TMS-evoked EEG potentials from prefrontal and parietal cortex: reliability, site specificity, and effects of dextromethorphan

Rogasch, N.; Zipser, C.; Darmani, G.; Mutanen, T. P.; Biabani, M.; Zrenner, C.; Desideri, D.; Belardinelli, P.; Müller-Dahlhaus, F.; Ziemann, U.

doi:10.1101/480111

bioRxiv · 10.1101/480111

TMS-evoked EEG potentials from prefrontal and parietal cortex: reliability, site specificity, and effects of dextromethorphan

Rogasch, N.·Zipser, C.·Darmani, G.·Mutanen, T. P.·Biabani, M.·Zrenner, C.·Desideri, D.·Belardinelli, P.·Müller-Dahlhaus, F.·Ziemann, U.

View original source ↗Export metadata ↓

Abstract

Measuring the brains response to transcranial magnetic stimulation (TMS) with electroencephalography (EEG) offers a unique insight into the local cortical circuits and networks activated following stimulation, particularly in non-motor regions where less is known about TMS physiology. However, the mechanisms underlying TMS-evoked EEG potentials (TEPs) remain largely unknown. We assessed TEP reliability, site-specificity, and sensitivity to changes in excitatory neurotransmission mediated by n-methyl-d-aspartate (NMDA) receptors following stimulation of non-motor regions. In fourteen male volunteers, resting EEG and TEPs from prefrontal (PFC) and parietal (PAR) cortex were measured before and after administration of either dextromethorphan (an NMDA receptor antagonist) or placebo across two sessions separated by at least a week in a double-blinded pseudo-randomised crossover design. At baseline, TEPs showed lower within-than between-subject variability for both stimulation sites across sessions, demonstrating the reliability of non-motor TEPs within individuals. There were differences in amplitude between PFC and PAR TEPs across a wide time range (15-250 ms), however the signals were correlated after ~80 ms, suggesting that early peaks reflect site-specific activity, whereas late peaks reflect activity patterns less dependent on the stimulated sites. TEPs were not altered following dextromethorphan compared to placebo, however low frequency resting oscillations were reduced in power. Our findings suggest that TEPs from PFC and PAR: 1) are reliable within and variable between individuals; 2) reflect stimulation site specific activity across early time periods (<80 ms); and 3) are not sensitive to changes in NMDA receptor-mediated neurotransmission.

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Rogasch, N., Zipser, C., Darmani, G., Mutanen, T. P., Biabani, M., Zrenner, C., Desideri, D., Belardinelli, P., Müller-Dahlhaus, F., Ziemann, U.. 2018-11-27. TMS-evoked EEG potentials from prefrontal and parietal cortex: reliability, site specificity, and effects of dextromethorphan. https://doi.org/10.1101/480111

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↗