Abstract
Addictive disorders are a severe health concern. Conventional therapies have just moderate success and the probability of relapse after treatment remains high. Brain stimulation techniques, such as transcranial Direct Current Stimulation (tDCS) and Deep Brain Stimulation (DBS), have been shown to be effective in reducing subjectively rated substance craving. However, there are few objective and measurable parameters that reflect neural mechanisms of addictive disorders and relapse. Key electrophysiological features that characterize substance related changes in neural processing are Event-Related Potentials (ERP). These high temporal resolution measurements of brain activity are able to identify neurocognitive correlates of addictive behaviours. Moreover, ERP have shown utility as biomarkers to predict treatment outcome and relapse probability. A future direction for the treatment of addiction might include neural interfaces able to detect addiction-related neurophysiological parameters and deploy neuromodulation adapted to the identified pathological features in a closed-loop fashion. Such systems may go beyond electrical recording and stimulation to employ sensing and neuromodulation in the pharmacological domain as well as advanced signal analysis and machine learning algorithms. In this review, we describe the state-of-the-art in the treatment of addictive disorders with electrical brain stimulation and its effect on addiction-related neurophysiological markers. We discuss advanced signal processing approaches and multi-modal neural interfaces as building blocks in future bioelectronics systems for treatment of addictive disorders.
Highlights
Addictive disorders represent a severe health issue and a high economic burden on society
Assessment of craving in humans is usually performed using questionnaires which consist of selfratings on statements reflecting urges, desires and intent of substance consumption, anticipation of positive/negative outcome and relief from withdrawal as well as lack of control of substance consumption (e.g. Alcohol Craving Questionnaire (ACQ) (Singleton et al 1994), Marihuana Craving Questionnaire (MCQ) (Heishman et al 2001), Questionnaire on Smoking Urges (QSU) (Tiffany and Drobes 1991))
In the following review we describe neurobiological and electrophysiological parameters associated with craving behaviour in substance use disorders (SUD)
Summary
Addictive disorders represent a severe health issue and a high economic burden on society. Assessment of craving in humans is usually performed using questionnaires which consist of selfratings on statements reflecting urges, desires and intent of substance consumption, anticipation of positive/negative outcome and relief from withdrawal as well as lack of control of substance consumption (e.g. Alcohol Craving Questionnaire (ACQ) (Singleton et al 1994), Marihuana Craving Questionnaire (MCQ) (Heishman et al 2001), Questionnaire on Smoking Urges (QSU) (Tiffany and Drobes 1991)). These assessments have been exposed to criticism as there is neither a consistent definition of craving nor a conclusive opinion about its. Craving is associated with changes in neurotransmitter contents within these areas as revealed by measurements using implanted biosensors in rodent models that received drug injections, selfadministered drugs via lever pressing or showed druginduced conditioned place preference
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