50:50 condition and number of smoked cigarettes within 14 days after tDCS.

Inclusion Criteria:

• informed consent
• daily cigarette consumption (already in the first half of the day)

Exclusion Criteria:

Acute or chronic disease (also anamnestic) that may affect brain metabolism:

• pre-existing diabetes mellitus (E10-E14) according to ICD-10
• Renal insufficiency from stage 3 of the Kidney Disease Outcomes Quality Initiative onwards
• Uncontrolled hypertension (I10.x according to ICD-10)
• Moderate or severe traumatic brain injury (GCS 3-12) or 2nd- or 3rd-degree traumatic brain injury with loss of consciousness > 30 min
• Epilepsy (personal or in first-degree relatives).
• Currently present psychiatric or neurological disease
• Regular use of medications that affect blood flow (e.g., ASA).