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.
Age range
18 Years – 70 Years
Sex
ALL
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Craving ratings
Timeframe: Measurement day 1
Prefrontal fNIRS activity
Timeframe: Measurement day 1
Activity of the sympathetic nervous system (SNS)
Timeframe: Measurement day 1
Activity of the parasympathetic nervous system (PNS): Heart-rate variability (HRV)
Timeframe: Measurement day 1
Functional connectivity of dlPFC and OFC (fNIRS data)
Timeframe: Measurement day 1
Multimodal SVM craving classifiers
Timeframe: Measurement day 1
Efficacy of extinction learning
Timeframe: 14 days after measurement day 2
Agnes Kroczek, Dr.