Craving and Neurophysiological Markers in Patients with Illicit Substances Use Disorder

Substance us disorder is a serious social and public health problem worldwide. The major illicit drugs are methamphetamine, heroin, and ketamine, while the major type of new psychoactive substances (NPS) is synthetic cathinones in Taiwan. There are currently no pharmacological interventions available to treat the use of METH, ketamine or NPS. For patients with substance use disorder, craving is a key challenge in cognitive behavioral therapy and individuals’ attempts at abstinence.　The hypothesis of this study is that there exist common and differential neurophysiological characteristics in related to craving in patients abusing METH, ketamine and NPS and that their cravings are affected by the interaction of personal characteristics, types of abused substance and length of abstinence. We aim to detect neurophysiological markers of craving in patients with illicit substances use disorder, with special focuses on METH, ketamine and NPS. In this 3-years study, we aim to recruit 120 patients with illicit substances use disorder, including estimated 60 with exclusively METH use disorder, 60 with ketamine use disorder, NPS use disorder or poly-drug use disorder, as well as 60 healthy controls. We will assess the patients by Diagnostic Interview for Genetic Studies (DIGS) to ascertain the DSM-5 diagnoses. Psychiatric symptoms and craving will be assessed using the Positive and Negative Syndrome Scale (PANSS), Becker Depression Inventory (BDI), Becker Anxiety Inventory (BAI), and The Visual Analog Scale for Craving (VASc). Frequency and quantity of illicit substance use in the past 30 days will be recorded using Time-line follow-back (TLFB) method. EEG data and peripheral signals including electrocardiography (ECG), respiratory rate, skin conductance, blood volume pulse, and temperature will be collected in resting states, Balloon Analogue Risk Task (BART) and cue reactivity paradigms. EEG feature selection and classification will be analyzed based on machine learning. We will also associate these changes in craving, EEG and peripheral signals with brain changes from magnetic resonance imaging. We hope the neurophysiological markers identified in this study could be applied to develop treatment programs, such as biofeedback or neurofeedback, for psychoactive substance use disorder in the future.

Project ID:PC10907-1543
External Project ID:MOST109-2314-B182-046