Electrophysiological Biomarkers Research Articles

Aperiodic (1/f) neural activity robustly tracks symptom severity changes in treatment-resistant depression.

A reliable physiological biomarker for Major Depressive Disorder is essential for developing and optimizing neuromodulatory treatment paradigms. This study investigates a passive electrophysiologic biomarker that tracks changes in depressive symptom severity on the order of minutes to hours. We analyze brief recordings from intracranial electrodes implanted deep in the brain during a clinical trial of deep brain stimulation for treatment-resistant depression in 5 human subjects (nfemale= 3, nmale = 2). This surgical setting allows for precise temporal and spatial sensitivity in the ventromedial prefrontal cortex, a challenging area to measure. We focused on the aperiodic slope of the power spectral density, a metric reflecting the balance of activity across all frequency bands and serving as a proxy for excitatory/inhibitory balance in the brain. Our findings demonstrate that shifts in aperiodic slope correlate with depression severity, with flatter (less negative) slopes indicating reduced depression severity. This significant correlation was observed in all N=5 subjects, particularly in the ventromedial prefrontal cortex. This biomarker offers a new way to track patient responses to Major Depressive Disorder treatment, paving the way for individualized therapies in both intracranial and non-invasive monitoring contexts.

A Commentary: Invisibility of Older African-American Adults in Electrophysiological Research on Alzheimer's Disease.

Currently, researchers are examining the feasibility of integrating electrophysiological biomarkers in the clinical assessment of older adults (≥65 years of age) with Alzheimer's disease (AD). This research has been executed predominantly in older Caucasian adults. Older African-American adults have not been effectively recruited for this research. This issue has resulted in a significant gap in the literature about electrophysiological biomarkers and potential clinical utility in assessing for and diagnosing AD in older African-American adults. To share an opinion about the invisibility of older African-American adults in electrophysiological research on AD and potential outcome their inclusion can have on the integration of electrophysiological biomarkers into clinical practice. For this commentary, it was necessary to determine the status of older African-American adults in electrophysiological research. Studies were identified using the search engines PUBMED, CINAHL, Elsevier, and Scopus with a time range of between 2016 and 2022. Nineteen peer-reviewed studies supported this commentary. In older Caucasian adults with AD, electrophysiological biomarkers were associated with the onset and progression of AD. These biomarkers related to the cognitive impairment of AD and its manifestations. There were no studies characterizing any electrophysiological biomarkers in older African-American adults with AD. Research is growing to support the integration of electrophysiological biomarkers into clinical practice. The invisibility of older African-American adults in this research affects the reliability of electrophysiological biomarkers and their application to persons with AD in racially diverse groups. This invisibility also contributes to health disparities confronting older African-American adults with AD and their caregivers.

Cyclic Alternating EEG Patterns: From Sleep to Encephalopathy.

In the 2021 version of the Standardized Critical Care EEG Terminology, the American Clinical Neurophysiology Society introduced new definitions, including for the cyclic alternating pattern of encephalopathy (CAPE). CAPE refers to changes in background EEG activity, with two patterns alternating spontaneously in a regular manner. CAPE shares remarkable similarities with the cyclic alternating pattern, a natural EEG phenomenon occurring in normal non-rapid eye movement sleep, considered the main electrophysiological biomarker of sleep instability. This review explores similarities and differences between cyclic alternating pattern and CAPE and, leveraging the existing expertise on cyclic alternating pattern, aims to extend knowledge on CAPE. A standardized assessment of CAPE features is key to ascertain its prevalence and clinical significance among critically ill patients and to encompass the impact of confounding factors such as anesthetic and sedative agents. Although the preservation of non-rapid eye movement sleep-related elements has a well-known prognostic value in the critical care setting, the clinical importance of cyclic oscillating patterns and the prognostic significance of CAPE remain to be elucidated.

Motor unit number index in Bell's palsy: A potential electrophysiological biomarker for early evaluation.

