Title: Modelling of monkey's motor cortical signals by an extended adaptive Liquid State Machine: an integrated procedure from model, identification, experiments, data fitting, to validation
Authors: Jiangshuai Huang; Yongji Wang; Quanmin Zhu; Jiping He
Addresses: Department of Control Science and Engineering, Key Lab for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan 430074, China. ' Department of Control Science and Engineering, Key Lab for Image Processing and Intelligent Control, Huazhong University of Science and Technology, Wuhan 430074, China. ' Bristol Institute of Technology, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK. ' Department of Biomedical Engineering, Arizona State University, Tempe, Arizona, USA
Abstract: 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.
Keywords: adaptive LSM; liquid state machine; motor cortical signals; modelling; motor cortex; monkey cortex; multilayer neural networks; supervised learning; brain-machine interface; arm movement; arm flexion; arm extension; movement stance; moving direction; arm trajectory.
International Journal of Systems, Control and Communications, 2011 Vol.3 No.3, pp.287 - 301
Published online: 11 Sep 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article