Bimodal brain-machine interface for motor control of robotic prosthetic

We are working on mapping multi-channel neural spike data, recorded from multiple cortical areas of an owl monkey, to corresponding 3D monkey arm positions. In earlier work on this mapping task, we observed that continuous function approximators (such as artificial neural networks) have difficulty in jointly estimating 3D arm positions for two distinct cases-namely, when the monkey's arm is stationary and when it is moving. Therefore, we propose a multiple-model approach that first classifies neural spike data into two classes, corresponding to two states of the monkey's arm: (1) stationary and (2) moving. Then, the output of this classifier is used as a gating mechanism for subsequent continuous models, with one model per class. In this paper, we first motivate and discuss our approach. Next, we present encouraging results for the classifier stage, based on hidden Markov models (HMMs), and also for the entire bimodal mapping system. Finally, we conclude with a discussion of the results and suggest future avenues of research.

[1]  Biing-Hwang Juang,et al.  Hidden Markov Models for Speech Recognition , 1991 .

[2]  A. Georgopoulos,et al.  One motor cortex, two different views , 2000, Nature Neuroscience.

[3]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[4]  Christopher R. Stambaugh,et al.  Simultaneous encoding of tactile information by three primate cortical areas , 1998, Nature Neuroscience.

[5]  Deniz Erdogmus,et al.  Input-output mapping performance of linear and nonlinear models for estimating hand trajectories from cortical neuronal firing patterns , 2002, Proceedings of the 12th IEEE Workshop on Neural Networks for Signal Processing.

[6]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[7]  A. Schwartz,et al.  One motor cortex, two different views , 2000, Nature Neuroscience.

[8]  Jerald D. Kralik,et al.  Real-time prediction of hand trajectory by ensembles of cortical neurons in primates , 2000, Nature.

[9]  Yangsheng Xu,et al.  Human action learning via hidden Markov model , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[10]  Deniz Erdogmus,et al.  Modeling the relation from motor cortical neuronal firing to hand movements using competitive linear filters and a MLP , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[11]  Emanuel Todorov,et al.  On the role of primary motor cortex in arm movement control , 2003 .

[12]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[13]  Yangsheng Xu,et al.  Learning and validation of human control strategies , 1998 .