Reliable, noninvasive early diagnostics of neuromuscular function in Bell's palsy, which causes facial paralysis and reduced quality of life, remain to be established. Here, we aimed to evaluate the utility of the motor unit number index (MUNIX) for the quantitative electrophysiological assessment of early-stage Bell's palsy, its correlation with clinical assessments, changes following treatment, and association with clinical prognosis. MUNIX measures were recorded from the bilateral zygomaticus, orbicularis oculi, and orbicularis oris muscles of 10 healthy individuals and 64 patients with Bell's palsy. The patients were assessed by two specialist neurologists using the House-Brackmann and Sunnybrook Facial Grading Systems. Repeat assessments were performed on 20 patients with Bell's palsy who received treatment. Additionally, the 64 patients were reassessed using clinical scales after a 1-month interval. The MUNIX values of the main affected muscles on the affected side were lower than those on the healthy side in patients with Bell's palsy (p<.05). The MUNIX measurements significantly correlated with the clinical facial nerve palsy scale scores (p<.05). Significant improvements were observed in the MUNIX values on repeat testing following treatment (p<.05). The baseline motor unit size index (the compound muscle action potential amplitude divided by MUNIX) was positively associated with improved clinical presentation after 1 month (p<.05). MUNIX can be used as an electrophysiological biomarker for the quantitative assessment of facial nerve palsy and treatment response, and as a prognostic biomarker, in patients with early Bell's palsy, and is recommended as a complement to conventional neurophysiological examinations.

Electrophysiological predictors of early response to antidepressants in major depressive disorder

BackgroundPsychomotor retardation (PMR) is a core feature of major depressive disorder (MDD), which is characterized by abnormalities in motor control and cognitive processes. PMR in MDD can predict a poor antidepressant response, suggesting that PMR may serve as a marker of the antidepressant response. However, the neuropathological relationship between treatment outcomes and PMR remains uncertain. Thus, this study examined electrophysiological biomarkers associated with poor antidepressant response in MDD. MethodsA total of 142 subjects were enrolled in this study, including 49 healthy controls (HCs) and 93 MDD patients. All participants performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. Patients who exhibited at least a 50 % reduction in disorder severity at the endpoint (>2 weeks) were considered to be responders. Motor-related beta desynchronization (MRBD) and inter- and intra-hemispheric functional connectivity were measured in the bilateral motor network. ResultsAn increased MRBD and decreased inter- and intra-hemispheric functional connectivity in the motor network during movement were observed in non-responders, relative to responders and HCs. This dysregulation predicted the potential antidepressant response. ConclusionAbnormal local activity and functional connectivity in the motor network indicate poor psychomotor function, which might cause insensitivity to antidepressant treatment. This could be regarded as a potential neural mechanism for the prediction of a patient's treatment response.

Prediction of Cognitive Heterogeneity in Parkinson's Disease: A 4-Year Longitudinal Study Using Clinical, Neuroimaging, Biological and Electrophysiological Biomarkers.

Cognitive impairment in Parkinson's disease (PD) can show a very heterogeneous trajectory among patients. Here, we explored the mechanisms involved in the expression and prediction of different cognitive phenotypes over 4 years. In 2 independent cohorts (total n = 475), we performed a cluster analysis to identify trajectories of cognitive progression. Baseline and longitudinal level II neuropsychological assessments were conducted, and baseline structural magnetic resonance imaging, resting electroencephalogram and neurofilament light chain plasma quantification were carried out. Linear mixed-effects models were used to study longitudinal changes. Risk of mild cognitive impairment and dementia were estimated using multivariable hazard regression. Spectral power density from the electroencephalogram at baseline and source localization were computed. Two cognitive trajectories were identified. Cluster 1 presented stability (PD-Stable) over time, whereas cluster 2 showed progressive cognitive decline (PD-Progressors). The PD-Progressors group showed an increased risk for evolving to PD mild cognitive impairment (HR 2.09; 95% CI 1.11-3.95) and a marked risk for dementia (HR 4.87; 95% CI 1.34-17.76), associated with progressive worsening in posterior-cortical-dependent cognitive processes. Both clusters showed equivalent clinical and sociodemographic characteristics, structural magnetic resonance imaging, and neurofilament light chain levels at baseline. Conversely, the PD-Progressors group showed a fronto-temporo-occipital and parietal slow-wave power density increase, that was in turn related to worsening at 2 and 4 years of follow-up in different cognitive measures. In the absence of differences in baseline cognitive function and typical markers of neurodegeneration, the further development of an aggressive cognitive decline in PD is associated with increased slow-wave power density and with a different profile of worsening in several posterior-cortical-dependent tasks. ANN NEUROL 2024;96:981-993.

