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Zhang F, Yang Y, Xin Y, Sun Y, Wang C, Zhu J, Tang T, Zhang J, Xu K. Efficacy of different strategies of responsive neurostimulation on seizure control and their association with acute neurophysiological effects in rats. Epilepsy Behav 2023; 143:109212. [PMID: 37172446 DOI: 10.1016/j.yebeh.2023.109212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 04/01/2023] [Indexed: 05/15/2023]
Abstract
Responsive neurostimulation (RNS) has shown promising but limited efficacy in the treatment of drug-resistant epilepsy. The clinical utility of RNS is hindered by the incomplete understanding of the mechanism behind its therapeutic effects. Thus, assessing the acute effects of responsive stimulation (AERS) based on intracranial EEG recordings in the temporal lobe epilepsy rat model may provide a better understanding of the potential therapeutic mechanisms underlying the antiepileptic effect of RNS. Furthermore, clarifying the correlation between AERS and seizure severity may help guide the optimization of RNS parameter settings. In this study, RNS with high (130 Hz) and low frequencies (5 Hz) was applied to the subiculum (SUB) and CA1. To quantify the changes induced by RNS, we calculated the AERS during synchronization by Granger causality and analyzed the band power ratio in the classic power band after different stimulations were delivered in the interictal and seizure onset periods, respectively. This demonstrates that only targets combined with an appropriate stimulation frequency could be efficient for seizure control. High-frequency stimulation of CA1 significantly shortened the ongoing seizure duration, which may be causally related to increased synchronization after stimulation. Both high-frequency stimulation of the CA1 and low-frequency stimulation delivered to the SUB reduced seizure frequency, and the reduced seizure risk may correlate with the change in power ratio near the theta band. It indicated that different stimulations may control seizures in diverse manners, perhaps with disparate mechanisms. More focus should be placed on understanding the correlation between seizure severity and synchronization and rhythm around theta bands to simplify the process of parameter optimization.
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Affiliation(s)
- Fang Zhang
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Yufang Yang
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Yanjie Xin
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Yuting Sun
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Chang Wang
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Junming Zhu
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, China; Department of Neurosurgery, Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang University, Zhejiang, China
| | - Tao Tang
- Zhejiang Lab, Hangzhou 311100, China
| | - Jianmin Zhang
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, China; Department of Neurosurgery, Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang University, Zhejiang, China
| | - Kedi Xu
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.
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Yang Y, Zhang F, Gao X, Feng L, Xu K. Progressive alterations in electrophysiological and epileptic network properties during the development of temporal lobe epilepsy in rats. Epilepsy Behav 2023; 141:109120. [PMID: 36868167 DOI: 10.1016/j.yebeh.2023.109120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 01/28/2023] [Accepted: 01/29/2023] [Indexed: 03/05/2023]
Abstract
OBJECTIVE Refractory temporal lobe epilepsy (TLE) with recurring seizures causing continuing pathological changes in neural reorganization. There is an incomplete understanding of how spatiotemporal electrophysiological characteristics changes during the development of TLE. Long-term multi-site epilepsy patients' data is hard to obtain. Thus, our study relied on animal models to reveal the changes in electrophysiological and epileptic network characteristics systematically. METHODS Long-term local field potentials (LFPs) were recorded over a period of 1 to 4 months from 6 pilocarpine-treated TLE rats. We compared variations of seizure onset zone (SOZ), seizure onset pattern (SOP), the latency of seizure onsets, and functional connectivity network from 10-channel LFPs between the early and late stages. Moreover, three machine learning classifiers trained by early-stage data were used to test seizure detection performance in the late stage. RESULTS Compared to the early stage, the earliest seizure onset was more frequently detected in hippocampus areas in the late stage. The latency of seizure onsets between electrodes became shorter. Low-voltage fast activity (LVFA) was the most common SOP and the proportion of it increased in the late stage. Different brain states were observed during seizures using Granger causality (GC). Moreover, seizure detection classifiers trained by early-stage data were less accurate when tested in late-stage data. SIGNIFICANCE Neuromodulation especially closed-loop deep brain stimulation (DBS) is effective in the treatment of refractory TLE. Although the frequency or amplitude of the stimulation is generally adjusted in existing closed-loop DBS devices in clinical usage, the adjustment rarely considers the pathological progression of chronic TLE. This suggests that an important factor affecting the therapeutic effect of neuromodulation may have been overlooked. The present study reveals time-varying electrophysiological and epileptic network properties in chronic TLE rats and indicates that classifiers of seizure detection and neuromodulation parameters might be designed to adapt to the current state dynamically with the progression of epilepsy.
