DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience.

Biomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher-dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets containing EEG recordings of healthy participants and patients with a psychiatric condition. Additionally, we performed an exploratory analysis that could inspire the development of biomarkers for healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function.

Resting-state EEG and MEG biomarkers of pathological fatigue - A transdiagnostic systematic review.

Fatigue is a highly prevalent and disabling symptom of many disorders and syndromes, resulting from different pathomechanisms. However, whether and how different mechanisms converge and result in similar symptomatology is only partially understood, and transdiagnostic biomarkers that could further the diagnosis and treatment of fatigue are lacking. We, therefore, performed a transdiagnostic systematic review (PROSPERO: CRD42022330113) of quantitative resting-state electroencephalography (EEG) and magnetoencephalography (MEG) studies in adult patients suffering from pathological fatigue in different disorders. Studies investigating fatigue in healthy participants were excluded. The risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semi-quantitative data synthesis was conducted using modified albatross plots. After searching MEDLINE, Web of Science Core Collection, and EMBASE, 26 studies were included. Cross-sectional studies revealed increased brain activity at theta frequencies and decreased activity at alpha frequencies as potential diagnostic biomarkers. However, the risk of bias was high in many studies and domains. Together, this transdiagnostic systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of pathological fatigue. Beyond, this review might help to guide future M/EEG studies on the development of fatigue biomarkers.

Local brain oscillations and interregional connectivity differentially serve sensory and expectation effects on pain.

Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

Resting-state electroencephalography and magnetoencephalography as biomarkers of chronic pain: a systematic review.

ABSTRACT: Reliable and objective biomarkers promise to improve the assessment and treatment of chronic pain. Resting-state electroencephalography (EEG) is broadly available, easy to use, and cost efficient and, therefore, appealing as a potential biomarker of chronic pain. However, results of EEG studies are heterogeneous. Therefore, we conducted a systematic review (PROSPERO CRD42021272622) of quantitative resting-state EEG and magnetoencephalography (MEG) studies in adult patients with different types of chronic pain. We excluded populations with severe psychiatric or neurologic comorbidity. Risk of bias was assessed using a modified Newcastle-Ottawa Scale. Semiquantitative data synthesis was conducted using modified albatross plots. We included 76 studies after searching MEDLINE, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and EMBASE. For cross-sectional studies that can serve to develop diagnostic biomarkers, we found higher theta and beta power in patients with chronic pain than in healthy participants. For longitudinal studies, which can yield monitoring and/or predictive biomarkers, we found no clear associations of pain relief with M/EEG measures. Similarly, descriptive studies that can yield diagnostic or monitoring biomarkers showed no clear correlations of pain intensity with M/EEG measures. Risk of bias was high in many studies and domains. Together, this systematic review synthesizes evidence on how resting-state M/EEG might serve as a diagnostic biomarker of chronic pain. Beyond, this review might help to guide future M/EEG studies on the development of pain biomarkers.

Longitudinal resting-state electroencephalography in patients with chronic pain undergoing interdisciplinary multimodal pain therapy.

ABSTRACT: Chronic pain is a major healthcare issue posing a large burden on individuals and society. Converging lines of evidence indicate that chronic pain is associated with substantial changes of brain structure and function. However, it remains unclear which neuronal measures relate to changes of clinical parameters over time and could thus monitor chronic pain and treatment responses. We therefore performed a longitudinal study in which we assessed clinical characteristics and resting-state electroencephalography data of 41 patients with chronic pain before and 6 months after interdisciplinary multimodal pain therapy. We specifically assessed electroencephalography measures that have previously been shown to differ between patients with chronic pain and healthy people. These included the dominant peak frequency; the amplitudes of neuronal oscillations at theta, alpha, beta, and gamma frequencies; as well as graph theory-based measures of brain network organization. The results show that pain intensity, pain-related disability, and depression were significantly improved after interdisciplinary multimodal pain therapy. Bayesian hypothesis testing indicated that these clinical changes were not related to changes of the dominant peak frequency or amplitudes of oscillations at any frequency band. Clinical changes were, however, associated with an increase in global network efficiency at theta frequencies. Thus, changes in chronic pain might be reflected by global network changes in the theta band. These longitudinal insights further the understanding of the brain mechanisms of chronic pain. Beyond, they might help to identify biomarkers for the monitoring of chronic pain.

Temporal-spectral signaling of sensory information and expectations in the cerebral processing of pain.

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual's expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain.

Modulating Brain Rhythms of Pain Using Transcranial Alternating Current Stimulation (tACS) - A Sham-Controlled Study in Healthy Human Participants.

