1. Connecting Brains with Machines The Neural Control of 2D Cursor Movement http://www.cs.uml.edu/~hgoodell M. J. Black, E. Bienenstock, J.P. Donoghue, M. Serruya, Wei Wu; Yun Gao, Proceedings of the First International IEEE EMBS Conference on Neural Engineering, pp. 610-613, Mar. 2003. http://donoghue.neuro.brown.edu/pubs/capri%20IEEE%20review.pdf

2. Neural Control of 2D Movement

3. Firing rate vs. velocity Firing rate roughly relative to speed Rough cosine dependence to preferred angle of motion Zc = h3 + hx vx + hy vy

4. Firing rate vs. velocity Measured Speed vs. DirectionBest Linear Model

5. Firing rate vs. position At a slower time scale (1.4 second vs. 70 ms for position), firing rate is also proportional to position.

6. Firing rate vs. position Measured positionBest Linear Model

7. General Linear Model Zk = Hxk + qk Z = vector of firing rates of sampled cells xk = x6 matrix (x,y position, velocity, accel) H = matrix of coefficients relating each cell’s firing rate to these 6 properties. Kalman filter trained with 3.5 minutes of data

8. Model performance (Kalman filter)