Neurologische Klinik und Poliklinik
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- 2023 (30) (entfernen)
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- Parkinson's disease (4)
- neuroimmunology (3)
- Altern (2)
- Fabry-Krankheit (2)
- Neurodegeneration (2)
- Neuropathie (2)
- deep brain stimulation (2)
- diseases of the nervous system (2)
- local field potentials (2)
- machine learning (2)
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- Neurologische Klinik und Poliklinik (30)
- Graduate School of Life Sciences (5)
- Institut für Molekulare Infektionsbiologie (2)
- Klinik und Poliklinik für Hals-, Nasen- und Ohrenkrankheiten, plastische und ästhetische Operationen (2)
- Medizinische Klinik und Poliklinik II (2)
- Betriebswirtschaftliches Institut (1)
- Frauenklinik und Poliklinik (1)
- Institut für Humangenetik (1)
- Institut für Klinische Epidemiologie und Biometrie (1)
- Institut für Klinische Neurobiologie (1)
Sonstige beteiligte Institutionen
The execution of voluntary movements is primarily governed by the cerebral hemisphere contralateral to the moving limb. Previous research indicates that the ipsilateral motor network, comprising the primary motor cortex (M1), supplementary motor area (SMA), and premotor cortex (PM), plays a crucial role in the planning and execution of limb movements. However, the precise functions of this network and its interplay in different task contexts have yet to be fully understood. Twenty healthy right-handed participants (10 females, mean age 26.1 ± 4.6 years) underwent functional MRI scans while performing biceps brachii representations such as bilateral, unilateral flexion, and bilateral flexion-extension. Ipsilateral motor evoked potentials (iMEPs) were obtained from the identical set of participants in a prior study using transcranial magnetic stimulation (TMS) targeting M1 while employing the same motor tasks. The voxel time series was extracted based on the region of interest (M1, SMA, ventral PM and dorsal PM). Directed functinal connectivity was derived from the extracted time series using time-resolved partial directed coherence. We found increased connectivity from left-PMv to both sides M1, as well as right-PMv to both sides SMA, in unilateral flexion compared to bilateral flexion. Connectivity from left M1 to left-PMv, and left-SMA to right-PMd, also increased in both unilateral flexion and bilateral flexion-extension compared to bilateral flexion. However, connectivity between PMv and right-M1 to left-PMd decreased during bilateral flexion-extension compared to unilateral flexion. Additionally, during bilateral flexion-extension, the connectivity from right-M1 to right-SMA had a negative relationship with the area ratio of iMEP in the dominant side. Our results provide corroborating evidence for prior research suggesting that the ipsilateral motor network is implicated in the voluntary movements and underscores its involvement in cognitive processes such as movement planning and coordination. Moreover, ipsilateral connectivity from M1 to SMA on the dominant side can modulate the degree of ipsilateral M1 activation during bilateral antagonistic contraction.
Axon degeneration and functional decline in myelin diseases are often attributed to loss of myelin but their relation is not fully understood. Perturbed myelinating glia can instigate chronic neuroinflammation and contribute to demyelination and axonal damage. Here we study mice with distinct defects in the proteolipid protein 1 gene that develop axonal damage which is driven by cytotoxic T cells targeting myelinating oligodendrocytes. We show that persistent ensheathment with perturbed myelin poses a risk for axon degeneration, neuron loss, and behavioral decline. We demonstrate that CD8\(^+\) T cell-driven axonal damage is less likely to progress towards degeneration when axons are efficiently demyelinated by activated microglia. Mechanistically, we show that cytotoxic T cell effector molecules induce cytoskeletal alterations within myelinating glia and aberrant actomyosin constriction of axons at paranodal domains. Our study identifies detrimental axon-glia-immune interactions which promote neurodegeneration and possible therapeutic targets for disorders associated with myelin defects and neuroinflammation.
