Neural and cognitive modeling with networks of leaky integrator units
نویسندگان
چکیده
After reviewing several physiological findings on oscillations in the electroencephalogram (EEG) and their possible explanations by dynamical modeling, we present neural networks consisting of leaky integrator units as an universal paradigm for neural and cognitive modeling. In contrast to standard recurrent neural networks, leaky integrator units are described by ordinary differential equations living in continuous time. We present an algorithm to train the temporal behavior of leaky integrator networks by generalized backpropagation and discuss their physiological relevance. Eventually, we show how leaky integrator units can be used to build oscillators which may serve as models of brain oscillations and cognitive processing.
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