Speaker Biography
Dr Ioannis Delis obtained a M.Eng. from the University of Patras, Greece (2006) and a M.Sc. from the University of Minnesota, USA (2009) both in Electrical and Computer Engineering and a Ph.D. in Computational Neuroscience from the University of Genoa, Italy (2013). He worked as a post-doctoral researcher at the University of Glasgow (Jan 2013 – Dec 2015) and Columbia University, New York (Jan 2016 – Dec 2017). Since January 2018, he has been a Lecturer at the School of Biomedical Sciences of the University of Leeds where he participated in the Sport & Exercise Sciences and Neuroscience research groups. Dr Delis is a member of the Motor Control & Neurorehabilitation and the Neural Circuits research themes, where he lead the research on Neural Data Science. Specifically, he developed data analytical approaches (based on machine learning, information theory and Bayesian modelling) to answer neuroscientific questions on human motor control, decision-making, multi-sensory processing & sensory-motor coupling.
If you wish to meet the speaker please contact Dr Aldo Faisal – a.faisal@imperial.ac.uk
Talk Abstract
Human sensorimotor behaviour relies on the dynamic interplay of multiple neural processes and the interactions between the nervous and the musculoskeletal systems. These interactions remain poorly understood primarily because of the lack of unifying methodology that allows their characterization at both the behavioural and neural levels. Here I will present our recent work on decoding neurophysiological signals to explain sensorimotor behaviour.
In movement execution, modularity of the motor system has been proposed as an efficient strategy to solve the degrees-of-freedom problem. After reviewing recent work in this field, I will introduce a neurally-plausible model of modularity in muscle activity. I will demonstrate that the proposed modularity model unifies existing models and yields a compact representation of motor signals as well as a reliable mapping to the task at hand.
Then, I will discuss the process of active sensing where movement is used to gather information in order to make perceptual choices. I will first present a behavioural paradigm to study active exploration and perceptual selection. I will then introduce a computational framework for the joint analysis of neural and behavioural signals. This approach, coupled with the cognitive modelling of decision-making behaviours, provides a window into the mechanisms underlying active decision formation. Finally, I will present recent work aiming to extend the above methodology to study multi-sensory information processing.