The impact of subclinical psychotic symptoms on delay and effort discounting: Insights from behavioral, computational, and electrophysiological methods

BackgroundThe ability to value rewards is crucial for adaptive behavior and is influenced by the time and effort required to obtain them. Impairments in these computations have been observed in patients with schizophrenia and may be present in individuals with subclinical psychotic symptoms (PS). MethodsIn this study, we employed delay and effort-discounting tasks with food rewards in thirty-nine participants divided into high and low levels of PS. We investigated the underlying mechanisms of effort-discounting through computational modelling of dopamine prefrontal and subcortical circuits and the electrophysiological biomarker of both delay and effort-discounting alterations through resting-state frontal alpha asymmetry (FAA). ResultsResults revealed greater delay discounting in the High PS group compared to the Low PS group but no differences in the effort discounting task. However, in this task, the same levels of estimated dopamine release were associated with a lower willingness to exert effort for high-calorie food rewards in High PS participants compared to Low PS participants. Although there were no significant differences in FAA between the High PS and Low PS groups, FAA was significantly associated with the severity of participants' negative symptoms. ConclusionsOur study suggests that the dysfunction in temporal and effort cost computations, seen in patients with schizophrenia, may be present in individuals with subclinical PS. These findings provide valuable insight into the early vulnerability markers (behavioral, computational, and electrophysiological) for psychosis, which may aid in the development of preventive interventions. These findings are preliminary and warrant further investigation.

Sleep EEG signatures in mouse models of 15q11.2-13.1 duplication (Dup15q) syndrome

BackgroundSleep disturbances are a prevalent and complex comorbidity in neurodevelopmental disorders (NDDs). Dup15q syndrome (duplications of 15q11.2-13.1) is a genetic disorder highly penetrant for NDDs such as autism and intellectual disability and it is frequently accompanied by significant disruptions in sleep patterns. The 15q critical region harbors genes crucial for brain development, notably UBE3A and a cluster of gamma-aminobutyric acid type A receptor (GABAAR) genes. We previously described an electrophysiological biomarker of the syndrome, marked by heightened beta oscillations (12-30 Hz) in individuals with Dup15q syndrome, akin to electroencephalogram (EEG) alterations induced by allosteric modulation of GABAARs. Those with Dup15q syndrome exhibited increased beta oscillations during the awake resting state and during sleep, and they showed profoundly abnormal NREM sleep. This study aims to assess the translational validity of these EEG signatures and to delve into their neurobiological underpinnings by quantifying sleep physiology in chromosome-engineered mice with maternal (matDp/ + mice) or paternal (patDp/ + mice) inheritance of the full 15q11.2-13.1-equivalent duplication, and mice with duplication of just the UBE3A gene (Ube3a overexpression mice; Ube3a OE mice) and comparing the sleep metrics with their respective wildtype (WT) littermate controls.MethodsWe collected 48-h EEG/EMG recordings from 35 (23 male, 12 female) 12–24-week-old matDp/ + , patDp/ + , Ube3a OE mice, and their WT littermate controls. We quantified baseline sleep, sleep fragmentation, spectral power dynamics during sleep states, and recovery following sleep deprivation. Within each group, distinctions between Dup15q mutant mice and WT littermate controls were evaluated using analysis of variance (ANOVA) and student’s t-test. The impact of genotype and time was discerned through repeated measures ANOVA, and significance was established at p < 0.05.ResultsOur study revealed that across brain states, matDp/ + mice mirrored the elevated beta oscillation phenotype observed in clinical EEGs from individuals with Dup15q syndrome. Time to sleep onset after light onset was significantly reduced in matDp/ + and Ube3a OE mice. However, NREM sleep between Dup15q mutant and WT littermate mice remained unaltered, suggesting a divergence from the clinical presentation in humans. Additionally, while increased beta oscillations persisted in matDp/ + mice after 6-h of sleep deprivation, recovery NREM sleep remained unaltered in all groups, thus suggesting that these mice exhibit resilience in the fundamental processes governing sleep-wake regulation.ConclusionsQuantification of mechanistic and translatable EEG biomarkers is essential for advancing our understanding of NDDs and their underlying pathophysiology. Our study of sleep physiology in the Dup15q mice underscores that the beta EEG biomarker has strong translational validity, thus opening the door for pre-clinical studies of putative drug targets, using the biomarker as a translational measure of drug-target engagement. The unaltered NREM sleep may be due to inherent differences in neurobiology between mice and humans. These nuanced distinctions highlight the complexity of sleep disruptions in Dup15q syndrome and emphasize the need for a comprehensive understanding that encompasses both shared and distinct features between murine models and clinical populations.