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Affiliation(s)
- Yufang Yang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.
| | - Fang Zhang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.
| | - Xiang Gao
- Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China; Institute of Advanced Digital Technology and Instrument, Zhejiang University, Hangzhou, China.
| | | | - Kedi Xu
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, Hangzhou, China.
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A Feature Extraction Method for Seizure Detection Based on Multi-Site Synchronous Changes and Edge Detection Algorithm. Brain Sci 2022; 13:brainsci13010052. [PMID: 36672034 PMCID: PMC9856467 DOI: 10.3390/brainsci13010052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/10/2022] [Accepted: 12/12/2022] [Indexed: 12/29/2022] Open
Abstract
Automatic detection of epileptic seizures is important in epilepsy control and treatment, and specific feature extraction assists in accurate detection. We developed a feature extraction method for seizure detection based on multi-site synchronous changes and an edge detection algorithm. We investigated five chronic temporal lobe epilepsy rats with 8- and 12-channel detection sites in the hippocampus and limbic system. Multi-site synchronous changes were selected as a specific feature and implemented as a seizure detection method. For preprocessing, we used magnitude-squared coherence maps and Canny edge detection algorithm to find the frequency band with the most significant change in synchronization and the important channel pairs. In detection, we used the maximal cross-correlation coefficient as an indicator of synchronization and the correlation coefficient curves' average value and standard deviation as two detection features. The method achieved high performance, with an average 96.60% detection rate, 2.63/h false alarm rate, and 1.25 s detection delay. The experimental results show that synchronization is an appropriate feature for seizure detection. The magnitude-squared coherence map can assist in selecting a specific frequency band and channel pairs to enhance the detection result. We found that individuals have a specific frequency band that reflects the most significant synchronization changes, and our method can individually adjust parameters and has good detection performance.
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Kang W, Ju C, Joo J, Lee J, Shon YM, Park SM. Closed-loop direct control of seizure focus in a rodent model of temporal lobe epilepsy via localized electric fields applied sequentially. Nat Commun 2022; 13:7805. [PMID: 36528681 PMCID: PMC9759546 DOI: 10.1038/s41467-022-35540-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 12/09/2022] [Indexed: 12/23/2022] Open
Abstract
Direct electrical stimulation of the seizure focus can achieve the early termination of epileptic oscillations. However, direct intervention of the hippocampus, the most prevalent seizure focus in temporal lobe epilepsy is thought to be not practicable due to its large size and elongated shape. Here, in a rat model, we report a sequential narrow-field stimulation method for terminating seizures, while focusing stimulus energy at the spatially extensive hippocampal structure. The effects and regional specificity of this method were demonstrated via electrophysiological and biological responses. Our proposed modality demonstrates spatiotemporal preciseness and selectiveness for modulating the pathological target region which may have potential for further investigation as a therapeutic approach.
