Neural network realization of sensorimotor space organization using predictability and decorrelation
Madhusudhana Rao, Daniel Weiller, Robert Märtin, Peter König · BMC Neuroscience · 2009
Different coding principles like stability have been successfully applied to passive sensory stimuli to capture sensory representation of neurons [ 1 ]. It has become obvious later that the agent's behavioral repertoire has a crucial impact on the formation of the sensory representation and thus highlights the importance of the sensorimotor space. A heuristic rule-based investigation [ 2 ] demonstrates that optimizing the predictability in sensorimotor space of foraging agent leads to the emergence of place fields. The present work implements this principle in a biologically plausible neural-network architecture.