Egidio d’Angelo is Full Professor of Physiology, co-chair of the Department of Brain and Behavioral Sciences and director of the Brain Connectivity Center of IRCCS Mondino. Egidio d’Angelo coordinates brain research at the international level, spanning from neurophysiology to neurotechnology and medicine, and has uninterruptedly coordinated 9 European projects and several National projects of the Italian Ministry of Health, of the Ministry of the University and Research and other institutions over the 1995-2022 period. In the last 10 years, Egidio d’Angelo has participated as core partner and co-director in the European Flagship Human Brain Project (HBP- 2020 Framework Programme for Research and Innovation under the Framework Partnership Agreement No. 650003), aimed at bridging cellular-molecular research with integrative neuroscience through computational models and advanced ICT technologies. This HBP activity involves world-wide collaborations on neuronal and microcircuit modeling, MRI and BOLD signals, closed-loop robotic simulators, cellular recordings in vivo, neuronal modelling, Virtual Brain Modeling, Medical Informatics. Egidio d’Angelo is core partner of CEN (Cerebellum and Emotional Networks), a Marie Skłodowska-Curie ITN that will explore the brain circuits that underlie emotional behavior (Horizon 2020 research and innovation programme- GA No 956414). Egidio d’Angelo published 234 peer reviewed papers (most as first or last author) including Nature, Science, Nature Neuroscience, Nature Communication, Nature Communications Biology, Cell, Neuron, TINS, J Neuroscience and presented his research at several meetings worldwide, often as invited speaker (recently UCL, CERN, Rimini, TEDex, CAETS). The main scientific interests are centered on the cellular and circuit functions of the cerebellum and its pathologies in the context of the whole-brain activity. Additional information can be found at https://dangelo.unipv.it/.
Abstract – Multiscale brain modelling for health and technology
Addressing the multiscale brain organization is fundamental not only to understand its inherent mechanisms of function but also to answer neuropathological questions and promote the development of new technologies for AI and health. While relevant advances have been made on the experimental front – encompassing genetics, molecular biology, cell physiology and brain imaging – recent developments in informatics and big data have opened a new scenario, in which multiscale computational models can be used to simulate brain functions and to foster a range of technological applications. Multiscale brain modelling is an emerging technological sector. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions, and behavior. More difficult is to infer neuronal functions from ensemble measurements like those currently obtained with MRI, EEG, MEG or PET. In this presentation, I will consider theories and strategies for combining bottom-up models, generated from principles of neuronal biophysics, with top-down models, based on ensemble representations of network activity and on functional principles. Modelling the relationship between microscopic phenomena and large-scale brain functions could allow to predict how a drug that binds specific receptors modifies local and distributed circuit activity or how genetic alterations of membrane ionic channels or receptors reverberate up to brain functions and dynamics. This, in turn, would allow to identify potential targets for pharmacological and physical therapy, e.g., through electrical or magnetic stimulation of specific circuits, or for precision surgery. Clearly, these applications open new perspectives toward personalized and precision medicine, for example generating brain digital twins. These can be intended as personalized copies of a subject’s brain that can be used to simulate specific functionalities anticipating the consequences of, e.g., neurorehabilitation or surgical intervention. Multiscale brain modeling has also breakthrough potential in information technologies and AI. Spiking neural networks can be transformed in hardware to generate neuromorphic computers and be embedded inside closed-loop controllers to generate new computational architectures and autonomous robots. In conclusion, multiscale brain modelling is not just fundamental to understand brain functioning but also to promote digital technologies for society and health in ways that remain to be worked out and exploited in full.