Research

About ICN

Our group combines a unique set of human neuroscience methods combining invasive neurophysiology, brain stimulation, machine learning and MRI based connectomics to advance neuromodulation therapies and gain mechanistic insights into brain function.

As part of the movement disorder and neuromodulation unit, we study the role of dopamine and cortex-basal ganglia networks in the physiology of movement and the pathophysiology of Parkinson's disease.

Funded through an European Research Council (ERC) starting grant, we pioneer state-specific closed-loop neurostimulation approaches that mimic the reinforcement effects of dopamine on neural circuits. In the future, we hope to develop brain circuit prostheses that can augment intrinsic brain function, through neurotechnological interventions.

Our Topics

Neurotechnology

Neurotechnology refers to the array of technologies designed to understand, interface with, or manipulate the nervous system. These technologies span a wide range of applications, from medical treatments to brain-computer interfaces, with the ultimate aim of improving brain function or compensating for neurological impairments. Our group works with invasive neurotechnology for deep brain stimulation and develops machine learning based algorithms to improve therapeutic approaches to alleviate the symptoms of brain disorders.

Dopamine

Dopamine is a neurotransmitter that plays a crucial role in many brain functions, including movement, reward, motivation, and cognitive processes.

It's heavily involved in both normal brain functioning and various neurological and psychiatric disorders. Dopamine is particularly relevant in the context of neurological and neuropsychiatric disorders where alterations in dopaminergic control of brain circuits can lead to debilitating symptoms.

Understanding the relationship of dopaminergic control, brain activity and neurological symptoms is central to our published research.

Parkinson's Disease

Parkinson's disease is a progressive neurodegenerative disorder primarily affecting motor function due to the degeneration of dopamine-producing neurons in the substantia nigra, a region of the brain critical for movement regulation. As dopamine levels decrease, the brain's ability to control movement becomes impaired, leading to the hallmark motor symptoms of the disease.

Our group studies the relationship of dopamine, Parkinson's disease, motor control and deep brain stimulation. We hope to develop a brain circuit prosthesis that can mimic the dynamic modulation exerted by dopamine.

Invasive neuorphysiology in patients with brain implants

Our group studies invasive brain signal recordings with a special emphasis on a mechanistic understanding of neural oscillations, which can be recorded intra- and perioperatively via implanted electrodes in patients undergoing neurosurgery. The aim of our work is to understand how the brain communicates across brain regions and how we can decipher this communication to advance neurotechnological treatment strategies, such as adaptive closed-loop stimulation. To do this, we study disease- and symptom-specific activity patterns and investigate the modulation of this activity by the pharmacological and interventional therapies. As the first and only center in Europe to perform electrocorticography (ECoG) combined with neuromodulation, we are developing a deeper understanding of how long range cortical subcortical interactions shape neural communication in health and disease. We combine these invasive recordings with MRI based whole-brain connectomics to elucidate the network nature of neural disorders and their treatments with next-generation brain implants.

Computational reproducibility for FAIR translational neuromodulation research in clinical neuroscience

We are working on the characterization of biomarkers and the development of algorithms for invasive neurotechnology. Our research has immediate translational potential for therapy optimization. However, a lack of scientific transparency and reproducibility hinders the integration of promising innovations in everyday clinical practice. We are actively developing groundbreaking data strategies for multimodal neuromodulation research. The aim of this project is to provide automated data flow algorithms from data acquisition to computationally reproducible publications.

Methods

Our strengths are the implementation of methods for multimodal and multidimensional data analysis for clinical neurotechnology applications. Our current work combines computational modelling, machine and deep learning, structural and functional connectomics (fMRI), invasive (LFP/ECoG) and non-invasive (EEG/MEG) neurophysiology, to develop the next-generation of intelligent clinical brain computer interfaces. Our neuroscientific research focus and the ERC starting grant that funds our group focusses on empirical work on neural learning and dopamine in Parkinson's disease.

Invasive Neurophysiology

local field potential recordings from deep brain stimulation (DBS) electrodes and electrocorticography (ECOG) from the cortex

Non-invasive Neurophysiology

We analyze data from electroencephalography (EEG) and magnetoencephalography (MEG).

Neuroimaging

We use both functional and structural neuroimaging with access to 3T MRI in the department of neuroradiology.

Machine learning