Levin Kuhlmann

The paper examines how naturalistic context affects psilocybin's frequency-specific electrophysiological effects using EEG data from 56 participants.

This study shows psilocybin improves cognitive flexibility in rats under food restriction but not after anorexia exposure, with changes in striatal dopamine signaling.

This paper presents a simulation framework to evaluate EEG source localisation methods by generating biologically plausible seizure dynamics and EEG signals with known ground truth.

This paper uses structural eigenmodes of the brain to improve EEG source localization in epilepsy, finding geometric eigenmodes slightly outperform connectome eigenmodes.

The paper uses MEG data to infer neural connectivity and dynamics during altered states of consciousness, finding correlations between consciousness levels and specific brain regions and dynamics.

This study develops machine learning models to predict co-regulatory modules and gene regulatory networks in the heart using epigenomic data, identifying key transcription factors involved in cardiac development.

Neurodesk provides a portable and reproducible neuroimaging analysis platform using software containers to enable accessible and flexible data analysis pipelines.

The paper introduces linc2function, a deep learning model that identifies and functionally annotates long noncoding RNAs using sequence, structure, and interactome features across species.

This paper demonstrates a computational model showing how orientation selectivity in V1 develops through retinal activity and Hebbian plasticity without external input.

This paper introduces a whole-brain imaging framework to identify neurophysiological mechanisms, applied to resting-state alpha rhythm, revealing key brain regions and their roles in modulating alpha power.

This paper introduces a taxonomy of seizure dynamotypes based on bifurcation theory and applies it to EEG data, identifying 16 dynamotypes and their variations across patients.

This study identifies critical slowing as a biomarker for seizure susceptibility using long-term iEEG recordings from epilepsy patients.

This study investigates the effects of NMDA-antagonist anesthetics Xe and N2O on cortical power changes using MEG and EEG source imaging, finding distinct frequency-specific patterns.