Elevated and low blood pressure (BP) may lead to poor functional outcome after ischemic stroke, which is conflicting. Hence, there must be another factor—such as cerebral small vessel disease (cSVD) -interacting with BP and thus, affecting outcome. Here, we investigate the relationship between BP and cSVD regarding outcome after stroke. Data of 423/503 stroke patients were prospectively analyzed. Diastolic (DBP) and systolic BP (SBP) were collected on hospital admission (BP\(_{ad}\)) and over the first 72 h (BP\(_{72h}\)). cSVD-burden was determined on MR-scans. Good functional outcome was defined as a modified Rankin Scale score ≤ 2 at hospital discharge and 12 months thereafter. cSVD was a predictor of poor outcome (OR 2.8; p < 0.001). SBPad, DBP\(_{ad}\) and SBP\(_{72h}\) were not significantly associated with outcome at any time. A significant relationship was found between DBP\(_{72h}\), (p < 0.01), cSVD (p = 0.013) and outcome at discharge. At 12 months, we found a relationship between outcome and DBP\(_{72h}\) (p = 0.018) and a statistical tendency regarding cSVD (p = 0.08). Changes in DBP72h were significantly related with outcome. There was a U-shaped relationship between DBP\(_{72h}\) and outcome at discharge. Our results suggest an individualized stroke care by either lowering or elevating DBP depending on cSVD-burden in order to influence functional outcome.
Topological differences and confounders of mental rotation in cervical dystonia and blepharospasm
(2023)
Mental rotation (mR) bases on imagination of actual movements. It remains unclear whether there is a specific pattern of mR impairment in focal dystonia. We aimed to investigate mR in patients with cervical dystonia (CD) and blepharospasm (BS) and to assess potential confounders. 23 CD patients and 23 healthy controls (HC) as well as 21 BS and 19 hemifacial spasm (HS) patients were matched for sex, age, and education level. Handedness, finger dexterity, general reaction time, and cognitive status were assessed. Disease severity was evaluated by clinical scales. During mR, photographs of body parts (head, hand, or foot) and a non-corporal object (car) were displayed at different angles rotated within their plane. Subjects were asked to judge laterality of the presented image by keystroke. Both speed and correctness were evaluated. Compared to HC, CD and HS patients performed worse in mR of hands, whereas BS group showed comparable performance. There was a significant association of prolonged mR reaction time (RT) with reduced MoCA scores and with increased RT in an unspecific reaction speed task. After exclusion of cognitively impaired patients, increased RT in the mR of hands was confined to CD group, but not HS. While the question of whether specific patterns of mR impairment reliably define a dystonic endophenotype remains elusive, our findings point to mR as a useful tool, when used carefully with control measures and tasks, which may be capable of identifying specific deficits that distinguish between subtypes of dystonia.
Seed amplification assays (SAA) are becoming commonly used in synucleinopathies to detect α-synuclein aggregates. Studies in Parkinson’s disease (PD) and isolated REM-sleep behavior disorder (iRBD) have shown a considerably lower sensitivity in the olfactory epithelium than in CSF or skin. To get an insight into α-synuclein (α-syn) distribution within the nervous system and reasons for low sensitivity, we compared SAA assessment of nasal brushings and skin biopsies in PD (n = 27) and iRBD patients (n = 18) and unaffected controls (n = 30). α-syn misfolding was overall found less commonly in the olfactory epithelium than in the skin, which could be partially explained by the nasal brushing matrix exerting an inhibitory effect on aggregation. Importantly, the α-syn distribution was not uniform: there was a higher deposition of misfolded α-syn across all sampled tissues in the iRBD cohort compared to PD (supporting the notion of RBD as a marker of a more malignant subtype of synucleinopathy) and in a subgroup of PD patients, misfolded α-syn was detectable only in the olfactory epithelium, suggestive of the recently proposed brain-first PD subtype. Assaying α-syn of diverse origins, such as olfactory (part of the central nervous system) and skin (peripheral nervous system), could increase diagnostic accuracy and allow better stratification of patients.
Inflammation in the brain and gut is a critical component of several neurological diseases, such as Parkinson’s disease (PD). One trigger of the immune system in PD is aggregation of the pre-synaptic protein, α-synuclein (αSyn). Understanding the mechanism of propagation of αSyn aggregates is essential to developing disease-modifying therapeutics. Using a brain-first mouse model of PD, we demonstrate αSyn trafficking from the brain to the ileum of male mice. Immunohistochemistry revealed that the ileal αSyn aggregations are contained within CD11c+ cells. Using single-cell RNA sequencing, we demonstrate that ileal CD11c\(^+\) cells are microglia-like and the same subtype of cells is activated in the brain and ileum of PD mice. Moreover, by utilizing mice expressing the photo-convertible protein, Dendra2, we show that CD11c\(^+\) cells traffic from the brain to the ileum. Together these data provide a mechanism of αSyn trafficking between the brain and gut.
