Closed-loop control of neural spike rate of cultured neurons using a thermoplasmonics-based photothermal neural stimulation

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Objective. Photothermal neural stimulation has been developed in a variety of interfaces as an alternative technology that can perturb neural activity. The demonstrations of these techniques have heavily relied on open-loop stimulation or complete suppression of neural activity. To extend the controllability of photothermal neural stimulation, combining it with a closed-loop system is required. In this work, we investigated whether photothermal suppression mechanism can be used in a closed-loop system to reliably modulate neural spike rate to non-zero setpoints. Approach. To incorporate the photothermal inhibition mechanism into the neural feedback system, we combined a thermoplasmonic stimulation platform based on gold nanorods (GNRs) and near-infrared illuminations (808 nm, spot size: 2 mm or 200 mu m in diameter) with a proportional-integral (PI) controller. The closed-loop feedback control system was implemented to track predetermined target spike rates of hippocampal neuronal networks cultured on GNR-coated microelectrode arrays. Main results. The closed-loop system for neural spike rate control was successfully implemented using a PI controller and the thermoplasmonic neural suppression platform. Compared to the open-loop control, the target-channel spike rates were precisely modulated to remain constant or change in a sinusoidal form in the range below baseline spike rates. The spike rate response behaviors were affected by the choice of the controller gain. We also demonstrated that the functional connectivity of a synchronized bursting network could be altered by controlling the spike rate of one of the participating channels. Significance. The thermoplasmonic feedback controller proved that it can precisely modulate neural spike rate of neural activity in vitro. This technology can be used for studying neuronal network dynamics and might provide insights in developing new neuromodulation techniques in clinical applications.
Publisher
IOP PUBLISHING LTD
Issue Date
2021-11
Language
English
Article Type
Article
Citation

JOURNAL OF NEURAL ENGINEERING, v.18, no.6, pp.066002

ISSN
1741-2560
DOI
10.1088/1741-2552/ac3265
URI
http://hdl.handle.net/10203/289508
Appears in Collection
BiS-Journal Papers(저널논문)
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