Optimal Neural States
Influence of Prior and Imagined Movements on Motor Adaptation – Magdalena Gippert
Magdalena Gippert
In my PhD project I explore the effectiveness of different prior movements on motor adaptation and their neural correlates. Prior movement kinematics of the opposite arm can serve as effective cues for force field-specific motor adaptation, showing that linked movements across body parts can influence adaptation processes (Gippert et al., 2023, J Neurosci). In addition, motor imagery of a prior movement also allows adaptation, supporting the idea of functional equivalence between motor imagery and executed movements in this context (Gippert et al., 2025, PNAS). My work provides insights into motor learning mechanisms, with implications for rehabilitation and skill training by leveraging both actual and imagined movement sequences to improve motor adaptation.
In my PhD project I explore the effectiveness of different prior movements on motor adaptation and their neural correlates. Prior movement kinematics of the opposite arm can serve as effective cues for force field-specific motor adaptation, showing that linked movements across body parts can influence adaptation processes (Gippert et al., 2023, J Neurosci). In addition, motor imagery of a prior movement also allows adaptation, supporting the idea of functional equivalence between motor imagery and executed movements in this context (Gippert et al., 2025, PNAS). My work provides insights into motor learning mechanisms, with implications for rehabilitation and skill training by leveraging both actual and imagined movement sequences to improve motor adaptation.
Functional, Structural, and Mechanistic Aspects of Alpha Oscillations - Alina Studenova
Alina Studenova
Alpha rhythm is the most prominent and widely studied dynamical correlate of cognition in the human brain. The overarching goal of my research program is to understand how the alpha rhythm that is measured non-invasively on the scalp relates to neuronal activity. In particular, I’m looking for answers to the following questions: How do resting-state alpha power and task-based alpha amplitude change relate to microstructure at different cortical depths? What is the underlying mechanism of alpha amplitude change during a task? How could the alpha rhythm relation to cognitive mental processes be mediated by brain microstructure? Overall, the aim of this research program is to bridge research evidence from different recording modalities in order to construct an all-encompassing view of brain dynamics and cognition.
Alpha rhythm is the most prominent and widely studied dynamical correlate of cognition in the human brain. The overarching goal of my research program is to understand how the alpha rhythm that is measured non-invasively on the scalp relates to neuronal activity. In particular, I’m looking for answers to the following questions: How do resting-state alpha power and task-based alpha amplitude change relate to microstructure at different cortical depths? What is the underlying mechanism of alpha amplitude change during a task? How could the alpha rhythm relation to cognitive mental processes be mediated by brain microstructure? Overall, the aim of this research program is to bridge research evidence from different recording modalities in order to construct an all-encompassing view of brain dynamics and cognition.
Heart-Brain Interactions in Health and Disease - Paul Steinfath
Paul Steinfath
The interaction between brain and body is increasingly being recognized as an important feature for our understanding of cognitive functions, emotions, and overall well-being. In my research, I investigate electrophysiological markers for cardiac activity, primarily heartbeat evoked potentials (HEP) and the methods that are used to study them. Since HEPs are prone to being confounded by heartbeat-unrelated activity, part of my work is focused on the development of robust methods for their analysis (Steinfath et al., 2025, IMAG). In addition, since the HEP field is challenged by variable findings, we (Maria Azanova, Nikolai Kapralov, and I) asked ourselves the question of whether this heterogeneity could be related to the diversity of methods used. To answer this question, we systematically reviewed 132 HEP studies with a focus on the methods used from data acquisition to statistical analysis (Steinfath, Azanova, Kapralov et al., 2025, BioRxiv). Lastly, we empirically investigate the influence of data analysis choices on HEP and the HEP to anxiety association in a multiverse analysis of a large population-based dataset (together with Maria Azanova, in prep.).
The interaction between brain and body is increasingly being recognized as an important feature for our understanding of cognitive functions, emotions, and overall well-being. In my research, I investigate electrophysiological markers for cardiac activity, primarily heartbeat evoked potentials (HEP) and the methods that are used to study them. Since HEPs are prone to being confounded by heartbeat-unrelated activity, part of my work is focused on the development of robust methods for their analysis (Steinfath et al., 2025, IMAG). In addition, since the HEP field is challenged by variable findings, we (Maria Azanova, Nikolai Kapralov, and I) asked ourselves the question of whether this heterogeneity could be related to the diversity of methods used. To answer this question, we systematically reviewed 132 HEP studies with a focus on the methods used from data acquisition to statistical analysis (Steinfath, Azanova, Kapralov et al., 2025, BioRxiv). Lastly, we empirically investigate the influence of data analysis choices on HEP and the HEP to anxiety association in a multiverse analysis of a large population-based dataset (together with Maria Azanova, in prep.).
