Abstract

Objective. We propose a closed-loop transcranial ultrasound stimulation (TUS) with a fuzzy controller to realize real-time and precise control of the motor response and neural activity of mice. Approach. The mean absolute value (MAV) of the electromyogram (EMG) and peak value (PV) of the local field potential (LFP) were measured under different ultrasound intensities. A model comprising the characteristics of the MAV of the EMG, PV of the LFP, and ultrasound intensity was built using a neural network, and a fuzzy controller, proportional-integral-derivative (PID) controller, and immune feedback controller were proposed to adjust the ultrasound intensity using the feedback of the EMG MAV and the LFP PV. Main results. In simulation, the quantitative calculation indicated that the maximum relative errors between the simulated EMG MAV and the expected values were 17% (fuzzy controller), 110% (PID control), 66% (immune feedback control); furthermore, the corresponding values of the LFP PV were 12% (fuzzy controller), 53% (PID control), 55% (immune feedback control). The average relative errors of fuzzy controller, PID control, immune feedback control were 4.97%, 13.15%, 11.52%, in the EMG closed-loop experiment and 7.76%, 11.84%, 13.56%, in the LFP closed-loop experiment. Significance. The simulation and experimental results demonstrate that the closed-loop TUS with a fuzzy controller can realize the tracking control of the motor response and neural activity of mice.

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