Biomarkers and neuromodulation techniques in substance use disorders

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.

A Multimodal Neuroprosthetic Interface to Record, Modulate and Classify Electrophysiological Biomarkers Relevant to Neuropsychiatric Disorders

“…These processes also express as altered neural activity patterns that are supposed to normalize when neuromodulation is applied to improve behavior control and decrease relapse risk. First studies using tDCS to correct neural disturbances in substance use disorders could positively affect N2 and P3 components (for review see ( Habelt et al, 2020 )). In our study, implant-driven direct cortical stimulation successfully enhanced the N1, P2 or N2 components at most channels, indicating improved auditory processing, sensory gating and enhanced perception of the deviant stimulus.…”

A multimodal neuroprosthetic interface to record, modulate and classify electrophysiological correlates of cognitive function

“…These processes also express as altered neural activity patterns that are supposed to normalise when neuromodulation is applied to improve behaviour control and decrease relapse risk. First studies using tDCS to correct neural disturbances in substance use disorders could positively affect N2 and P3 components (for review see (58)). In our study, implant-driven direct cortical stimulation successfully enhanced the N1, P2 or N2 components at most channels, indicating improved auditory processing, sensory gating and enhanced perception of the deviant stimulus.…”

New Paradigms of Old Psychedelics in Schizophrenia

“…Biomarkers in neuropsychiatry are becoming immensely important and are playing a key role in facilitating diagnosis of the disorders, and the specific targeting of such biomarkers is helping in targeted treatments [ 131 ]. The findings of brain imaging studies have demonstrated an increase in the activation of neuronal structures involved in attention, reward perception, action selection, decision making and behaviour control following response to a drug therapy [ 132 ] in several brain regions [ 133 , 134 , 135 ], and altered neurochemicals in these brain areas was linked to drug craving [ 136 ]. Dopamine is a key neurotransmitter involved in various processes associated with cognition such as execution, decision-making, and planning, and also reinforces actions associated with reward and positive thinking [ 136 ].…”