Resting state oscillations suggest a motor component of Parkinson's Impulse Control Disorders

Electroencephalogram-Driven Machine-Learning Scenario for Assessing Impulse Control Disorder Comorbidity in Parkinson's Disease Using a Low-Cost, Custom LEGO-Like Headset

Patients with Parkinson's disease (PD) may develop cognitive symptoms of impulse control disorders (ICDs) when chronically treated with dopamine agonist (DA) therapy for motor deficits. Motor and cognitive comorbidities critically increase the disability and mortality of the affected patients. This study proposes an electroencephalogram (EEG)-driven machine-learning scenario to automatically assess ICD comorbidity in PD. We employed a classic Go/NoGo task to appraise the capacity of cognitive and motoric inhibition with a low-cost, custom LEGO-like headset to record task-relevant EEG activity. Further, we optimized a support vector machine (SVM) and support vector regression (SVR) pipeline to learn discriminative EEG spectral signatures for the detection of ICD comorbidity and the estimation of ICD severity, respectively. With a dataset of 21 subjects with typical PD, 9 subjects with PD and ICD comorbidity (ICD), and 25 healthy controls (HC), the study results showed that the SVM pipeline differentiated subjects with ICD from subjects with PD with an accuracy of 66.3% and returned an around-chance accuracy of 53.3% for the classification of PD versus HC subjects without the comorbidity concern. Furthermore, the SVR pipeline yielded significantly higher severity scores for the ICD group than for the PD group and resembled the ICD vs. PD distinction according to the clinical questionnaire scores, which was barely replicated by random guessing. Without a commercial, high-precision EEG product, our demonstration may facilitate deploying a wearable computer-aided diagnosis system to assess the risk of DA-triggered cognitive comorbidity in patients with PD in their daily environment.

Disruption of the Cortical-Vagal Communication Network in Parkinson's Disease

Parkinson's disease (PD) is a neuropathy characterized by motor disorders, but it has also been associated with the presence of autonomic alterations as a result of degradation of the dopaminergic system. Studying the relation between Band Power time series (BPts) and Heart Rate Variability (HRV), has been proposed as a tool to explore the bidirectional communication pathways between cortex and autonomic control. This work presents a primer analysis on study brain ↔ heart interaction on a databse of PD patients under two conditions: without and after levadopa (L-dopa) intake. Additionally a healthy control population was also analyzed, and used as comparison level between both conditions. Results show PD affects pathways by reducing the number of connections, specially association of beta and power and the second faster component of HRV seems to be more sensitive to L-dopa administration.

Subthalamic low-frequency oscillations predict vulnerability to cocaine addiction

Identifying vulnerable individuals before they transition to a compulsive pattern of drug seeking and taking is a key challenge in addiction to develop efficient prevention strategies. Oscillatory activity within the subthalamic nucleus (STN) has been associated with compulsive-related disorders. To study compulsive cocaine-seeking behavior, a core component of drug addiction, we have used a rat model in which cocaine seeking despite a foot-shock contingency only emerges in some vulnerable individuals having escalated their cocaine intake. We show that abnormal oscillatory activity within the alpha/theta and low-beta bands during the escalation of cocaine intake phase predicts the subsequent emergence of compulsive-like seeking behavior. In fact, mimicking STN pathological activity in noncompulsive rats during cocaine escalation turns them into compulsive ones. We also find that 30 Hz, but not 130 Hz, STN deep brain stimulation (DBS) reduces pathological cocaine seeking in compulsive individuals. Our results identify an early electrical signature of future compulsive-like cocaine-seeking behavior and further advocates the use of frequency-dependent STN DBS for the treatment of addiction.

Inhibitory control dysfunction in parkinsonian impulse control disorders

Impulse control disorders (ICDs) in Parkinson's disease have been associated with dysfunctions in the control of value- or reward-based responding (choice impulsivity) and abnormalities in mesocorticolimbic circuits. The hypothesis that dysfunctions in the control of response inhibition (action impulsivity) also play a role in Parkinson's disease ICDs has recently been raised, but the underlying neural mechanisms have not been probed directly. We used high-resolution EEG recordings from 41 patients with Parkinson's disease with and without ICDs to track the spectral and dynamical signatures of different mechanisms involved in inhibitory control in a simple visuomotor task involving no selection between competing responses and no reward to avoid potential confounds with reward-based decision. Behaviourally, patients with Parkinson's disease with ICDs proved to be more impulsive than those without ICDs. This was associated with decreased beta activity in the precuneus and in a region of the medial frontal cortex centred on the supplementary motor area. The underlying dynamical patterns pinpointed dysfunction of proactive inhibitory control, an executive mechanism intended to gate motor responses in anticipation of stimulation in uncertain contexts. The alteration of the cortical drive of proactive response inhibition in Parkinson's disease ICDs pinpoints the neglected role the precuneus might play in higher order executive functions in coordination with the supplementary motor area, specifically for switching between executive settings. Clinical perspectives are discussed in the light of the non-dopaminergic basis of this function.