A5040460070- Multiple Sclerosis Research Studies
- Long-Term Effects of COVID-19
- Stress Responses and Cortisol
- Functional Brain Connectivity Studies
- Neural and Behavioral Psychology Studies
- Eating Disorders and Behaviors
- Dementia and Cognitive Impairment Research
- Brain Tumor Detection and Classification
- AI in cancer detection
- Machine Learning in Healthcare
- Regulation of Appetite and Obesity
- Advanced Neuroimaging Techniques and Applications
- Digital Imaging for Blood Diseases
- Obsessive-Compulsive Spectrum Disorders
- Diet and metabolism studies
- Neural Networks and Applications
- Advanced MRI Techniques and Applications
- Peripheral Neuropathies and Disorders
- Olfactory and Sensory Function Studies
- Neural dynamics and brain function
- Face Recognition and Perception
- Tryptophan and brain disorders
- Intensive Care Unit Cognitive Disorders
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Ultrasound Imaging and Elastography
Charité - Universitätsmedizin Berlin
2015-2024
Humboldt-Universität zu Berlin
2017-2024
Freie Universität Berlin
2017-2024
Max Delbrück Center
2020-2024
Berlin Institute of Health at Charité - Universitätsmedizin Berlin
2019-2022
Bernstein Center for Computational Neuroscience Berlin
2011-2019
Einstein Center for Neurosciences Berlin
2019
Justus-Liebig-Universität Gießen
2006-2007
Institute for Frontier Areas of Psychology and Mental Health
2007
Mindfulness meditators practice the non-judgmental observation of ongoing stream internal experiences as they arise. Using voxel-based morphometry, this study investigated MRI brain images 20 mindfulness (Vipassana) (mean 8.6 years; 2 h daily) and compared regional gray matter concentration to that non-meditators matched for sex, age, education handedness. Meditators were predicted show greater in regions are typically activated during meditation. Results confirmed right anterior insula,...
Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer's disease (AD) detection based on structural magnetic resonance (MRI) data. However, the network decisions are often perceived as being highly non-transparent making it difficult apply these algorithms clinical routine. In this study, we propose using layer-wise relevance propagation (LRP) visualize convolutional for AD MRI Similarly other visualization methods, LRP produces a heatmap...
Machine learning-based imaging diagnostics has recently reached or even surpassed the level of clinical experts in several domains. However, classification decisions a trained machine learning system are typically non-transparent, major hindrance for integration, error tracking knowledge discovery. In this study, we present transparent deep framework relying on 3D convolutional neural networks (CNNs) and layer-wise relevance propagation (LRP) diagnosing multiple sclerosis (MS), most...
This study addresses how visual food cues are encoded in reward related brain areas and whether this encoding might provide information to differentiate between patients suffering from eating disorders [binge-eating disorder (BED) bulimia nervosa (BN)], overweight controls (C-OW), normal-weight (C-NW). Participants passively viewed pictures of stimuli neutral a cue reactivity design. Two classification analyses were conducted. First, we used multivariate pattern recognition techniques decode...
This study investigates the prediction of mild cognitive impairment-to-Alzheimer's disease (MCI-to-AD) conversion based on extensive multimodal data with varying degrees missing values.Based Alzheimer's Disease Neuroimaging Initiative from MCI-patients including all available modalities, we predicted to AD within 3 years. Different ways replacing in combination different classification algorithms are compared. The performance was evaluated features prioritized by experts and automatically...
Postoperative cognitive dysfunction (POCD) is a detrimental complication after surgery with lasting impact on the patients' daily life. It most common postoperative delirium. Dopaminergic has been suggested to play role in delirium, but little knowledge exists regarding its relevance for POCD. We hypothesized that POCD associated altered resting-state functional connectivity of ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) magnetic resonance imaging (fMRI) before at...
Objective Here, we use pattern-classification to investigate diagnostic information for multiple sclerosis (MS; relapsingremitting type) in lesioned areas, areas of normalappearing grey matter (NAGM), and normal-appearing white (NAWM) as measured by standard MR techniques. Methods A lesion mapping was carried out an experienced neurologist Turbo Inversion Recovery Magnitude (TIRM) images individual subjects. Combining this with templates from a neuroanatomic atlas, the TIRM were segmented...
Purpose To improve the resolution of elasticity maps by adapting motion and distortion correction methods for phase-based magnetic resonance imaging (MRI) contrasts such as elastography (MRE), a technique measuring mechanical tissue properties in vivo. Materials Methods MRE data brain were acquired with echo-planar (EPI) at 3T (n = 14) 7T 18). Motion parameters estimated using magnitude images. The real imaginary part complex corrected separately recombined. width point-spread function (PSF)...
Prospective clinical studies support a link between psychological stress and multiple sclerosis (MS) disease severity, peripheral systems are frequently dysregulated in MS patients. However, the exact neurobiological symptoms is unknown. To evaluate neural responses parameters, we used an arterial-spin-labeling functional MRI paradigm 36 patients 21 healthy controls. Specifically, measured brain activity during mental arithmetic with performance-adaptive task frequency performance feedback...
Background: Fatigue in multiple sclerosis (MS) is conceived as a multidimensional construct. Objectives: This study aims to describe the changes of balance and gait parameters after 6 min walking (6 MW) potential quantitative markers for perceptions state fatigue trait MS. Methods: A total 19 patients with MS (17 fatigue) 24 healthy subjects underwent static posturography, analysis, ratings perceived exertion before MW. Results: MW was exhaustive, but both groups featured more dynamic...
Depression is among the most common comorbidities in multiple sclerosis and has severe psychosocial consequences. Alterations neural emotion regulation amygdala prefrontal cortex have been recognized as key mechanism of depression but never investigated depression. In this cross-sectional observational study, we employed a functional MRI task investigating by contrasting regulated versus unregulated negative stimulus perception 16 persons with (47.9 ± 11.8 years; 14 female) 26 without (47.3...
Decision-making (DM) abilities deteriorate with multiple sclerosis (MS) disease progression which impairs everyday life and is thus clinically important.To investigate the underlying neurocognitive processes their relation to regional gray matter (GM) loss induced by MS.We used a functional magnetic resonance imaging (fMRI) Iowa Gambling Task measure DM-related brain activity in 36 MS patients 21 healthy controls (HC). From this activity, we determined neural parameters of two cognitive...
Although multiple sclerosis (MS) is frequently accompanied by visuo-cognitive impairment, especially functional brain mechanisms underlying this impairment are still not well understood. Consequently, we used a MRI (fMRI) backward masking task to study visual information processing stratifying unconscious and conscious in MS. Specifically, 30 persons with MS (pwMS) 34 healthy controls (HC) were shown target stimuli followed mask presented 8-150 ms later had compare the reference stimulus....
Abstract The advent of functional magnetic resonance imaging (fMRI) brain function 20 years ago has provided a new methodology for non-invasive measurement that is now widely used in cognitive neuroscience. Traditionally, fMRI data been analyzed looking overall activity changes regions response to stimulus or task. Now, recent developments have introduced more elaborate, content-based analysis techniques. When multivariate decoding applied the detailed patterning regionally-specific...