Neurophysiological Mechanisms of Action Observation and Motor Imagery - Emma Nesbit
Emma Nesbit
Action observation combined with motor imagery (AOMI) paradigms, wherein participants mentally rehearse observed motor sequences, modulate corticospinal excitability and activate distributed sensorimotor networks, including primary motor cortex (M1), premotor areas, and posterior parietal regions, without eliciting detectable peripheral motor output. The neuroplasticity-inducing approach of AOMI holds significant translational potential for optimising neurorehabilitation interventions, particularly in post-stroke motor recovery, and for enhancing motor skill consolidation in athletic performance contexts and fine motor learning paradigms. My doctoral research encompasses two synergistic objectives:
1) Understanding the neurophysiological substrates of motor imagery: I aim to delineate the mechanistic basis of imagery-induced cortical plasticity, particularly when coupled with action observation or multimodal sensory integration, through electroencephalography (EEG) and kinematic assessments using a Kinarm robotic exoskeleton system.
2) Developing evidence-based therapeutic paradigms: Leveraging these foundational neurophysiological findings, I wish to contribute to developing optimised AOMI protocols to maximise motor recovery in (post-stroke) patients and/or enhance skill acquisition in healthy individuals.
Action observation combined with motor imagery (AOMI) paradigms, wherein participants mentally rehearse observed motor sequences, modulate corticospinal excitability and activate distributed sensorimotor networks, including primary motor cortex (M1), premotor areas, and posterior parietal regions, without eliciting detectable peripheral motor output. The neuroplasticity-inducing approach of AOMI holds significant translational potential for optimising neurorehabilitation interventions, particularly in post-stroke motor recovery, and for enhancing motor skill consolidation in athletic performance contexts and fine motor learning paradigms. My doctoral research encompasses two synergistic objectives:
1) Understanding the neurophysiological substrates of motor imagery: I aim to delineate the mechanistic basis of imagery-induced cortical plasticity, particularly when coupled with action observation or multimodal sensory integration, through electroencephalography (EEG) and kinematic assessments using a Kinarm robotic exoskeleton system.
2) Developing evidence-based therapeutic paradigms: Leveraging these foundational neurophysiological findings, I wish to contribute to developing optimised AOMI protocols to maximise motor recovery in (post-stroke) patients and/or enhance skill acquisition in healthy individuals.
Neural Correlates of Tactile Mental Imagery - Wenyue Liu
Wenyue Liu
Mental imagery—the ability to represent and manipulate information without sensory input—is an important part of cognitive function. While most research has focused on visual and motor domains, tactile mental imagery (TMI) remains largely unexplored. My PhD project combines EEG, ultra-high field layer fMRI and multimodal physiology recording (ECG, respiration) to investigate the micro-anatomy of TMI and how it is modulated by interoceptive signals, offering new insights into top-down sensory information processing.
Mental imagery—the ability to represent and manipulate information without sensory input—is an important part of cognitive function. While most research has focused on visual and motor domains, tactile mental imagery (TMI) remains largely unexplored. My PhD project combines EEG, ultra-high field layer fMRI and multimodal physiology recording (ECG, respiration) to investigate the micro-anatomy of TMI and how it is modulated by interoceptive signals, offering new insights into top-down sensory information processing.
Structural and Functional Correlates of Oscillatory Dynamics in the Sensorimotor System - Kamil Kilic
Kamil Kilic
Beta oscillations (~13–30 Hz) are crucial for sensorimotor and cognitive processes, yet their exact functional role remains debated. In this project I will investigate beta bursts features in sensorimotor system. Using magnetoencephalography (MEG) and ultra-high-field 7T MRI, I will explore how distinct beta burst types relate to functional roles and how burst features correlate with cortical myelination content. This will improve our understanding of beta bursts and their potential as biomarkers for neurological conditions such as Parkinson’s disease.
Beta oscillations (~13–30 Hz) are crucial for sensorimotor and cognitive processes, yet their exact functional role remains debated. In this project I will investigate beta bursts features in sensorimotor system. Using magnetoencephalography (MEG) and ultra-high-field 7T MRI, I will explore how distinct beta burst types relate to functional roles and how burst features correlate with cortical myelination content. This will improve our understanding of beta bursts and their potential as biomarkers for neurological conditions such as Parkinson’s disease.
Neural modulation effects of AI-generated faces - Yonghao Chen
Yonghao Chen
With the rapid advancement of computer-generated graphics (CG) and generative neural networks, distinguishing AI-generated images or videos from real ones has become increasingly difficult. My Ph.D. project examines the neural mechanisms underlying the perception of “realism” in AI-generated faces by integrating EEG and behavioral analyses, with a particular focus on alpha oscillatory activity.