Designing closed-loop brain-machine interfaces with network of spiking neurons using MPC strategy

Hongguang Pan, Baocang Ding, Weimin Zhong, Gautam Kumar, Mayuresh V. Kothare

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Brain-machine interfaces (BMIs) are human-machine integration systems that provide an interface between the brain and a machine to sense cortical neuronal activity for the purpose of restoring impaired motor tasks. In our previous work [1], an optimal design of BMIs based on artificial sensory feedback was developed using model predictive control which relied on neuronal activity in the form of spiking. From a real implementation perspective, a more generalized framework that utilizes spiking is proposed in this paper. Specifically, a charge-balanced intra-cortical micro-stimulation (ICMS) current and a network of spiking neurons are adopted to compensate the lost feedback information. Next, an artificial sensory feedback framework using the network of spiking neurons is designed based on model predictive control (MPC) strategy, and an optimization problem is formulated according to this framework. Since the charge-balanced ICMS current is composed of several integer parameters, the optimization problem also includes some integer decision variables and is hard to be solved. In this paper, a heuristic population-based search algorithm called particle swarm optimization (PSO) algorithm is used to solve this optimization problem. Considering the updated particles may violate the input constraints, additional constraints are designed to guarantee that the decision variables can satisfy the input constraints. Finally, simulation results show the effectiveness of the designed closed-loop BMIs during recovery of natural performance.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2543-2548
Number of pages6
Volume2015-July
ISBN (Print)9781479986842
DOIs
StatePublished - Jul 28 2015
Externally publishedYes
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Other

Other2015 American Control Conference, ACC 2015
CountryUnited States
CityChicago
Period7/1/157/3/15

Fingerprint

Model predictive control
Neurons
Brain
Sensory feedback
Particle swarm optimization (PSO)
Feedback
Recovery

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Pan, H., Ding, B., Zhong, W., Kumar, G., & Kothare, M. V. (2015). Designing closed-loop brain-machine interfaces with network of spiking neurons using MPC strategy. In Proceedings of the American Control Conference (Vol. 2015-July, pp. 2543-2548). [7171117] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2015.7171117

Designing closed-loop brain-machine interfaces with network of spiking neurons using MPC strategy. / Pan, Hongguang; Ding, Baocang; Zhong, Weimin; Kumar, Gautam; Kothare, Mayuresh V.

Proceedings of the American Control Conference. Vol. 2015-July Institute of Electrical and Electronics Engineers Inc., 2015. p. 2543-2548 7171117.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pan, H, Ding, B, Zhong, W, Kumar, G & Kothare, MV 2015, Designing closed-loop brain-machine interfaces with network of spiking neurons using MPC strategy. in Proceedings of the American Control Conference. vol. 2015-July, 7171117, Institute of Electrical and Electronics Engineers Inc., pp. 2543-2548, 2015 American Control Conference, ACC 2015, Chicago, United States, 7/1/15. https://doi.org/10.1109/ACC.2015.7171117
Pan H, Ding B, Zhong W, Kumar G, Kothare MV. Designing closed-loop brain-machine interfaces with network of spiking neurons using MPC strategy. In Proceedings of the American Control Conference. Vol. 2015-July. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2543-2548. 7171117 https://doi.org/10.1109/ACC.2015.7171117
Pan, Hongguang ; Ding, Baocang ; Zhong, Weimin ; Kumar, Gautam ; Kothare, Mayuresh V. / Designing closed-loop brain-machine interfaces with network of spiking neurons using MPC strategy. Proceedings of the American Control Conference. Vol. 2015-July Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2543-2548
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