DBScope as a versatile computational toolbox for the visualization and analysis of sensing data from deep brain stimulation

Different neurostimulators for deep brain stimulation (DBS) come already with the ability to chronically sense local field potentials during stimulation. This invaluable new data has the potential to increase our understanding of disease-related brain activity patterns, their temporal evolution, and their modulation in response to therapies. It also gives the opportunity to unveil new electrophysiological biomarkers and ultimately bring adaptive stimulation therapies closer to clinical practice. Unfortunately, there are still very limited options on how to visualize, analyze, and exploit the full potential of the sensing data from these new DBS neurostimulators. To answer this need, we developed a free open-source toolbox, named DBScope, that imports data from neurostimulation devices and can be operated in two ways: via user interface and programmatically, as a library of functions. In this way, it can be used by both clinicians during clinical sessions (for instance, to visually inspect data from the current or previous in-clinic visits), and by researchers in their research pipelines (e.g., for pre-processing, feature extraction and biomarker search). All in all, the DBScope toolbox is set to facilitate the clinical decision-making process and the identification of clinically relevant biomarkers. The toolbox is already being used in clinical and research environments, and it is freely available to download at GitHub (where it is also fully documented).

Changes in slow-wave sleep characteristics in Parkinson's disease patients with mild-moderate depression

IntroductionDepression and sleep disturbances are commonly seen non-motor symptoms in patients with Parkinson's disease (PD). This study used polysomnography to examine the relationship between mild-moderate depression in PD and sleep characteristics, particularly slow wave activities (SWA). Methods59 PD patients were split into two groups: nd-PD (n = 27) (patients with PD without depression) and d-PD (n = 32) (patients with PD with mild-moderate depression). Their clinical features, polysomnography parameters, and demographics were evaluated. Early and late sleep SWA spectrum densities and overnight SWA decline in different brain regions were particularly analyzed. ResultsNon-rapid eye movement 3 (N3) sleep duration and percentage were greater in the d-PD group. N3 percentage was linked to depression (p = 0.014). During late sleep, higher SWA (0.5–4Hz) in the frontal and central regions, higher low-SWA (0.5–2Hz) in the whole brain, central and occipital regions, and higher high-SWA (2–4Hz) in the frontal region was observed in the d-PD group. During early sleep, there was also higher low-SWA (0.5–2Hz) in the occipital region. Patients in d-PD group exhibited reduced overnight high-SWA (2–4Hz) decline (Δhigh-SWA) in the whole brain and occipital regions. Δhigh-SWA(2–4Hz) in the occipital region were associated with depression (p = 0.049). ConclusionPD patients with mild-moderate depression have impaired slow wave sleep, exhibiting as increased N3 sleep, SWA, and reduced overnight SWA decline. This implies that synaptic strength reduction during sleep and impaired synaptic homeostasis regulation may be associated with depression in PD. Reduced overnight high-SWA decline in the occipital region may serve as a novel electrophysiological biomarker for indicating depression in PD.

