Abstract:
The prevalence of wearable sensing devices and smartphones is resulting in a multitude of physiological data being collected, for example heart rate, gait and eye movement. Driven by applications in health and behavioural monitoring, as well as affective computing, there is a growing demand for computational models that are able to accurately predict multimodal features in a variety of contexts. While machine learning models excel at identifying features in physiological signals, they lack reliability guarantees and need to be adapted to the user. This talk will give an overview of modelling and personalisation techniques developed as part of the AffecTech project and their applications in the context of biometric security and emotion recognition. Future challenges in this important field will also be discussed.
Bio: Marta Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College, University of Oxford. Kwiatkowska has made fundamental contributions to the theory and practice of model checking for probabilistic systems, focusing on automated techniques for verification and synthesis from quantitative specifications. She led the development of the PRISM model checker, the leading software tool in the area and winner of the HVC Award 2016. Probabilistic model checking has been adopted in diverse fields, including distributed computing, wireless networks, security, robotics, healthcare, systems biology, DNA computing and nanotechnology, with genuine flaws found and corrected in real-world protocols. Kwiatkowska is the first female winner of the Royal Society Milner Award and was awarded an honorary doctorate from KTH Royal Institute of Technology in Stockholm in 2014. Her recent work was supported by the ERC Advanced Grant VERIWARE and the EPSRC Programme Grant on Mobile Autonomy. She is a Fellow of ACM and Member of Academia Europea.
Abstract:
Starting from the 20s, researchers have begun to explore the possibility to create ‘hybrid’ systems in vitro at the interface between neuroscience and robotics (I will call them ‘neurohybrid interfaces’), thus providing an excellent test bed for modulation of neuronal tissue and forming the basis of future adaptive, bi-directional Brain Machine Interfaces and neuroprostheses. The first-ever in vitro closed-loop neurohybrid system consisted of a lamprey brainstem bi-directionally connected to a small wheeled robot. Inspired by that and other pioneering studies, a bi-directional system involving in vitro neocortical networks grown on Micro Electrode Arrays (MEAs) and a small robot was developed and tested in my lab.
A similar technology could be exploited also for brain repair, with relevance in the field of cognitive neuroprosthetics. The idea is to use closed-loop neurohybrid interfaces to treat the neuronal injury in the brain, where the damage is actually located, and to possibly promote brain plasticity in order to speed up the recovery process. Within this framework, I will show two examples. I will start by presenting the development and the results related to an in vitro ‘brain-prosthesis’, aimed at restoring the communications between damaged neuronal networks. Then, I will present recent results related to closed-loop paradigms for brain repair in vivo, focusing on how different types of stimulation can affect the neural activity. Further developments and applications in the fields of neurorehabilitation and neurorobotics will be briefly introduced and discussed.
Bio: Michela Chiappalone graduated in Electronic Engineering (summa cum laude) in 1999 and obtained a PhD in Electronic Engineering and Computer Science from University of Genova (Italy) in 2003. In 2002 she has been visiting scholar at the Dept of Physiology, Northwestern University (Chicago, IL, USA), supervised by Prof F. A. Mussa-Ivaldi. After a Post Doc at the University of Genova, in 2007 she joined Neuroscience and Brain Technologies Dept at the Istituto Italiano di Tecnologia (IIT) as a Post Doc. In 2013 she got a group leader position (‘Researcher’) in the same Institution. In 2015 she has been visiting Professor at the KUMED (Kansas City, KS, USA), hosted by Prof. RJ Nudo. From 2012 to 2015 M. Chiappalone has been Coordinator of the FET Open European Project BrainBow, judged excellent. In 2014 she got the national scientific habilitation as Associate Professor of Bioengineering, while in 2018 he obtained the habilitation as Full Professor of Bioengineering. In 2017, M. Chiappalone joined the Rehab Technologies facility of IIT to lead a group aimed at interfacing robotic devices with the nervous system for applications in neuroprosthetics and neurorehabilitation.
Abstract:
Reaction network theories are tools for stability analysis of open reacting systems provided that stoichiometric (chemical) equations are given for each reaction step together with power law rate expressions. Based on stoichiometry alone, elementary subnetworks (known also as elementary modes or extreme currents) are identified and their capacity for displaying dynamical instabilities, such as bistability and oscillations, is evaluated by examining associated Jacobian matrix. This analysis is qualitative in the sense that only reaction orders are needed as input information, whereas rate coefficients may remain unspecified. In the next step, the subnetworks are combined to form the entire network and its stability is determined by stability of the constituting subnetworks. This combination principle can be conveniently used for kinetic parameter estimation of the unknown/unspecified rate coefficients by applying linear optimization to a set of constraint equations balancing linearly combined subnetworks with the corresponding rate expressions. Mathematically, this amounts to convex optimization.
From the application point of view, we wish to describe an experimentally measured biosystem in which chemical processes take place (such as enzyme control loops, metabolism, gene regulation, etc.) giving rise to experimentally observed change from a steady state to oscillatory or bistable dynamics. For such a system a reaction mechanism is assumed (or available from previous research) with only a limited set of known kinetic parameters, in addition to input/output parameters known from the experiment. Then the set of unknown kinetic parameters is estimated via linear optimization so that the dynamics displayed by the model coincides with the experimentally observed behavior (emergence of oscillations or bistable switch). Such an estimate may not yield the ultimate best fit, rather, it helps to locate a region in the parameter space, where the observed dynamics are reproduced by the model. This global approach is useful especially when the number of unknown parameters is large. Once a suitable parameter region is found, standard least-square methods or other more refined algorithms assuming a well chosen initial guess may be used to fine tune the parameters values.
In addition, reaction network theory is useful in identifying subnetworks that are responsible for destabilizing the steady state. In particular, such subnetworks provide prototypes of chemical oscillators, also called oscillatory motifs, which possess a characteristic network topology. Thus the search for dynamical instabilities in arbitrarily large networks, as is typical in biosystems, can be reduced to the search for motifs.
Bio: Igor Schreiber has a Ph.D in Chemical Engineering from the University of Chemistry and Technology (UTC) of Prague. From 1984 to 1989 he has been assistant professor at the UTC Prague. From 1989 to 1993 he has been a visiting scholar at the Chemistry Department of Stanford University, hosted by John Ross. From 1994 to 2005, he has been associate professor at UTC Prague. From 2007 to 2014 he has been head of the Department of Chemical Engineering at UTC Prague. Since 2005, he is Full Professor of Chemical Engineering at UCT Prague. His research interests include reaction kinetics and nonlinear dynamical systems, stability and bifurcation theory, mechanisms of oscillatory chemical and biochemical/enzyme reactions, reaction networks theory and its applications to biosystems. He has published 70 journal papers, 3 books, 200+ papers in conference proceedings. He is also a member of ACS, AICHE, EFCE, and the Czech Society for Chemical Engineering.