Neural networks and Machine Learning By Marius Yamakou, FAU DCN-AvH, Friedrich-Alexander-Universität Erlangen-Nürnberg Neural Networks with time delayed connections Neurons communicate with each other through electrical signals. It is well known that these signals are oscillatory and that the properties of the oscillations depend on the characteristics of the individual neurons, […]
Math Marius Yamakou
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Stochastic Synchronization of Chaotic Neurons By Marius Yamakou, FAU DCN-AvH, Friedrich-Alexander-Universität Erlangen-Nürnberg Real biological neurons can show chaotic dynamics when excited by the certain external input current. The behavior of these neurons is characterized by instability and, as a result, limited predictability in time. Mathematically, a system is chaotic […]
Stochastic Neural Dynamics By Marius Yamakou, FAU DCN-AvH, Friedrich-Alexander-Universität Erlangen-Nürnberg Neural activity shows fluctuations and unpredictable transitions in its dynamics. This randomness can be an integral aspect of neuronal function; examples range from discrete fluctuations of ion channels to sudden sleep stage transitions involving the entire brain. To understand brain […]