UNIverse - Public Research Portal

[FG] Kappos Ludwig

Projects & Collaborations

8 found
Show per page
Project cover

Improved prediction and montoring of CNS disorders with advanced neurophysiological and genetic assessment

Research Project  | 10 Project Members

Objective: To establish a numerical model for better characterization and prediction of the course of the two most prevalent chronic neurological disorders with high impact on quality of life in young and elderly human beings, respectively: Multiple Sclerosis (MS) and Alzheimer's disease (AD). The numerical model will contain clinical, neuropsychological, genetic, imaging and neurophysiological data. Background: Although diagnosis of MS has greatly improved over the last decade, reliable prediction of the disease course (prognosis) is still not satisfying. In AD and other dementia types diagnosis is more difficult early in the disorder and depends in part on the course of symptoms. In both disease groups, clinical examination is still the main tool to assess the course of disease and the grade of impairment. Neurophysiological measurements like electroencephalography (EEG) at rest and during visual and sensory stimulation (evoked potentials, EP) represent parameters of impulse propagation in the central nervous system. These measures are likely to be abnormal early in the course of MS and AD. Therefore, they may add important information on the prognosis in MS and AD, and on the differential diagnosis of dementias. Recent technical developments allow the recording of EEG and EP with high resolution (256 channels) resulting in precise identification and localization of pathological changes. Genetic testing is likely to further improve the prediction of the disease course. Methods: In the MS subproject one hundred patients and fifty age-matched healthy controls will be examined three times at yearly intervals. Clinical and neuropsychological examination will be complemented by high-resolution EEG and EP, genetic testing and brain imaging by magnetic resonance tomography. In the AD subproject, forty patients with dementia will be compared to forty age matched healthy controls in regard to their cognitive performance, genetic profile and results of high resolution EEG and EP. All results of the different tests will be analyzed with a statistical model, which summarizes all data of an individual to a score to predict the clinical course in MS and AD. Significance: Reliable markers of disease progression and prognosis would allow to conduct clinical trials with a smaller number of patients or in less time, thus reaching clinically meaningful results more efficiently. This is especially important in MS and AD, where innovative treatment options are entering the phase of clinical testing in coming years. Moreover, improved prediction of the course of MS and AD may be useful even in individual patients for counselling and treatment decisions.

Project cover

Investigations on the functional and structural connectivity of cognitive impairment in multiple sclerosis patients

Research Project  | 4 Project Members

Bei Patienten mit Multipler Sklerose wird in erster Linie die weisse Hirnsubstanz, die die Faserverbindungen zwischen den verschiedenen Hirnregionen enthält, durch umschriebene entzündlich-demyelinisierende Läsionen geschädigt und in ihrer Funktion beeinträchtigt. Gleichzeitig sind grundlegende kognitive Funktionen wie Reaktion, Aufmerksamkeit und Kurzzeitgedächtnis relativ häufig bei MS Patienten beeinträchtigt. Erst vor kurzem konnte gezeigt werden, dass eine funktionelle Konnektivität zwischen funktionell verbundenen Hirnregionen besteht. Mit der funktionellen Konnektivitäts-Magnetresonanztomographie (fcMRT) steht eine neue MRT-Technik zur Verfügung, die auf der Grundlage von niedrigfrequenten Fluktuationen des BOLD-Signals (Blood Oxygenation Level Dependent) funktionell verbundene Areale im akustischen, motorischen System und dem Kurzzeitgedächtnis identifizieren kann. Durch die charakteristischen Läsionen in der weissen Substanz bei der MS kann es zu sogenannten Diskonnektions-Syndromen kommen, die anders als einzelne Läsionen in der Hirnrinde, wie z.B. bei einem Schlaganfall Geistesfähigkeiten in typischer Art und Weise beeinträchtigen. Dabei werden die langen Faserverläufe zwischen fronto-temporo-parietalen Netzwerkanteilen, funktionellen Netzwerke bei der MS beeinträchtigt, als Ursache komplexer Gedächtnis- und kognitiver Dysfunktionen. Durch den Einsatz von fcMRT und Diffusions-Tensor-Imaging (DTI) wird die Schädigung der Netzwerke und die daraus resultierenden Kurzzeitgedächtnisstörungen bei Patienten mit MS untersucht, die als Modellerkrankung für Schädigungen der Netzwerkkomponenten von Gedächtnisleistungen dient. Durch die Kombination von DTI und fcMRI werden zwei neue, vielversprechende MR-Techniken eingesetzt, um strukturelle Veränderungen und ihre funktionellen Konsequenzen wesentlich genauer darzustellen als es zuvor möglich war. Strukturelle und funktionelle Konnektivitätsveränderungen werden parallel mit etablierten neuropsychologischen Testverfahren untersucht. Die Ergebnisse der Studie sollen dazu dienen wichtige Fragen zu den Erkrankungsmechanismen und die Reaktion darauf in Form von kompensatorischen Mechanismen und Plastizität systematisch zu beleuchten.

