Now showing 1 - 3 of 3
ItemA circle criterion observer for estimating the unmeasured membrane potential of neuronal populationsChong, M ; Postoyan, R ; Nešić, D ; Kuhlmann, L ; Varsavsky, A (IEEE, 2011-12-01)A circle criterion observer is designed for estimating the unmeasured membrane potential of neuronal populations using the electroencephalogram (EEG) from a class of parameterised models that replicates patterns seen on the EEG. Compared to existing similar designs, we provide a less conservative linear matrix inequality (LMI) condition that is shown to be fulfilled for the neural models we consider. The designed observer is robust towards disturbances in the input and measurement, as well as model uncertainty. We show that the observer can be designed for a model that reproduces alpha rhythms in the EEG as an illustrative example.
ItemParameter and state estimation for a class of neural mass modelsPostoyan, R ; Chong, M ; Nesic, D ; Kuhlmann, L (IEEE, 2012-01-01)We present an adaptive observer which asymptotically reconstructs the parameters and states of a model of interconnected cortical columns. Our study is motivated by the fact that the considered model is able to realistically reproduce patterns seen on (intracranial) electroencephalograms (EEG) by varying its parameters. Therefore, by estimating its parameters and states, we could gain a better understanding of the mechanisms underlying neurological phenomena such as seizures, which might lead to the prediction of the onsets of epileptic seizures. Simulations are performed to illustrate our results.
ItemA nonlinear estimator for the activity of neuronal populations in the hippocampusChong, M ; Postoyan, R ; Nešić, D ; Kuhlmann, L ; Varsavsky, A (IFAC - International Federation of Automatic Control, 2011-01-01)We present an estimator design to reconstruct the mean membrane potential of individual neuronal populations from a single channel simulated electroencephalographic signal based on a model of the hippocampus. The robustness of the estimator against variations in the synaptic gains of the neuronal populations and disturbances in the input and measurement is studied. Our results are further illustrated in simulations.