TRR 295


Insights and latest results of our research are regularly published in peer-reviewed journals. The majority of our articles are published open access to ensure the availability to a broad audience including affected people and the general lay public.

Desynchronizing two oscillators while stimulating and observing only one. 

Mau ET, Rosenblum M. 


In this paper, we focus on desynchronizing two self-sustained oscillators by short pulses delivered to the system in a phase-specific manner. We analyze a non-trivial case when we cannot access both oscillators but stimulate only one.
Published: Jul 2023

Neuroimaging-based analysis of DBS outcomes in pediatric dystonia: Insights from the GEPESTIM registry.

Al-Fatly B, Giesler SJ, Oxenford S, Li N, Dembek TA, Achtzehn J, Krause P, Visser-Vandewalle V, Krauss JK, Runge J, Tadic V, Bäumer T, Schnitzler A, Vesper J, Wirths J, Timmermann L, Kühn AA, Koy A; GEPESTIM consortium.


We assembled pediatric normative neuroimaging resources from open-access datasets in order to comply with age-related anatomical and functional differences in pediatric DBS populations.
Published: Jun 2023

Insights and opportunities for deep brain stimulation as a brain circuit intervention.

Neumann WJ, Horn A, Kühn AA.


This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS.
Published: Jun 2023

A First Methodological Development and Validation of ReTap: An Open-Source UPDRS Finger Tapping Assessment Tool Based on Accelerometer-Data

Habets JGV, Spooner RK, Mathiopoulou V, Feldmann LK, Busch JL, Roediger J, Bahners BH, Schnitzler A, Florin E, Kühn AA


We assessed finger tapping in 37 people with Parkinson’s disease (PwP) during routine treatment follow ups and analyzed their 350 sessions of 10-s tapping using index finger accelerometry. Herein, we developed and validated ReTap, an open-source tool for the automated prediction of finger tapping scores.
Published: May 2023

Learning how network structure shapes decision-making for bio-inspired computing.

Schirner M, Deco G, Ritter P.


To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants.
Published: May 2023

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Neumann WJ, Gilron R, Little S, Tinkhauser G


The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years.
Published: May 2023