Mathematical models and signal processing for Neuroscience

One research topic concerns the development of biologically inspired neural networks. In this area, the group develops models of sensory integration between different modalities (auditory, visual, tactile, proprioceptive), to achieve a theoretical understanding of the underlying neural mechanisms and for potential model application in clinics in order to improve cognitive or motor deficits. Other models are developed to analyze object recognition and formulate hypotheses on semantic memory and its relationship with language acquisition. Models of oscillatory neuronal populations are used to investigate the role of brain rhythms in sleep and wakefulness, to study the memorization of event sequences in the hippocampus, and to explore rhythm propagation and connectivity among brain regions. Basal ganglia models are developed to study the response of Parkinsonian subjects to levodopa treatment. The modeling approach is supported by an experimental approach devoted to the acquisition and processing of physiological signals with particular reference to electromyographic signals (EMG) for the analysis of muscle activation, electrocardiographic signals (ECG) for the analysis of heart variability, and electroencephalographic signals (EEG) interpreted via advanced analysis techniques, including the estimation of cortical sources, the estimation of connectivity among cortical regions, graph theory and artificial intelligence techniques. Overall, these approaches allow the investigation of the neural bases underlying cognitive processes (e.g. attention, fear conditioning, working memory) and motor processes (e.g. postural control, reaching movements), the characterization of brain mechanism modifications in neurological disorders (e.g. autism spectrum disorders, schizotypy, epilepsy) or in states of altered consciousness (e.g. sleep, coma), and the study of the effects of brain stimulation procedures.

Settori ERC

  • PE7_7 – Signal processing 
  • LS5_16 - Systems and computational neuroscience (e.g. modelling, simulation, brain oscillations, connectomics)
  • LS5_5 – Neural Networks and plasticity

Scientific coordinator: Prof. Elisa Magosso 

Faculty

Davide Borra

Junior assistant professor (fixed-term)

Cristiano Cuppini

Associate Professor

Elisa Magosso

Full Professor

Mauro Ursino

Full Professor

PhD Students and Research Fellows

Matteo Fraternali

Research fellow

Melissa Monti

PhD Student

Teaching tutor

Silvana Pelle

PhD Student

Giulia Piermaria

Research fellow

Gabriele Pirazzini

PhD Student

Research fellow

Teaching tutor