| Movement generation with circuits of spiking neurons (2005) | |||||||||||||||
Abstract | |||||||||||||||
| How can complex movements that take hundreds of milliseconds be gen-erated by stereotypical neural microcircuits consisting of spiking neurons with a much faster dynamics? We show that linear readouts from generic neural microcircuit models can be trained to generate basic arm movements. Such movement generation is independent of the arm-model used and the type of feedbacks that the circuit receives. We demonstrate this by consider-ing two different models of a two-jointed arm, a standard model from robotics and a standard model from biology, that each generate different kinds of feed-back. Feedbacks that arrive with biologically realistic delays of 50–280 ms turn out to give rise to the best performance. If a feedback with such desir-able delay is not available, the neural microcircuit model also achieves good performance if it uses internally generated estimates of such feedback. Ex-isting methods for movement generation in robotics that take the particular dynamics of sensors and actuators into account (“embodiment of motor sys-tems”) are taken one step further with this approach, which provides methods for also using the “embodiment of motion generation circuitry”, i.e., the in-herent dynamics and spatial structure of neural circuits, for the generation of movements. 1 1 | |||||||||||||||
Publication details | |||||||||||||||
| |||||||||||||||