TY - GEN
T1 - Optimal feedback control framework suggests that changes in the preferred direction during BMI experiments may occur even with no adaptation
AU - Benyamini, Miri
AU - Zacksenhouse, Miriam
N1 - Publisher Copyright: © 2016 IEEE.
PY - 2017/2/6
Y1 - 2017/2/6
N2 - Brain Machine Interfaces (BMIs) rely on the correlation between neural activity and movement kinematics. However, many characteristics of the neural activity change after switching from pole control to brain control. Of particular interest are changes in the preferred direction (PD), and whether they reflect adaptation to the BMI filter. Here we investigate changes in the PD of simulated neurons that encode signals that are relevant for state estimation and control with the framework of optimal feedback control (OFC). Simulated BMI experiments based on the OFC framework demonstrate that changes in the PD may occur even with no adaptation. Further theoretical and simulations indicate the conditions under which there is no change in the PD upon switching to brain control Insights gained from this research can be used to improve the design of BMI filter - not only to minimize reconstruction error during pole control, but also to endow the neurons with desired PDs in brain control.
AB - Brain Machine Interfaces (BMIs) rely on the correlation between neural activity and movement kinematics. However, many characteristics of the neural activity change after switching from pole control to brain control. Of particular interest are changes in the preferred direction (PD), and whether they reflect adaptation to the BMI filter. Here we investigate changes in the PD of simulated neurons that encode signals that are relevant for state estimation and control with the framework of optimal feedback control (OFC). Simulated BMI experiments based on the OFC framework demonstrate that changes in the PD may occur even with no adaptation. Further theoretical and simulations indicate the conditions under which there is no change in the PD upon switching to brain control Insights gained from this research can be used to improve the design of BMI filter - not only to minimize reconstruction error during pole control, but also to endow the neurons with desired PDs in brain control.
KW - Brain-machine interfaces
KW - Computational motor control
KW - Neural modulations
KW - Optimal feedback control
UR - http://www.scopus.com/inward/record.url?scp=85015783673&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/SMC.2016.7844839
DO - https://doi.org/10.1109/SMC.2016.7844839
M3 - منشور من مؤتمر
T3 - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
SP - 3876
EP - 3881
BT - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016 - Conference Proceedings
T2 - 2016 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2016
Y2 - 9 October 2016 through 12 October 2016
ER -