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About

K. R. Gurney is a leading researcher in computational neuroscience and neurorobotics, whose work centers on understanding the neural mechanisms of action selection—how the brain resolves conflicts between competing motor programs. His major contributions include developing the first embodied computational model of the vertebrate basal ganglia, demonstrating how these subcortical nuclei function as a central action selection system. This foundational 2000 paper (40 citations) embedded a biologically plausible basal ganglia model within the control architecture of a Khepera robot, bridging neuroscience and robotics. Gurney has further advanced the field by implementing multi-layer leaky integrator networks on cellular processor arrays (2007), enabling complex neural network simulations on parallel hardware. His more recent work (2024) explores the critical role of dopamine modulation in basal ganglia function, simulating how altered dopamine levels affect action selection in neurorobotic models. Gurney also investigated instrumental conditioning driven by neutral stimuli (2008), challenging traditional reinforcement learning assumptions. His research has profound implications for understanding neurological disorders like Parkinson’s disease and for developing bio-inspired robotic control systems.