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RELATED STAFF
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DynamIC Seminars
(
Complete List
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Name
Title
Date
Time
Room
Amir Jafarian (UCL)
Duffing Neural Mass Models
Abstract:
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 sets
Abstract:
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)
TBA
Abstract:
Tuesday, 23 October 2018
14:00
Huxley 139
DynamIC Workshops and Mini-Courses
(
Complete List
)
Title
Date
Venue
Analysis Aspects of Dynamics
Wednesday, 16 May 2018 – Friday, 18 May 2018
Imperial College London
Meeting on Network Inference and Random Dynamics
Wednesday, 2 May 2018 – Thursday, 3 May 2018
UCL and Imperial College London
One Day of Network Dynamics
Friday, 9 February 2018
Imperial College London
Short-term DynamIC Visitors
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