A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology
Targeted stimulation of nervous system has become an increasingly important research tool as well as therapeutic modality, and the stimulation signal acquisition based on the expected signal needs a closed-loop system. Due to the difficulty of biological experiments, the real-time simulation of neur...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9709268/ |
| _version_ | 1827927115306106880 |
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| author | Weitong Liu Siyuan Chang Jiang Wang Chen Liu |
| author_facet | Weitong Liu Siyuan Chang Jiang Wang Chen Liu |
| author_sort | Weitong Liu |
| collection | DOAJ |
| description | Targeted stimulation of nervous system has become an increasingly important research tool as well as therapeutic modality, and the stimulation signal acquisition based on the expected signal needs a closed-loop system. Due to the difficulty of biological experiments, the real-time simulation of neural activity is of great significance for the mechanism analysis and the performance improvement of neuromodulation techniques. This paper proposes a real-time hardware experimental platform for closed-loop electrophysiology. The platform integrates a neural computing module and a real-time control module on TMS320F28377D digital signal processors (DSP), and it reserves a programmable interface for users to call the required modules and set module parameters simultaneously. The platform has high compatibility and can be used for closed-loop electrophysiological experiments with different models, different control algorithms and different clamps. We implement the thalamocortical relay neural computing model and iteration improves proportional-integral algorithm on the platform for experimental verification in this paper. The neuron firing waveforms of the DSP platform and the MATLAB R2020b simulation waveforms are consistent. Under the same physiological time, the simulation speed of DSP platform is 3 times faster than that of the Intel Core i5-8400 CPU computer, and the neural firing rate of DSP platform is due to the real-time. This platform can be used as a tool to explore the working mechanism of the nervous system. It may promote the development of neuroscience, especially the field of closed-loop neuroscience. |
| first_indexed | 2024-03-13T05:47:15Z |
| format | Article |
| id | doaj.art-cf9f1004c6d045c68f99d65d4ed61833 |
| institution | Directory Open Access Journal |
| issn | 1558-0210 |
| language | English |
| last_indexed | 2024-03-13T05:47:15Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj.art-cf9f1004c6d045c68f99d65d4ed618332023-06-13T20:08:06ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1558-02102022-01-013038038910.1109/TNSRE.2022.31503259709268A Real-Time Hardware Experiment Platform for Closed-Loop ElectrophysiologyWeitong Liu0Siyuan Chang1https://orcid.org/0000-0002-7684-6083Jiang Wang2https://orcid.org/0000-0002-2189-8003Chen Liu3https://orcid.org/0000-0003-1635-3479School of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaSchool of Electrical and Information Engineering, Tianjin University, Tianjin, ChinaTargeted stimulation of nervous system has become an increasingly important research tool as well as therapeutic modality, and the stimulation signal acquisition based on the expected signal needs a closed-loop system. Due to the difficulty of biological experiments, the real-time simulation of neural activity is of great significance for the mechanism analysis and the performance improvement of neuromodulation techniques. This paper proposes a real-time hardware experimental platform for closed-loop electrophysiology. The platform integrates a neural computing module and a real-time control module on TMS320F28377D digital signal processors (DSP), and it reserves a programmable interface for users to call the required modules and set module parameters simultaneously. The platform has high compatibility and can be used for closed-loop electrophysiological experiments with different models, different control algorithms and different clamps. We implement the thalamocortical relay neural computing model and iteration improves proportional-integral algorithm on the platform for experimental verification in this paper. The neuron firing waveforms of the DSP platform and the MATLAB R2020b simulation waveforms are consistent. Under the same physiological time, the simulation speed of DSP platform is 3 times faster than that of the Intel Core i5-8400 CPU computer, and the neural firing rate of DSP platform is due to the real-time. This platform can be used as a tool to explore the working mechanism of the nervous system. It may promote the development of neuroscience, especially the field of closed-loop neuroscience.https://ieeexplore.ieee.org/document/9709268/Hardware experimental platformclosed-loop electrophysiologyneural computing modelthalamocortical relay neuraliterative learning control |
| spellingShingle | Weitong Liu Siyuan Chang Jiang Wang Chen Liu A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology IEEE Transactions on Neural Systems and Rehabilitation Engineering Hardware experimental platform closed-loop electrophysiology neural computing model thalamocortical relay neural iterative learning control |
| title | A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology |
| title_full | A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology |
| title_fullStr | A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology |
| title_full_unstemmed | A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology |
| title_short | A Real-Time Hardware Experiment Platform for Closed-Loop Electrophysiology |
| title_sort | real time hardware experiment platform for closed loop electrophysiology |
| topic | Hardware experimental platform closed-loop electrophysiology neural computing model thalamocortical relay neural iterative learning control |
| url | https://ieeexplore.ieee.org/document/9709268/ |
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