Biology subjects

Bartels, R.

Publications and source records attributed to Bartels, R..

3 recordsLinked to original sources

bioRxiv2026

Impact of Axon Model Complexity on Deep Brain Stimulation: A Comparative Analysis of MRG and Cohen Double-Cable Models

Deep brain stimulation (DBS) modeling relies heavily on biophysical neuron models to estimate neural activation thresholds and predict stimulation spread. In this study, we systematically compared a widely adopted axon model, the McIntyre-Richardson-Grill (MRG) model (Model I), with a more detailed biophysical model, the Cohen model (Model II), to assess how structural and electrophysiological differences affect predicted DBS outcomes. Electric field distributions generated by 2202 DBS lead were applied to the neuron models as extracellular input stimuli. Both models were simulated under biphasic pulse stimulation across varying axon-electrode distances, pulse widths, and stimulation frequencies. Activation distances ranged from approximately 2 to 10 mm depending on stimulation parameters and contact location. At 2 mA, Model I achieved an activation distance of 6 mm, whereas Model II reached 10 mm, indicating greater excitability. Across matched fiber tracts, threshold differences ranged from -1.40 mA to 0.27 mA, with Model II requiring lower thresholds in 97.7% of cases. Both models showed a strong inverse relationship between pulse width and activation threshold. However, frequency responses differed: Model II exhibited increasing thresholds at higher frequencies, while Model I showed a slight decrease. Machine learning regressors trained on distance, pulse width, and frequency achieved high predictive accuracy, with Gradient Boosting performing best. Model II demonstrated superior prediction metrics (R^2 = 0.986; RMSE = 0.045 mA; MAE = 0.034 mA) compared to Model I (R^2 = 0.977; RMSE = 0.089 mA; MAE = 0.068 mA). Overall, both models reliably estimate DBS-induced activation, but structural differences significantly affect excitability and frequency-dependent behavior. With appropriate awareness of their respective strengths and limitations, either model can be used to derive activation distances for estimating electric field isolevels and the volume of tissue activated in patient-specific DBS simulations.

biophysics↗

bioRxiv2026

ACPC-MAP: A protocol for manually aligning structural T1-weighted Magnetic Resonance Images to the Anterior Commissure - Posterior Commissure plane according to clinical standards.

Realigning structural MR images to stereotactic AC-PC space is a standard procedure that enhances anatomical consistency both within and across neuroimaging studies, allowing for precise spatial localization and reliable cross-subject comparisons in both clinical and research contexts. However, different versions of AC-PC spaces, stemming from varying definitions of the AC-PC axis as outlined in common stereotactic atlases like Talairach and Schaltenbrand, often lead to discrepancies between the neurosurgical and neuroimaging communities. Manual realignment of structural MR images to the clinically used version of the AC-PC plane is often necessary to validate the results of automated methods or to realign the image when these methods fail. Furthermore, manual realignment provides a critical ground truth for the development of new automated tools. However, such manual interventions are typically performed in a non-standardised manner by domain experts who possess the specialized knowledge of neuroanatomy and neuroimaging required to ensure accurate alignment. To address these challenges, we have developed and validated a standardized protocol for manually realigning structural MR images to the clinically used Schaltenbrand AC-PC plane, using a set of visual criteria to ensure accurate realignment. This protocol can be used to manually align images, verify results, validate existing automated methods, or generate ground truth data for developing new automated techniques.

neuroscience↗

bioRxiv2023

Spatial N-glycan rearrangement on α5β1 integrin nucleates galectin-3 oligomers to determine endocytic fate α

Membrane glycoproteins frequently adopt different conformations when altering between active and inactive states. Here, we discover a molecular switch that exploits dynamic spatial rearrangements of N-glycans during such conformational transitions to control protein function. For the conformationally switchable cell adhesion glycoprotein 5{beta}1 integrin, we find that only the bent-closed state arranges N-glycans to nucleate the formation of up to tetrameric oligomers of the glycan-binding protein galectin-3. We propose a structural model of how these galectin-3 oligomers are assembled and how they clamp the bent-closed state to prime it for endocytic uptake and subsequent retrograde trafficking to the Golgi for polarized distribution in cells. Our findings highlight an unexpectedly dynamic regulation of the glycan landscape at the cell surface to achieve oligomerization of galectin-3. Galectin-3 oligomers are thereby identified as decoders of defined spatial patterns of N-glycans and as functional extracellular interactors of specifically the bent- closed conformational state of 5{beta}1 integrin and possibly other family members.

cell biology↗