Henrik Heitmann

Depression is a highly prevalent and disabling disorder affecting approximately 5% of the adult population worldwide. Despite its impact, the underlying pathophysiology remains insufficiently understood, and current treatments are only partially effective. Brain-based biomarkers offer promise for clarifying mechanisms of depression and guiding novel treatment approaches, including neuromodulation. EEG is particularly attractive for this purpose due to its wide availability, cost-effectiveness, and potential for direct neuromodulatory targeting. We conducted a PROSPERO-registered systematic review in accordance with PRISMA guidelines to assess resting-state EEG biomarkers in adult patients with depression, diagnosed according to DSM-IV/V or ICD-10/11. Included studies reported cross-sectional or correlational data on quantitative EEG measures such as power, cordance, peak frequency, and alpha asymmetry. Semiquantitative analyses using modified albatross plots and meta-analyses were performed. Study quality was assessed with a modified Newcastle-Ottawa Scale. Fifty-two studies met the inclusion criteria. Findings indicated increased low- frequency (delta, theta) and high-frequency (beta, gamma) power, and left frontal alpha asymmetry in depressed patients compared to healthy controls. Meta-analysis confirmed a significant increase in beta power. However, results regarding disease severity correlations and data on peak alpha frequency and cordance were insufficient for interpretation. Risk of bias across studies was high. Our results support increased beta and potentially also theta oscillations and alpha asymmetry as candidate diagnostic EEG biomarkers for depression. These oscillations may reflect disrupted corticolimbic control and reward processing and partially overlap with mechanisms implicated in chronic pain and fatigue. Further investigation is warranted into their potential as diagnostic tools and neuromodulatory treatment targets.

Chronic pain is a prevalent and debilitating condition whose neural mechanisms are incompletely understood. An imbalance of cerebral excitation and inhibition (E/I), particularly in the medial prefrontal cortex (mPFC), is believed to represent a crucial mechanism in the development and maintenance of chronic pain. Thus, identifying a non-invasive, scalable marker of E/I could provide valuable insights into the neural mechanisms of chronic pain and aid in developing clinically useful biomarkers. Recently, the aperiodic component of the electroencephalography (EEG) power spectrum has been proposed to represent a non-invasive proxy for E/I. We, therefore, assessed the aperiodic component in the mPFC of resting-state EEG recordings in 149 people with chronic pain and 115 healthy participants. We found robust evidence against differences in the aperiodic component in the mPFC between people with chronic pain and healthy participants, and no correlation between the aperiodic component and pain intensity. These findings were consistent across different subtypes of chronic pain and were similarly found in a whole-brain analysis. Their robustness was supported by preregistration and multiverse analyses across many different methodological choices. Together, our results suggest that the EEG aperiodic component does not differentiate between people with chronic pain and healthy individuals. These findings and the rigorous methodological approach can guide future studies investigating non-invasive, scalable markers of cerebral dysfunction in people with chronic pain and beyond.

Chronic pain is a prevalent and debilitating condition whose neural mechanisms are incompletely understood. An imbalance of cerebral excitation and inhibition (E/I), particularly in the medial prefrontal cortex (mPFC), is believed to represent a crucial mechanism in the development and maintenance of chronic pain. Thus, identifying a non-invasive, scalable marker of E/I could provide valuable insights into the neural mechanisms of chronic pain and aid in developing clinically useful biomarkers. Recently, the aperiodic component of the electroencephalography (EEG) power spectrum has been proposed to represent a noninvasive proxy for E/I. We, therefore, assessed the aperiodic component in the mPFC of resting-state EEG recordings in 149 people with chronic pain and 115 healthy participants. We found robust evidence against differences in the aperiodic component in the mPFC between people with chronic pain and healthy participants, and no correlation between the aperiodic component and pain intensity. These findings were consistent across different subtypes of chronic pain and were similarly found in a whole-brain analysis. Their robustness was supported by preregistration and multiverse analyses across many different methodological choices. Together, our results suggest that the EEG aperiodic component does not differentiate between people with chronic pain and healthy individuals. These findings and the rigorous methodological approach can guide future studies investigating non-invasive, scalable markers of cerebral dysfunction in people with chronic pain and beyond.

