Data science and computational modelling

Understanding the biological mechanisms in the brain activity during learning necessities deriving the behavioural motifs and juxtaposing them with the brain activity. In this project, we analyse the behavioural data of subjects (animals/humans) during reward-based learning experiments and derive their learning motifs. We define a learning motif as a behavioural policy that the subject exhibits during parts of the learning process. We develop ...

Multi-layer networks lend themselves for the construction of phenotypes of individuals, because intra-layer and inter-layer similarity can be used to express elaborate forms of proximity between individuals in the same layer and between features/layers. However, the features of these individuals change over time: people grow older, degenerative diseases lead to cognition decline, exercising leads gradually to better health. Translating this ev...

Parkinson’s disease (PD) is the second most common neurodegenerative disease with many motor and non-motor symptoms that range from impairments of motor capabilities to decreased sense of smell and cognitive abilities. Thus, unidimensional quantification of PD progression is inaccurate and can potentially introduce biases into the analysis of pathology. At the same time, the long-term nature of PD means that randomized controlled experiments a...

Objective ranking and clustering of behavioural data that utilize different metrics is an essential foundation for understanding the relationship between behaviour and physiology, as well as neurological processes in medicine and neuroscience. However, the inherent complexity of biological systems being studied and the small data size usually produced by experimental studies present challenges for the existing statistical methods. In this proj...