Synchronization of a network of chaotic neurons using adaptive control in noisy environments

The synchronization of chaotic systems have received an increasing interest in the last few years. In an attempt to understand some of the possible me chanisms of synchronization of neurons in a noisy environment, the present study extends a control method which is based on the Kalman filter. This ad aptive control mechanism is able to modulate the frequency and the clusteri ng behavior of a network of neurons and can thus make the network switch dy namically to different rhythmic activity, leading to different coding possi bility.