Projects
Major topics of somatosensory group
- Determinants and consequences of somatosensory perception
- Sequelae of somatosensory stroke (especially poststroke pain)
- BCI and stroke rehabilitation
- EEG/MEG source reconstruction methodology
How expectations shape brain-body interactions - a near-threshold somatosensory detection task
I investigate how expectations shape brain-body interactions in a near-threshold somatosensory detection task involving electrical stimulation of the index finger and confidence ratings. While collecting EEG, respiratory, cardiac, and eye-tracking data, my main focus is on respiration and its potential role in the unconscious optimisation of perceptual performance and alpha power dynamics (Kluger et al., 2021). My research includes overt manipulations of stimulus expectation (with colleague Carina Forster) and covert manipulations of temporal expectation. By varying temporal parameters, I examine how internal rhythms align with external regularities (as seen in Grund et al., 2022) and modulate perceptual sensitivity. Though focused on non-clinical populations, this work may inform future research into conditions marked by reduced physiological flexibility, disrupted attentional or sensorimotor function.
Neural correlates of mechanical versus electrical somatosensory detection
In my PhD project I investigate the mechanisms behind the perception of near-threshold somatosensory stimuli. The ERP component N140 correlates with conscious processing, whereas the P50 reflects processing physical stimulus characteristics (Forschack et al. 2020, Schröder et al., 2021). This finding is challenged by insights from a study using mechanical stimulation, indicating that the P50 already reflects conscious processes (Förster et al., 2025). I aim to compare the brain’s response to electrical stimulation with the response to more realistic mechanical stimulation and shine light on the origin of the somatosensory perception correlates. I combine computational and experimental methodologies by conducting an eeg study and fitting the recorded data to a biophysical model of the somatosensory microcircuit.
Neural correlates of tactile mental imagery: the micro-anatomy and interoceptive modulation
Mental imagery—the ability to represent and manipulate information without sensory input—is a core cognitive function. While most research has focused on visual and motor domains, tactile mental imagery (TMI) remains largely unexplored. This study aims to investigate the neural mechanisms of TMI, specifically focusing on the dynamics of somatosensory cortices and the interaction between interoception and top-down somatosensory information processing. We combine ultra-high field layer fMRI, EEG, and multimodal physiology recording methods (ECG, respiration) to investigate the micro-anatomy of TMI and its modulation by interoceptive signals, offering new insights into top-down sensory information processing.
Structural and functional correlates of oscillatory dynamics in sensorimotor system
In my PhD project, I will investigate the structural and functional correlates of beta oscillatory dynamics in the human sensorimotor system, using magnetoencephalography (MEG) and 7T MRI. The first study focuses on analyzing the diverse temporal and spectral properties of beta bursts to determine their distinct roles in sensorimotor processing. The second study examines how these beta burst features relate to cortical myelin content, aiming to uncover structural underpinnings using 7T MRI.
Regional and Whole-brain Alterations in Functional Connectivity in Central Post Stroke Pain (CPSP)
In my PhD project, I will focus on the central post stroke patients (CPSP). In stroke patients, CPSP has a prevalence of 8%, it is frequently refractory to traditional medical treatment and it often impairs patients’ quality of life dramatically. I will explore structural and functional differences in CPSP patients and non-pain sensory stroke patients (NPSS) based on a cross-sectional (CPSP versus NPSS) and longitudinal analysis (before and after pain, comparing CPSP versus NPSS) and will identify potential predictors of CPSP based on MRI findings (resting-state, structural MRI) and clinical findings in the first week after the stroke, but BEFORE pain has occurred.
Modulating brain plasticity in stroke recovery: investigating rTMS and BCI in clinical populations
Can neurotechnology help us modulate brain plasticity to benefit clinical populations? And if so, which are the mechanisms that underlie its effect? These are the questions that I address in my PhD thesis. I focus on the effects of repetitive transcranial magnetic stimulation (rTMS) and EEG-guided brain computer interface (BCI). For this, I collaborate with Alexander Grygorian, PhD., to inspect correlates of functional plasticity after BCI; and with Anastasia Asmolova, MSc. to explore the structural correlates of brain plasticity after rTMS. Also, as my main PhD project, I explore whether the application of rTMS before BCI training can benefit motor function recovery in patients with stroke on the Neurotech stroke clinical trial.
Dopaminergic modulation on spatio-spectral EEG dynamics during BCI learning: a double-blind analysis
In my PhD project I will investigate novel neurorehabilitation strategies for stroke-related motor impairments, focusing on Brain-Computer Interfaces (BCIs) and extended reality (XR). One study explores enhancing BCI learning in individuals with BCI illiteracy through dopaminergic modulation, aiming to improve the neural signals underlying motor control. The second study adapts Mirror Therapy using Augmented Reality (AR) to provide richer somatosensory feedback during movement.
Source Reconstruction and Connectivity in M/EEG: From Simulation to Somatosensory Potentials
In my PhD project, I investigate different methods for source reconstruction of EEG and MEG (M/EEG) activity with the focus on estimation of functional connectivity between brain regions of interest. Most of my analyses rely on having ground truth information about source activity and typically require simulating the data. However, early components of evoked potentials related to perception (for example, the N20 component of the somatosensory evoked potential) provide a unique opportunity to get a relatively well-defined ground truth in real data. We utilize this opportunity to study the nuances of different methods using real data.