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Connecting Brains with Machines

Connecting Brains with Machines. The Neural Control of 2D Cursor Movement http://www.cs.uml.edu/~hgoodell.

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Connecting Brains with Machines

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  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. Direction Best 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 position Best 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)

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