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Giulia Carigi
Andrew Clarke
Federico Graceffa
Michael Hartl
Giuseppe Malavolta
Guillermo Olicón Méndez
Cezary Olszowiec
Christian Pangerl
Mohammad Pedramfar
Kalle Timperi
Shangzhi Li
Ole Peters
Camille Poignard
Cristina Sargent
Bill Speares
Kevin Webster
Mauricio Barahona
Davoud Cheraghi
Martin Hairer
Darryl Holm
Xue-Mei Li
Greg Pavliotis

DynamIC Seminars (Complete List)

Name Title Date Time Room
Amir Jafarian (UCL)Duffing Neural Mass ModelsAbstract: In this talk, a mesoscopic model of a cortical column, known as a Duffing Neural Mass Model (DNMM), is developed to emulate stochastic mechanisms of initiation and termination of seizures in intracranial electroencephalogram (iEEG) recordings. The DNMM is constructed by applying perturbations to linear models of synaptic transmission in the Jansen and Rit [1] neural mass model. Random input (noise) can cause switches between normal activity and pathological activity similar to seizures in the DNMM. A bifurcation analysis and simulations are presented to provide insights into the behaviour of the model and to motivate questions for discussion. To replicate the pathological dynamics of ion currents, the model is extended to a slow-fast DNMM by considering a slow dynamics model (relative to the membrane potentials and firing rates) for some internal model parameters. The slow-fast DNMM can replicate initiation and termination of seizures that are caused by both random input fluctuations and pathological dynamics. Model comparison and the most likely to capture the underlying dynamics of recorded iEEG is sought through measuring a likelihood function estimated using a continuous-discrete unscented Kalman filter. Reference: [1]. B. Jansen and V. Rit. Electroencephalogram and visual evoked potential generation in a mathematical model of coupled cortical columns. Biological Cybernetics, 73:357-366, 1995. ISSN 0340-1200. Tuesday, 26 June 2018 12:00 Huxley 140
Janosch Rieger (Monash University)A Galerkin-type approach to shape optimisation in the space of convex setsAbstract: In this talk, I will discuss spaces of polytopes with fixed outer normals and their use in theoretical and practical shape optimization. These spaces possess a natural system of coordinates, and all admissible coordinates can be characterized by a linear inequality, which is handy both from an analytical as well as from a computational perspective. The polytope spaces approximate the space of all nonempty convex and compact subsets in Hausdorff distance uniformly on every bounded set, so they behave like classical Galerkin approximations to function spaces. I will show that for simple shape optimization problems, the set of global minimizers of auxiliary problems posed in the polytope spaces converges to the set of global minimizers of the original problem. Tuesday, 10 July 2018 14:00 Huxley 139
Mike Todd (St Andrews)TBAAbstract: Tuesday, 23 October 2018 14:00 Huxley 139

DynamIC Workshops and Mini-Courses (Complete List)

Title Date Venue
Analysis Aspects of DynamicsWednesday, 16 May 2018 – Friday, 18 May 2018Imperial College London
Meeting on Network Inference and Random DynamicsWednesday, 2 May 2018 – Thursday, 3 May 2018UCL and Imperial College London
One Day of Network DynamicsFriday, 9 February 2018Imperial College London

Short-term DynamIC Visitors (Complete List)

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