Chronic pain is a major health care problem. A better mechanistic understanding and new treatment approaches are urgently needed. In the brain, pain has been associated with neural oscillations at alpha and gamma frequencies, which can be targeted using transcranial alternating current stimulation (tACS). Thus, we investigated the potential of tACS to modulate pain and pain-related autonomic activity in an experimental model of chronic pain in 29 healthy participants. In 6 recording sessions, participants completed a tonic heat pain paradigm and simultaneously received tACS over prefrontal or somatosensory cortices at alpha or gamma frequencies or sham tACS. Concurrently, pain ratings and autonomic responses were collected. Using the present setup, tACS did not modulate pain or autonomic responses. Bayesian statistics confirmed a lack of tACS effects in most conditions. The only exception was alpha tACS over somatosensory cortex where evidence was inconclusive. Taken together, we did not find significant tACS effects on tonic experimental pain in healthy humans. Based on our present and previous findings, further studies might apply refined stimulation protocols targeting somatosensory alpha oscillations. TRIAL REGISTRATION: The study protocol was pre-registered at ClinicalTrials.gov (NCT03805854). PERSPECTIVE: Modulating brain oscillations is a promising approach for the treatment of pain. We therefore applied transcranial alternating current stimulation (tACS) to modulate experimental pain in healthy participants. However, tACS did not modulate pain, autonomic responses, or EEG oscillations. These findings help to shape future tACS studies for the treatment of pain.

Dynamics of brain function in patients with chronic pain assessed by microstate analysis of resting-state electroencephalography.

ABSTRACT: Chronic pain is a highly prevalent and severely disabling disease that is associated with substantial changes of brain function. Such changes have mostly been observed when analyzing static measures of resting-state brain activity. However, brain activity varies over time, and it is increasingly recognized that the temporal dynamics of brain activity provide behaviorally relevant information in different neuropsychiatric disorders. Here, we therefore investigated whether the temporal dynamics of brain function are altered in chronic pain. To this end, we applied microstate analysis to eyes-open and eyes-closed resting-state electroencephalography data of 101 patients suffering from chronic pain and 88 age- and sex-matched healthy controls. Microstate analysis describes electroencephalography activity as a sequence of a limited number of topographies termed microstates that remain stable for tens of milliseconds. Our results revealed that sequences of 5 microstates, labelled with the letters A to E, consistently described resting-state brain activity in both groups in the eyes-closed condition. Bayesian analysis of the temporal characteristics of microstates revealed that microstate D has a less predominant role in patients than in controls. As microstate D has previously been related to attentional networks and functions, these abnormalities might relate to dysfunctional attentional processes in chronic pain. Subgroup analyses replicated microstate D changes in patients with chronic back pain, while patients with chronic widespread pain did not show microstates alterations. Together, these findings add to the understanding of the pathophysiology of chronic pain and point to changes of brain dynamics specific to certain types of chronic pain.

Neural oscillations and connectivity characterizing the state of tonic experimental pain in humans.

Pain is a complex phenomenon that is served by neural oscillations and connectivity involving different brain areas and frequencies. Here, we aimed to systematically and comprehensively assess the pattern of neural oscillations and connectivity characterizing the state of tonic experimental pain in humans. To this end, we applied 10-min heat pain stimuli consecutively to the right and left hand of 39 healthy participants and recorded electroencephalography. We systematically analyzed global and local measures of oscillatory brain activity, connectivity, and graph theory-based network measures during tonic pain and compared them to a nonpainful control condition. Local measures showed suppressions of oscillatory activity at alpha frequencies together with stronger connectivity at alpha and beta frequencies in sensorimotor areas during tonic pain. Furthermore, sensorimotor areas contralateral to stimulation showed significantly increased connectivity to a common area in the medial prefrontal cortex at alpha frequencies. Together, these observations indicate that the state of tonic experimental pain is associated with a sensorimotor-prefrontal network connected at alpha frequencies. These findings represent a step further toward understanding the brain mechanisms underlying long-lasting pain states in health and disease.

From correlation towards causality: modulating brain rhythms of pain using transcranial alternating current stimulation.

INTRODUCTION: Accumulating evidence suggests that neural oscillations at different frequencies and their synchrony between brain regions play a crucial role in the processing of nociceptive input and the emergence of pain. Most findings are limited by their correlative nature, however, which impedes causal inferences. OBJECTIVE: To move from correlative towards causal evidence, methods that allow to experimentally manipulate oscillatory brain activity are needed. RESULTS: Transcranial alternating current stimulation (tACS) is a noninvasive brain stimulation technique designed to modulate neural oscillations in a frequency specific manner and as such a suitable method to investigate the contribution of oscillatory brain activity to pain. Despite its appeal, tACS has been barely applied in the field of pain research. In the present review, we address this issue and discuss how tACS can be used to gather mechanistic evidence for the relationship between pain and neural oscillations in humans. CONCLUSIONS: Transcranial alternating current stimulation holds great potential for the investigation of the neural mechanisms underlying pain and the development of new treatment approaches for chronic pain if necessary methodological precautions are taken.

Brain dysfunction in chronic pain patients assessed by resting-state electroencephalography.