An Unpredictable Brain Is a Conscious, Responsive Brain.

Severe traumatic brain injuries typically result in loss of consciousness or coma. In deeply comatose patients with traumatic brain injury, cortical dynamics become simple, repetitive, and predictable. We review evidence that this low-complexity, high-predictability state results from a passive cortical state, represented by a stable repetitive attractor, that hinders the flexible formation of neuronal ensembles necessary for conscious experience. Our data and those from other groups support the hypothesis that this cortical passive state is because of the loss of thalamocortical input. We identify the unpredictability and complexity of cortical dynamics captured by local field potential as a sign of recovery from this passive coma attractor. In this Perspective article, we discuss how these electrophysiological biomarkers of the recovery of consciousness could inform the design of closed-loop stimulation paradigms to treat disorders of consciousness.

Beta Oscillations in the Sensory Thalamus During Severe Facial Neuropathic Pain Using Novel Sensing Deep Brain Stimulation

ObjectiveAdvancements in deep brain stimulation (DBS) devices provide a unique opportunity to record local field potentials longitudinally to improve the efficacy of treatment for intractable facial pain. We aimed to identify potential electrophysiological biomarkers of pain in the ventral posteromedial nucleus (VPM) of the thalamus and periaqueductal gray (PAG) using a long-term sensing DBS system. Materials and MethodsWe analyzed power spectra of ambulatory pain-related events from one patient implanted with a long-term sensing generator, representing different pain intensities (pain >7, pain >9) and pain qualities (no pain, burning, stabbing, and shocking pain). Power spectra were parametrized to separate oscillatory and aperiodic features and compared across the different pain states. ResultsOverall, 96 events were marked during a 16-month follow-up. Parameterization of spectra revealed a total of 62 oscillatory peaks with most in the VPM (77.4%). The pain-free condition did not show any oscillations. In contrast, β peaks were observed in the VPM during all episodes (100%) associated with pain >9, 56% of episodes with pain >7, and 50% of burning pain events (center frequencies: 28.4 Hz, 17.8 Hz, and 20.7 Hz, respectively). Episodes of pain >9 indicated the highest relative β band power in the VPM and decreased aperiodic exponents (denoting the slope of the power spectra) in both the VPM and PAG. ConclusionsFor this patient, an increase in β band activity in the sensory thalamus was associated with severe facial pain, opening the possibility for closed-loop DBS in facial pain.

F.1 Oscillatory network markers of subcallosal cingulate deep brain stimulation for depression

Background: Identifying functional biomarkers related to treatment success can aid in optimizing therapy and provide a better understanding of the neural mechanisms of treatment-resistant depression (TRD) and subcallosal cingulate deep brain stimulation (SCC-DBS). Methods: Magnetoencephalography data were obtained from 16 individuals with SCC-DBS for TRD and 25 healthy subjects. We identified region-specific oscillatory modulations that both (i) discriminate individuals with TRD (SCC-DBS OFF) from healthy controls and (ii) discriminate responders from non-responders (SCC-DBS ON). The effects of stimulation intensity and frequency were also explored. Results: Discriminative regions that differentiated responders from non-responders based on modulations of increased alpha (8-12 Hz) and decreased gamma (32-116 Hz) power included nodes of the default mode, central executive, and somatomotor networks, Broca’s area, and lingual gyrus. Furthermore, low stimulation frequency had stronger effects on oscillatory modulation. Conclusions: The identified functional biomarkers implicate modulations of TRD-related activity in brain regions involved in emotional control/processing, motor control, and interactions between speech, vision, and memory – all implicated in depression. These electrophysiological biomarkers have the potential to be used as functional proxies for therapy optimization. Additional stimulation parameter analyses revealed that oscillatory modulations are strengthened by increasing stimulation intensity or reducing frequency, which may benefit SCC-DBS non-responders.

