Networks of spiking neurons: the third generation of neural network models
Transactions of the Society for Computer Simulation International - Special issue: simulation methodology in transportation systems
Movement prediction from real-world images using a liquid state machine
Applied Intelligence
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In this paper, the LSM model is upgraded to enable it to the modelling of motor cortical signals, in which liquid states are no longer the spikes but the analogue potentials sampled from the neurons in the circuit and the readout layer is the standard multi-layer neural network with supervised learning algorithm. The input signals are spikes distilled from the monkey's cortex and output are the move directions of the trajectories of its right wrist. The results of the modelling process shows this LSM can be set up a good model with acceptable precision for a wide range of applications.