Neural Decoding of Cursor Motion Using a Kalman Filter

The direct neural control of external devices such as computer displays or prosthetic limbs requires the accurate decoding of neural activity representing continuous movement. We develop a real-time control system using the spiking activity of approximately 40 neurons recorded with an electrode array implanted in the arm area of primary motor cortex. In contrast to previous work, we develop a control-theoretic approach that explicitly models the motion of the hand and the probabilistic relationship between this motion and the mean firing rates of the cells in 70ms bins. We focus on a realistic cursor control task in which the subject must move a cursor to "hit" randomly placed targets on a computer monitor. Encoding and decoding of the neural data is achieved with a Kalman filter which has a number of advantages over previous linear filtering techniques. In particular, the Kalman filter reconstructions of hand trajectories in off-line experiments are more accurate than previously reported results and the model provides insights into the nature of the neural coding of movement.

[1]  Pamela Reinagel,et al.  Decoding visual information from a population of retinal ganglion cells. , 1997, Journal of neurophysiology.

[2]  R A Normann,et al.  The Utah intracortical Electrode Array: a recording structure for potential brain-computer interfaces. , 1997, Electroencephalography and clinical neurophysiology.

[3]  Michael J. Black,et al.  Inferring Hand Motion from Multi-Cell Recordings in Motor Cortex using a Kalman Filter , 2002 .

[4]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .

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

[6]  Michael J. Black,et al.  Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex , 2001, NIPS.

[7]  A. P. Georgopoulos,et al.  Neuronal population coding of movement direction. , 1986, Science.

[8]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[9]  B L McNaughton,et al.  Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells. , 1998, Journal of neurophysiology.

[10]  Dawn M. Taylor,et al.  Direct Cortical Control of 3D Neuroprosthetic Devices , 2002, Science.

[11]  Nicholas G. Hatsopoulos,et al.  Brain-machine interface: Instant neural control of a movement signal , 2002, Nature.

[12]  E N Brown,et al.  A Statistical Paradigm for Neural Spike Train Decoding Applied to Position Prediction from Ensemble Firing Patterns of Rat Hippocampal Place Cells , 1998, The Journal of Neuroscience.

[13]  A B Schwartz,et al.  Motor cortical representation of speed and direction during reaching. , 1999, Journal of neurophysiology.