Aperiodic components of local field potentials reflect inherent differences between cortical and subcortical activity.

The aperiodic component of local field potentials can be modeled to produce useful and reproducible indices of neural activity. Here we refined a widely used phenomenological model for extracting aperiodic parameters (namely the exponent, offset and knee), with which we fit cortical, basal ganglia, and thalamic intracranial local field potentials, recorded from unique cohorts of movement disorders and epilepsy patients. We found that the aperiodic exponent in motor cortex is higher in Parkinson's disease patients with more severe motor symptoms, suggesting that aperiodic features may have potential as electrophysiological biomarkers for movement disorders symptoms. Remarkably, we found conspicuous differences in the aperiodic parameters of basal ganglia and thalamic signals compared to those from neocortex.

Role of electrophysiological activity and interactions of lateral habenula in the development of depression-like behavior in a chronic restraint stress model

Closed-loop deep brain stimulation (DBS) system offers a promising approach for treatment-resistant depression, but identifying universally accepted electrophysiological biomarkers for closed-loop DBS systems targeting depression is challenging. There is growing evidence suggesting a strong association between the lateral habenula (LHb) and depression. Here, we took LHb as a key target, utilizing multi-site local field potentials (LFPs) to study the acute and chronic changes in electrophysiology, functional connectivity, and brain network characteristics during the formation of a chronic restraint stress (CRS) model. Furthermore, our model combining the electrophysiological changes of LHb and interactions between LHb and other potential targets of depression can effectively distinguish depressive states, offering a new way for developing effective closed-loop DBS strategies.

Natural history and biomarkers of KCNV2-associated retinopathy.

KCNV2-associated retinopathy is an autosomal recessive inherited retinal disease classically named cone dystrophy with supernormal rod response (CDSRR). This study aims to identify the best biomarker for evaluating the condition. A retrospective review of eight patients from seven families with genetically confirmed KCNV2-associated retinopathy was performed. The best corrected visual acuity (BCVA), full-field electroretinogram (ffERG), pattern ERG (pERG), fundus imaging: retinal photograph and fundus autofluorescence (FAF), and optical coherence tomography (OCT) were analysed. There was a disproportionate increase in b-wave amplitude with a relatively small light intensity increase, especially between the two dimmest stimuli of DA 0.002 and 0.01 (-2.7 and -2.0 log cd.s/m2). The a-wave amplitude was normal. The a-wave peak time was delayed in all stimuli. The b-wave peak time was delayed compared to normal, but the gap tightened as intensity increased. The b:a wave ratio was above or at the upper limit for the reference values. FAF bull's eye maculopathy pattern was prominent and variable foveal disruption on OCT was apparent in all patients. Legal blindness was reached before the age of 25. We identified three potential electrophysiology biomarkers to assist in evaluating future therapies: the disproportionate b-wave amplitude jump, delayed a-wave and b-wave peak time, and the higher than normal b:a wave ratio. Any of these biomarkers found with photoreceptor ellipsoid zone foveal-perifoveal disruption should prompt consideration for KCNV2 retinopathy. The BCVA natural history data suggests the probable optimum therapeutic window in the first three decades of life.

Atypical brain responses to 40-Hz click trains in girls with Rett syndrome: Auditory steady-state response and sustained wave.