Project cover

dreaMS Validation Study 1

Research Project  | 1 Project Members

Background of the Clinical Trial

Multiple Sclerosis (MS) is a chronic inflammatory disease of the central nervous system, characterized by a wide range of physical and cognitive symptoms. Clinical assessments, magnetic resonance imaging (MRI), and laboratory analyses form the basis of diagnosis and treatment decisions. However, traditional tools such as the Expanded Disability Status Scale (EDSS) have significant limitations. These include variability between examiners, insensitivity to subtle changes, and limited utility in tailoring individualized treatment strategies.

Digital biomarkers represent a promising new approach. Collected via smartphones, they include passive data (e.g., step count, sleep duration) and active performance-based measures (e.g., tests of walking, dexterity, or cognition). Because they are gathered frequently and in the patient’s natural environment, digital biomarkers can offer more granular, objective, and ecologically valid insights into disease progression.


To harness this potential, the Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), in collaboration with the digital health company Indivi, developed dreaMS - a smartphone app specifically designed for people with MS (PwMS). The app includes a range of interactive “challenges” that assess functions commonly affected by MS, such as mobility, dexterity, vision, and cognition.


We are currently conducting three clinical studies to validate the dreaMS app: Validation Study 1 (VS1, see below), Validation Study 2 and Clinnova Study.


Study Objectives

The primary aim of the dreaMS Validation Study 1 (VS1) is to identify and validate digital biomarkers that accurately reflect neurological disability in PwMS. These digital measures have the potential to inform patient care, support clinical research, and guide regulatory decisions on MS therapies. Beyond validation, the study seeks to establish a collaborative platform for future studies and international research partnerships. Ultimately, this work aims to advance personalized MS monitoring and improve outcomes through novel digital health technologies.

Project cover

dreaMS Validation Study 2

Research Project  | 1 Project Members

Background of the Clinical Trial

Multiple Sclerosis (MS) is a chronic, inflammatory disease affecting the central nervous system. Diagnosis and treatment decisions for people with MS (PwMS) rely on clinical assessments, imaging, and body fluid evaluations. However, the current methods provide limited predictive value for individualizing treatments. Emerging digital measures, like the dreaMS software program developed by the Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB) in collaboration with Indivi, aim to offer more granular, continuous, and remote monitoring of disease progression. These digital tools are embedded in a mobile app and have shown promise in generating digital biomarkers (DB) that may enhance traditional MS assessments.


Goal of the Study

The main objective of the DreaMS VS2 study is to provide validated digital biomarkers that can be used for patient care, research, and regulatory decisions related to MS treatment. Beyond validation, the study aims to create a collaborative research platform for future studies and international academic partnerships. This research will contribute to more precise MS monitoring and treatment, improving the quality of life for PwMS by leveraging advanced digital health technologies.


Method of the Study

The DreaMS VS2 study is an international research project designed to validate the digital biomarkers generated through the dreaMS software. It builds on the previous DreaMS VS1 study, which included 300-400 PwMS and assessed the clinical validity of candidate digital biomarkers (cDB) related to movement, balance, dexterity, vision, and cognition. The current study involves a larger international population, systematically replicating the results of VS1 while extending the evaluation to additional patient-relevant outcomes such as hospitalizations and quality of life. Sub-studies and deep phenotyping are included for more detailed analysis, and patients are actively involved in the study’s design and dissemination activities.