Bioimages frequently exhibit low signal-to-noise ratios due to experimental conditions, specimen characteristics, and imaging trade-offs. Reliable segmentation of such ambiguous images is difficult and laborious. Here we introduce deepflash2, a deep learning-enabled segmentation tool for bioimage analysis. The tool addresses typical challenges that may arise during the training, evaluation, and application of deep learning models on ambiguous data. The tool’s training and evaluation pipeline uses multiple expert annotations and deep model ensembles to achieve accurate results. The application pipeline supports various use-cases for expert annotations and includes a quality assurance mechanism in the form of uncertainty measures. Benchmarked against other tools, deepflash2 offers both high predictive accuracy and efficient computational resource usage. The tool is built upon established deep learning libraries and enables sharing of trained model ensembles with the research community. deepflash2 aims to simplify the integration of deep learning into bioimage analysis projects while improving accuracy and reliability.
Highlights
• Beta-Guided programming is an innovative approach that may streamline the programming process for PD patients with STN DBS.
• While preliminary findings from our study suggest that Beta Titration may potentially mitigate STN overstimulation and enhance symptom control,
• Our results demonstrate that beta-guided programming significantly reduces programming time, suggesting it could be efficiently integrated into routine clinical practice using a commercially available patient programmer.
Background
Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for advanced Parkinson's disease (PD). Clinical outcomes after DBS can be limited by poor programming, which remains a clinically driven, lengthy and iterative process. Electrophysiological recordings in PD patients undergoing STN-DBS have shown an association between STN spectral power in the beta frequency band (beta power) and the severity of clinical symptoms. New commercially-available DBS devices now enable the recording of STN beta oscillations in chronically-implanted PD patients, thereby allowing investigation into the use of beta power as a biomarker for DBS programming.
Objective
To determine the potential advantages of beta-guided DBS programming over clinically and image-guided programming in terms of clinical efficacy and programming time.
Methods
We conducted a randomized, blinded, three-arm, crossover clinical trial in eight Parkinson's patients with STN-DBS who were evaluated three months after DBS surgery. We compared clinical efficacy and time required for each DBS programming paradigm, as well as DBS parameters and total energy delivered between the three strategies (beta-, clinically- and image-guided).
Results
All three programming methods showed similar clinical efficacy, but the time needed for programming was significantly shorter for beta- and image-guided programming compared to clinically-guided programming (p < 0.001).
Conclusion
Beta-guided programming may be a useful and more efficient approach to DBS programming in Parkinson's patients with STN-DBS. It takes significantly less time to program than traditional clinically-based programming, while providing similar symptom control. In addition, it is readily available within the clinical DBS programmer, making it a valuable tool for improving current clinical practice.
Low-frequency oscillatory patterns of pallidal local field potentials (LFPs) have been proposed as a physiomarker for dystonia and hold the promise for personalized adaptive deep brain stimulation. Head tremor, a low-frequency involuntary rhythmic movement typical of cervical dystonia, may cause movement artifacts in LFP signals, compromising the reliability of low-frequency oscillations as biomarkers for adaptive neurostimulation. We investigated chronic pallidal LFPs with the Percept\(^{TM}\) PC (Medtronic PLC) device in eight subjects with dystonia (five with head tremors). We applied a multiple regression approach to pallidal LFPs in patients with head tremors using kinematic information measured with an inertial measurement unit (IMU) and an electromyographic signal (EMG). With IMU regression, we found tremor contamination in all subjects, whereas EMG regression identified it in only three out of five. IMU regression was also superior to EMG regression in removing tremor-related artifacts and resulted in a significant power reduction, especially in the theta-alpha band. Pallido-muscular coherence was affected by a head tremor and disappeared after IMU regression. Our results show that the Percept PC can record low-frequency oscillations but also reveal spectral contamination due to movement artifacts. IMU regression can identify such artifact contamination and be a suitable tool for its removal.