Chronic pain is a common and severely disabling disease whose treatment is often unsatisfactory. Insights into the brain mechanisms of chronic pain promise to advance the understanding of the underlying pathophysiology and might help to develop disease markers and novel treatments. Here, we systematically exploited the potential of electroencephalography to determine abnormalities of brain function during the resting state in chronic pain. To this end, we performed state-of-the-art analyses of oscillatory brain activity, brain connectivity, and brain networks in 101 patients of either sex suffering from chronic pain. The results show that global and local measures of brain activity did not differ between chronic pain patients and a healthy control group. However, we observed significantly increased connectivity at theta (4-8 Hz) and gamma (>60 Hz) frequencies in frontal brain areas as well as global network reorganization at gamma frequencies in chronic pain patients. Furthermore, a machine learning algorithm could differentiate between patients and healthy controls with an above-chance accuracy of 57%, mostly based on frontal connectivity. These results suggest that increased theta and gamma synchrony in frontal brain areas are involved in the pathophysiology of chronic pain. Although substantial challenges concerning the reproducibility of the findings and the accuracy, specificity, and validity of potential electroencephalography-based disease markers remain to be overcome, our study indicates that abnormal frontal synchrony at theta and gamma frequencies might be promising targets for noninvasive brain stimulation and/or neurofeedback approaches.

Perceptual and motor responses directly and indirectly mediate the effects of noxious stimuli on autonomic responses.

Autonomic responses are an essential component of pain. They serve its adaptive function by regulating homeostasis and providing resources for protective and recuperative responses to noxious stimuli. To be adaptive and flexible, autonomic responses are not only determined by noxious stimulus characteristics, but likely also shaped by perceptual and motor responses to noxious stimuli. However, it is not fully known how noxious stimulus characteristics, perceptual responses, and motor responses interact in shaping autonomic responses. To address this question, we collected perceptual, motor, and autonomic responses to brief noxious laser stimuli of different intensities in 47 healthy human participants. Multilevel 2-path mediation analyses revealed that perceptual, but not motor responses mediated the translation of noxious stimuli into autonomic responses. Multilevel 3-path mediation analyses further specified that motor responses indirectly related to autonomic responses through their close association with perceptual responses. These findings confirm that autonomic responses are not only a reflexive reaction to noxious stimuli, but directly and indirectly shaped by perceptual and motor responses, respectively. These effects of motor and perceptual processes on autonomic responses likely allow for the integration of contextual processes into protective and regulatory autonomic responses, aiding adaptive and flexible coping with threat.

Insomnia Severity in Adults with Autism Spectrum Disorder is Associated with sensory Hyper-Reactivity and Social Skill Impairment.

Insomnia is a common source of distress in adults with autism spectrum disorder (ASD). Two characteristics of ASD could be relevant to insomnia complaints by hampering the entrainment of a circadian sleep-wake rhythm. First, sensory hyper-reactivity could lead to bright light avoidance and thus affect photoperiodic input to the circadian system. Second, impaired social skills complicate the establishment of a social interactions and thus affect scheduled social-behavioral input to the circadian system. We investigated the association of insomnia severity with sensory reactivity and social skills in 631 adults (18-65 years) with ASD. Results revealed positive associations of insomnia severity with general and visual sensory hyper-reactivity and with impairment of social skills. The findings warrant further studies which (1) directly assess whether a suboptimal functioning of the biological clock underlies these associations and (2) identify other factors that could contribute to observed sleep problems.

Distinct patterns of brain activity mediate perceptual and motor and autonomic responses to noxious stimuli.

Pain is a complex phenomenon involving perceptual, motor, and autonomic responses, but how the brain translates noxious stimuli into these different dimensions of pain is unclear. Here, we assessed perceptual, motor, and autonomic responses to brief noxious heat stimuli and recorded brain activity using electroencephalography (EEG) in humans. Multilevel mediation analysis reveals that each pain dimension is subserved by a distinct pattern of EEG responses and, conversely, that each EEG response differentially contributes to the different dimensions of pain. In particular, the translation of noxious stimuli into autonomic and motor responses involved the earliest N1 wave, whereas pain perception was mediated by later N2 and P2 waves. Gamma oscillations mediated motor responses rather than pain perception. These findings represent progress towards a mechanistic understanding of the brain processes translating noxious stimuli into pain and suggest that perceptual, motor, and autonomic dimensions of pain are partially independent rather than serial processes.

Motor Responses to Noxious Stimuli Shape Pain Perception in Chronic Pain Patients.

Pain serves vital protective functions, which crucially depend on appropriate motor responses to noxious stimuli. Such responses not only depend on but can themselves shape the perception of pain. In chronic pain, perception is often decoupled from noxious stimuli and motor responses are no longer protective, which suggests that the relationships between noxious stimuli, pain perception, and behavior might be changed. We here performed a simple experiment to quantitatively assess the relationships between noxious stimuli, perception and behavior in 22 chronic pain patients and 22 age-matched healthy human participants. Brief noxious and tactile stimuli were applied to the participants' hands and participants performed speeded motor responses and provided perceptual ratings of the stimuli. Multi-level moderated mediation analyses assessed the relationships between stimulus intensity, perceptual ratings and reaction times for both stimulus types. The results revealed a significantly stronger involvement of motor responses in the translation of noxious stimuli into perception than in the translation of tactile stimuli into perception. This significant influence of motor responses on pain perception was found for both chronic pain patients and healthy participants. Thus, stimulus-perception-behavior relationships appear to be at least partially preserved in chronic pain patients and motor-related as well as behavioral interventions might harness these functional relationships to modulate pain perception.