title: A proof-of-principle simulation for closed-loop control based on preexisting experimental thalamic DBS-enhanced instrumental learning.
abstract: Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption. However, when the association between the biomarkers of the model and stimulation is unclear, it is difficult to develop an optimal control scheme for other DBS applications, i.e., DBS-enhanced instrumental learning. Furthermore, few studies have investigated the effect of closed-loop DBS control for cognition function, such as instrumental skill learning, and have been implemented in simulation environments. In this paper, we proposed a proof-of-principle design for a closed-loop DBS system, cognitive-enhancing DBS (ceDBS), which enhanced skill learning based on in vivo experimental data. The ceDBS acquired local field potential (LFP) signal from the thalamic central lateral (CL) nuclei of animals through a neural signal processing system. A strong coupling of the theta oscillation (4-7 Hz) and the learning period was found in the water reward-related lever-pressing learning task. Therefore, the theta-band power ratio, which was the averaged theta band to averaged total band (1-55 Hz) power ratio, could be used as a physiological marker for enhancement of instrumental skill learning. The on-line extraction of the theta-band power ratio was implemented on a field-programmable gate array (FPGA). An autoregressive with exogenous inputs (ARX)-based predictor was designed to construct a CL-thalamic DBS model and forecast the future physiological marker according to the past physiological marker and applied DBS. The prediction could further assist the design of a closed-loop DBS controller. A DBS controller based on a fuzzy expert system was devised to automatically control DBS according to the predicted physiological marker via a set of rules. The simulated experimental results demonstrate that the ceDBS based on the closed-loop control architecture not only reduced power consumption using the predictive physiological marker, but also achieved a desired level of physiological marker through the DBS controller.
authors.affiliation: Department of Biomedical Engineering, National Yang Ming University, No.155, Sec.2, Linong St., Taipei 112, Taiwan, ROC.
authors.forename: Ching-Fu
authors.initials: CF
authors.lastname: Wang
authors.affiliation: Department of Mechanical and Computer Aided Engineering, Feng Chia University, No. 100, Wenhwa Rd., Taichung 407, Taiwan, ROC. Electronic address: shyang@fcu.edu.tw.
authors.forename: Shih-Hung
authors.initials: SH
authors.lastname: Yang
authors.affiliation: Department of Neurology, Tzu Chi General Hospital, Tzu Chi University, No. 707, Sec. 3, Chung, Yang Rd., Hualien 970, Taiwan, ROC. Electronic address: shlin355@icloud.com.
authors.forename: Sheng-Huang
authors.initials: SH
authors.lastname: Lin
authors.affiliation: Department of Biomedical Engineering, National Yang Ming University, No.155, Sec.2, Linong St., Taipei 112, Taiwan, ROC.
authors.forename: Po-Chuan
authors.initials: PC
authors.lastname: Chen
authors.affiliation: The Ph.D. Program for Neural Regenerative Medicine, Taipei Medical University, No. 250 Wu-Hsing St., Taipei 110, Taiwan, ROC.
authors.forename: Yu-Chun
authors.initials: YC
authors.lastname: Lo
authors.affiliation: Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No.35 Keyan Rd., Zhunan, Miaoli County 350, Taiwan, ROC.
authors.forename: Han-Chi
authors.initials: HC
authors.lastname: Pan
authors.affiliation: Interdisciplinary Institute of Neuroscience and Technology (ZIINT), Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, No.268, Kaixuan Rd., Hangzhou, Zhejiang 310029, China.
authors.forename: Hsin-Yi
authors.initials: HY
authors.lastname: Lai
authors.affiliation: Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No.35 Keyan Rd., Zhunan, Miaoli County 350, Taiwan, ROC; Singapore Institute for Neurotechnology (SINAPSE), Centre for Life Sciences, National University of Singapore, No.28 Medical Drive, #05-COR, 117456, Singapore.
authors.forename: Lun-De
authors.initials: LD
authors.lastname: Liao
authors.affiliation: Department and Institute of Physiology, School of Medicine, National Yang Ming University, Taipei 112, Taiwan, ROC; Brain Research Center, National Yang Ming University, No.155, Sec.2, Linong St., Taipei 112, Taiwan, ROC.
authors.forename: Hui-Ching
authors.initials: HC
authors.lastname: Lin
authors.affiliation: Department of Biomedical Engineering, National Yang Ming University, No.155, Sec.2, Linong St., Taipei 112, Taiwan, ROC.
authors.forename: Hsu-Yan
authors.initials: HY
authors.lastname: Chen
authors.affiliation: Department of Materials Science and Engineering, Carnegie Mellon University, No.5000 Forbes Avenue, Wean Hall 3325, Pittsburgh, PA 15213, USA.
authors.forename: Wei-Chen
authors.initials: WC
authors.lastname: Huang
authors.affiliation: Department of Mechanical and Computer Aided Engineering, Feng Chia University, No. 100, Wenhwa Rd., Taichung 407, Taiwan, ROC.
authors.forename: Wun-Jhu
authors.initials: WJ
authors.lastname: Huang
authors.affiliation: Department of Biomedical Engineering, National Yang Ming University, No.155, Sec.2, Linong St., Taipei 112, Taiwan, ROC. Electronic address: irradiance@so-net.net.tw.
authors.forename: You-Yin
authors.initials: YY
authors.lastname: Chen
mesh_terms: D000818:Animals; D058256:Brain Waves; D003216:Conditioning, Operant; D046690:Deep Brain Stimulation / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D000075082:Proof of Concept Study; D051381:Rats; D017207:Rats, Sprague-Dawley; D013788:Thalamus / Q000502:physiology*
keywords: Autoregressive exogenous; Closed-loop system; Deep brain stimulation; Fuzzy expert system; Instrumental skill learning; Local field potential