Background: Bedside teaching is essential to foster core clinical competences in medical education, especially in Neurology. However, bedside skills are declining and new concepts to enhance the effectiveness of bedside teaching are needed, also in view of limited in-person teaching possibilities in the ongoing pandemic situation. If theoretical knowledge is taught prior to in-person sessions this might allow to better focus on practical application aspects during bedside teaching. We thus aimed to answer the question to what extent such an approach can enhance the effectiveness of neurological bedside teaching. Methods: In this prospective controlled study, neurological bedside courses following a traditional and a flipped classroom (FC) approach were compared with regards to their effects on theoretical knowledge and practical skills of medical students. Evaluations were obtained from 161 students and their lecturers participating in a neurological bedside teaching course at a German university hospital between October 2020 and July 2021. Students were randomly assigned to course dates. However, the 74 students assigned to course dates from May to July 2021 completed a mandatory online preparation course prior to the bedside teaching. These students served as the interventional group (IG) and the remaining 87 students formed the control group (CG). Ratings of knowledge and skills provided by the students and their lecturers on numerical rating scales served as primary outcome measures. Moreover, the time needed to recapitulate theoretical contents during the in-person teaching session was assessed as a secondary outcome measure. Group comparisons were performed using t-statistics. Results: Theoretical knowledge upon entering the course was rated significantly higher in the IG by the students (p < 0.001) and lecturers (p = 0.003). Lecturers also rated the practical skills of students in the IG significantly higher (p < 0.001). Furthermore, significantly less time was needed to recapitulate theoretical contents during the in-person session in the IG (p = 0.03). Conclusions: Using a FC approach enhances the effectiveness of in-person neurological bedside teaching. Thus, these concepts are particularly valuable in the ongoing pandemic situation. Moreover, they might allow to reuse e-learning contents developed during the pandemic and to develop future bedside teaching concepts.

Background: The COVID-19 pandemic poses a huge challenge for clinical teaching due to contact restrictions and social distancing. Medical teachers have to balance potential risks and benefits of bedside teaching, especially in course formats intended to foster practical clinical skills. In this context, we aimed to address the question, whether presence-based teaching formats without patient involvement are suitable to teach practical skills. Methods: In this quasi-experimental study, presence-based teaching formats with and without patient contact were retrospectively compared regarding their effects on medical students’ theoretical knowledge and practical skills, i.e. the performance and clinical interpretation of the neurological exam. To this end, evaluations from 102 students and their lecturers participating in a neurological bedside teaching course at a German university hospital between October 2020 and April 2021 were obtained. Students were initially randomly assigned to course dates. However, 53 students assigned to courses in November and December 2020, were not able to go bedside due to contact restrictions. These students formed the interventional group and the remaining 49 students the control group. The primary outcome measures were students’ overall grading of the course (school grades, 1–6) as well as ratings of knowledge and skills provided by the students themselves and their lecturers on a numerical rating scale (0–10). Comparison between groups was performed using frequentist and Bayesian t-statistics. Results: The teaching format without patient contact received a significantly poorer overall grade by the students (p = 0.018). However, improvements in the students’ self-ratings of knowledge and skills did not differ between the two formats (all p > 0.05, BF_10max = 0.42). Moreover, especially practical skills were even rated significantly better in the group without patient contact by the lecturers (p < 0.001). Conclusions: Teaching formats without patient contact are less well-received by the students. However, they are able to teach practical skills regarding the performance and clinical interpretation of examination techniques. Still, the evaluations obtained might not adequately capture the importance of bedside teaching in preparing future physicians for their practice. Perspectively, hybrid teaching approaches including flipped-classroom concepts hold considerable potential to enhance effectiveness of bedside teaching in the present pandemic situation and in the future.

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.

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.