Approaches for Neural Dynamics

Neural dynamics is the study of the nervous system's remarkable capacity to change, and, at a systems level, the dynamic interplay between integration and segregation of brain regions enables all aspects of behaviour, including learning, memory, homeostasis and sensorimotor control. Real-time collision-free path planning and tracking control of a nonholonomic mobile robot in a dynamic environment is investigated using a neural dynamics based approach. The real-time robot path is generated through a dynamic neural activity landscape of a topologically organized neural network that represents the changing environment. The dynamics of each neuron is characterized by an additive neural dynamics model. The effectiveness and efficiency of this approach are demonstrated through simulation studies. A new approach for manipulating neural dynamics by using combined TMS and EEG recordings. Using the manipulative approach we can investigate (1) state-dependency in frequency-specific network connectivity by analyzing how TMS-evoked phase reset of on-going activity propagates from one cortical area to the rest of the brain in humans and (2) causal links between the neural dynamics and brain functions

 

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