A5003780363- Transcranial Magnetic Stimulation Studies
- Functional Brain Connectivity Studies
- Neuroscience and Neural Engineering
- Non-Destructive Testing Techniques
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Muscle activation and electromyography studies
- Advanced MRI Techniques and Applications
- Ultrasonics and Acoustic Wave Propagation
- Advanced Neuroimaging Techniques and Applications
- Structural Health Monitoring Techniques
- Electrical and Bioimpedance Tomography
- Probabilistic and Robust Engineering Design
- Motor Control and Adaptation
- Neurological disorders and treatments
- Magnetic Properties and Applications
- Reading and Literacy Development
- Neural and Behavioral Psychology Studies
- Welding Techniques and Residual Stresses
- Advanced Memory and Neural Computing
- stochastic dynamics and bifurcation
- Model Reduction and Neural Networks
- Electric Motor Design and Analysis
- Neural Networks and Applications
- Optical Imaging and Spectroscopy Techniques
Leipzig University of Applied Sciences
2020-2025
Max Planck Institute for Human Cognitive and Brain Sciences
2018-2025
Aarhus University
2023-2024
Technische Universität Ilmenau
2014-2023
University Hospital Leipzig
2020
Institute for Bioprocessing and Analytical Measurement Techniques
2020
Max Planck Society
2018-2019
Oldenburger Institut für Informatik
2015-2016
University of Virginia Hospital
2002
Pennsylvania State University
1974
Despite the widespread use of transcranial magnetic stimulation (TMS), precise cortical locations underlying resulting physiological and behavioral effects are still only coarsely known. To date, mapping strategies have relied on projection approaches (often termed "center gravity" approaches) or maximum electric field value evaluation, therefore localize stimulated site approximately indirectly. Focusing motor cortex, we present validate a novel method to reliably determine effectively at...
Uncertainty surrounding ohmic tissue conductivity impedes accurate calculation of the electric fields generated by non-invasive brain stimulation. We present an efficient and generic technique for uncertainty sensitivity analyses, which quantifies reliability field estimates identifies most influential parameters. For this purpose, we employ a non-intrusive generalized polynomial chaos expansion to compactly approximate multidimensional dependency on conductivities. demonstrate that proposed...
Transcranial magnetic stimulation (TMS) is a powerful tool to investigate causal structure-function relationships in the human brain. However, precise delineation of effectively stimulated neuronal populations notoriously impeded by widespread and complex distribution induced electric field. Here, we propose method that allows rapid feasible cortical localization at individual subject level. The functional relationship between field behavioral effect quantified combining experimental data...
Abstract Transcranial magnetic stimulation (TMS) is an invaluable non-invasive brain (NIBS) technique to modulate cortical activity and behavior, but high within- between-participant variability limits its efficacy reliability. Here, we explore the potential of electric field (e-field) based TMS dosing reduce discuss current challenges as well future pathways. In contrast previous approaches, e-field better matches strength across areas, both within individuals. Challenges include...
The left temporo-parietal cortex (TPC) is critical for phonological decoding during reading and appears hypoactive in dyslexia. Therefore, a promising approach to alleviating deficits dyslexia modulate TPC functioning. However, it unclear how neurostimulation alters activity network interactions To address this gap, we combined facilitatory transcranial magnetic stimulation (TMS) the adults with an overt word pseudoword task functional neuroimaging. We found TMS-induced improvements reading,...
A fast BEM (boundary element method) based approach is developed to solve an EEG/MEG forward problem for a modern high-resolution head model. The method utilizes charge-based accelerated by the multipole (BEM-FMM) with adaptive mesh pre-refinement (called b-refinement) close singular dipole source(s). No costly matrix-filling or direct solution steps typical standard are required; generates on-skin voltages as well MEG magnetic fields models within 90 seconds after initial model assembly...
Conceptual knowledge is central to human cognition. The left posterior inferior parietal lobe (pIPL) implicated by neuroimaging studies as a multimodal hub representing conceptual related various perceptual–motor modalities. However, the causal role of pIPL in processing remains unclear. Here, we transiently disrupted function with transcranial magnetic stimulation (TMS) probe its relevance for retrieval action and sound knowledge. We compared effective TMS over sham TMS, while healthy...
When modeling transcranial electrical stimulation (TES) and magnetic (TMS) in the brain, meninges - dura, arachnoid, pia mater are often neglected due to high computational costs.We investigate impact of meningeal layers on cortical electric field TES TMS while considering headreco segmentation as base model.We use T1/T2 MRI data from 16 subjects apply boundary element fast multipole method with adaptive mesh refinement, which enables us accurately solve this problem establish convergence at...
Abstract Objective. In our recent work pertinent to modeling of brain stimulation and neurophysiological recordings, substantial errors in the computed electric field potential have sometimes been observed for standard multi-compartment head models. The goal this study is quantify those and, further, eliminate them through an adaptive mesh refinement (AMR) algorithm. concentrates on transcranial magnetic (TMS), electrical (TES), electroencephalography (EEG) forward problems. Approach. We...
Abstract We derived computationally efficient average response models of different types cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. used 24 reconstructions pyramidal cells (PC) layer 2/3, 245 small, nested, and large basket 4, 30 PC 5 with morphologies for deriving models. With these models, it is possible efficiently estimate the stimulation thresholds depending on underlying field distribution in brain, without having implement...
When modeling transcranial magnetic stimulation (TMS) in the brain, a fast and accurate electric field solver can support interactive neuronavigation tasks as well comprehensive biophysical modeling. We formulate, test, disseminate direct (i.e., non-iterative) TMS that accurately determine global fields for any coil type everywhere high-resolution MRI-based surface model with ~ 200,000 or more arbitrarily selected observation points within approximately 5 s, solution time itself of 3 s. The...
Notwithstanding advances in computational models of neuromodulation, there are mismatches between simulated and experimental activation thresholds. Transcranial Magnetic Stimulation (TMS) the primary motor cortex generates evoked potentials (MEPs). At threshold MEP generation, whole-head predict macroscopic (at millimeter scale) electric fields (50-70 V/m) which considerably below conventionally cortical neuron thresholds (175-350 V/m). We hypothesize that this apparent contradiction is part...
The dorsolateral prefrontal cortex (DLPFC) is a principal target for repetitive transcranial magnetic stimulation (rTMS) in the treatment of major depressive disorder, with therapeutic effects hypothesized to be mediated by connectivity between DLPFC and subgenual anterior cingulate (sgACC). Interestingly, these depression-related hubs are also part heart-brain axis, thus potentially rendering stratification individual depression targets possible tapping into short-term heart rate modulation...