Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/371997

Outcome of TMS-based motor mapping depends on TMS current direction

Vink, J. J.·Petrov, P. I.·Mandija, S.·Dijkhuizen, R. M.·Neggers, S. F.
View original source ↗Export metadata ↓

Abstract

Navigated transcranial magnetic stimulation (TMS) in combination with electromyography (EMG) recordings can be used to map the brain regions in which TMS evokes motor-evoked potentials (MEPs) in certain muscles. Navigated TMS (nTMS) is used increasingly to identify the functional motor area of different muscles for clinical applications, including neurosurgical planning. However, the accuracy of TMS-based mapping of functional motor areas may depend on the TMS-induced current direction due to anisotropic cortical morphology, complicating association of the functional motor maps with neuroanatomical structures. Furthermore, it is not clear how well nTMS can distinguish nearby muscle representations on the cortical surface. We therefore investigated the functional motor maps obtained with posterior-to-anterior (PA) and lateral-to-medial (LM) TMS-induced currents within a spatially defined area by stimulating targets in a grid of locations over the left primary motor cortex in 8 healthy participants. Results were compared to functional MRI (fMRI) activation maps obtained using a voluntary opposing thumb movement task. We found that TMS applied with PA-induced currents identifies a motor area that is located significantly more anterior (8.7 - 10.4 mm depending on the muscle) with respect to an MEP motor area identified using LM-induced currents for the same muscle. Motor maps obtained with LM-induced currents show more overlap with the motor map identified using fMRI compared to PA-induced currents. In conclusion, the spatial representation of the MEP motor map identified by TMS is dependent on the direction of the induced current. These findings suggest that the application of nTMS using an LM-induced current direction corresponds best with the hand motor area as measured with fMRI.

Explore related subjects

neurosciencePreprint

Keep this discovery

BibTeXRIS

Vink, J. J., Petrov, P. I., Mandija, S., Dijkhuizen, R. M., Neggers, S. F.. 2018-07-20. Outcome of TMS-based motor mapping depends on TMS current direction. https://doi.org/10.1101/371997

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗
bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗
bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