The current study aimed to infer neurophysiological mechanisms of auditory processing in children with Rett syndrome (RTT)-rare neurodevelopmental disorders caused by MECP2 mutations. We examined two brain responses elicited by 40-Hz click trains: auditory steady-state response (ASSR), which reflects fine temporal analysis of auditory input, and sustained wave (SW), which is associated with integral processing of the auditory signal. We recorded electroencephalogram findings in 43 patients with RTT (aged 2.92-17.1 years) and 43 typically developing children of the same age during 40-Hz click train auditory stimulation, which lasted for 500 ms and was presented with interstimulus intervals of 500 to 800 ms. Mixed-model ancova with age as a covariate was used to compare amplitude of ASSR and SW between groups, taking into account the temporal dynamics and topography of the responses. Amplitude of SW was atypically small in children with RTT starting from early childhood, with the difference from typically developing children decreasing with age. ASSR showed a different pattern of developmental changes: the between-group difference was negligible in early childhood but increased with age as ASSR increased in the typically developing group, but not in those with RTT. Moreover, ASSR was associated with expressive speech development in patients, so that children who could use words had more pronounced ASSR. ASSR and SW show promise as noninvasive electrophysiological biomarkers of auditory processing that have clinical relevance and can shed light onto the link between genetic impairment and the RTT phenotype.

Comparing novel electrophysiological biomarkers and circulating cardiac biomarkers in predicting cardiovascular mortality and all-cause mortality in the Akershus Sleep Apnea (ASAP) epidemiological cohort

Comparing novel electrophysiological biomarkers and circulating cardiac biomarkers in predicting cardiovascular mortality and all-cause mortality in the Akershus Sleep Apnea (ASAP) epidemiological cohort

A meta-analysis of electrophysiological biomarkers of reward and error monitoring in substance misuse.

Substance use disorders are characterized by marked changes in reward and error processing. The primary objective of this meta-analysis was to estimate effect sizes for the reward positivity (RewP) and error-related negativity (ERN), two event-related potential indicators of outcome monitoring, in substance users compared to controls. The secondary objective was to test for moderation by demographic, substance type, and EEG experiment parameters. Final PubMed searches were performed in August 2023. Inclusion criteria were substance use disorder/dependence or validated self-report of substance misuse, RewP/ERN means available, healthy control comparison group, non-acute drug study, peer-reviewed journal, English language, and human participants. Selection bias was tested through modified Egger's regression and exploratory 3-parameter selection model tests. The RewP results (19 studies, 1641 participants) did not support an overall effect (Hedges' g = 0.07, 95% CI [-0.44, 0.58], p = .777) and nor effect of any moderators. The ERN results (20 studies, 1022 participants) indicated no significant overall effect (g = 0.41, 95%CI [-0.05, 0.88]). Subgroup analyses indicated that cocaine users had a blunted ERN compared to controls (g = 1.12, 95%CI [0.77, 1.47]). There was limited evidence for publication/small study bias. Although the results indicate a potential dissociation between substance types, this meta-analysis revealed the need for additional research on the RewP/ERN in substance using populations and for better designed experiments that adequately address research questions.

Improving naturalistic neuroscience with patient engagement strategies.

The clinical implementation of chronic electrophysiology-driven adaptive deep brain stimulation (DBS) algorithms in movement disorders requires reliable representation of motor and non-motor symptoms in electrophysiological biomarkers, throughout normal life (naturalistic). To achieve this, there is the need for high-resolution and -quality chronic objective and subjective symptom monitoring in parallel to biomarker recordings. To realize these recordings, an active participation and engagement of the investigated patients is necessary. To date, there has been little research into patient engagement strategies for DBS patients or chronic electrophysiological recordings. We here present our concept and the first results of a patient engagement strategy for a chronic DBS study. After discussing the current state of literature, we present objectives, methodology and consequences of the patient engagement regarding study design, data acquisition, and study infrastructure. Nine patients with Parkinson's disease and their caregivers participated in the meeting, and their input led to changes to our study design. Especially, the patient input helped us designing study-set-up meetings and support structures. We believe that patient engagement increases compliance and study motivation through scientific empowerment of patients. While considering patient opinion on sensors or questionnaire questions may lead to more precise and reliable data acquisition, there was also a high demand for study support and engagement structures. Hence, we recommend the implementation of patient engagement in planning of chronic studies with complex designs, long recording durations or high demand for individual active study participation.