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Affiliation(s)
- Wonok Kang
- grid.49100.3c0000 0001 0742 4007School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea
| | - Chanyang Ju
- grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Convergence IT Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea
| | - Jaesoon Joo
- grid.264381.a0000 0001 2181 989XBiomedical Engineering Research Center, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, 06351 South Korea
| | - Jiho Lee
- grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Convergence IT Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea
| | - Young-Min Shon
- grid.264381.a0000 0001 2181 989XBiomedical Engineering Research Center, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, 06351 South Korea ,grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, School of Medicine, Sungkyunkwan University, Seoul, 06351 Republic of Korea
| | - Sung-Min Park
- grid.49100.3c0000 0001 0742 4007School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Medical Device Innovation Center, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Convergence IT Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Electrical Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.49100.3c0000 0001 0742 4007Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, 37673 Republic of Korea ,grid.15444.300000 0004 0470 5454Institute of Convergence Science, Yonsei University, Seoul, 03722 Republic of Korea
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Jiang L, Wu B, Wei X, Lv X, Xue H, Lu G, Zeng Y, Xing J, Wu W, Wu J. Flexible lead-free piezoelectric arrays for high-efficiency wireless ultrasonic energy transfer and communication. MATERIALS HORIZONS 2022; 9:2180-2190. [PMID: 35686946 DOI: 10.1039/d2mh00437b] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Implantable medical electronics (IMEs) are now becoming increasingly prevalent for diagnostic and therapeutic purposes. Despite extensive efforts, a primary challenge for IMEs is reliable wireless power and communication to provide well-controlled, therapeutically relevant effects. Ultrasonic energy transfer and communication (UETC) employing traveling ultrasound waves to transmit energy has emerged as a promising wireless strategy for IMEs. Nevertheless, conventional UETC systems are rigid, bulky, and based on toxic lead-based piezoelectric materials, raising efficiency and safety concerns. Here, we present a novel transcutaneous UETC system based on a two-dimensional flexible lead-free piezoelectric array (f-LFPA) that hybridizes high-performance (piezoelectric coefficient d33 ≈ 503 pC N-1) (K,Na)NbO3-based eco-friendly piezo-units with soft structural components. The newly developed lead-free piezo-unit exhibits submicron ferroelectric domains and superior energy harvesting figures of merit (d33g33 ≈ 20 000 × 10-15 m2 N-1), resulting in the prepared f-LFPA demonstrating a high output voltage of 22.4 V, a power density of 0.145 W cm-2, and a signal-to-noise ratio of more than 30 dB within the FDA safety limits, while maintaining the flexibility for wide-angle receiving. Further ex vivo experiment demonstrates the adequate power supply capabilities of the f-LFPA and its possible application in future implantable eco-friendly bioelectronics for diagnostics, therapy, and real-time monitoring.
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Affiliation(s)
- Laiming Jiang
- College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
| | - Bo Wu
- Sichuan Province Key Laboratory of Information Materials, Southwest Minzu University, Chengdu, 610041, P. R. China.
| | - Xiaowei Wei
- College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
| | - Xiang Lv
- College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
| | - Haoyue Xue
- College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
| | - Gengxi Lu
- Department of Biomedical Engineering Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Yushun Zeng
- Department of Biomedical Engineering Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Jie Xing
- College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
| | - Wenjuan Wu
- Sichuan Province Key Laboratory of Information Materials and Devices Application, Chengdu University of Information Technology, Chengdu 610225, P. R. China
| | - Jiagang Wu
- College of Materials Science and Engineering, Sichuan University, Chengdu 610064, China.
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Li Y, Xu S, Wang Y, Duan Y, Jia Q, Xie J, Yang X, Wang Y, Dai Y, Yang G, Yuan M, Wu X, Song Y, Wang M, Chen H, Wang Y, Cai X, Pei W. Wireless Closed-Loop Optical Regulation System for Seizure Detection and Suppression In Vivo. FRONTIERS IN NANOTECHNOLOGY 2022. [DOI: 10.3389/fnano.2022.829751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
There are approximately 50 million people with epilepsy worldwide, even about 25% of whom cannot be effectively controlled by drugs or surgical treatment. A wireless closed-loop system for epilepsy detection and suppression is proposed in this study. The system is composed of an implantable optrode, wireless recording, wireless energy supply, and a control module. The system can monitor brain electrical activity in real time. When seizures are recognized, the optrode will be turned on. The preset photosensitive caged compounds are activated to inhibit the seizure. When seizures are inhibited or end, the optrode is turned off. The method demonstrates a practical wireless closed-loop epilepsy therapy system.
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Wen Y, Zhang Y, Wen L, Cao H, Ai G, Gu M, Wang P, Chen H. A 65nm/0.448 mW EEG processor with parallel architecture SVM and lifting wavelet transform for high-performance and low-power epilepsy detection. Comput Biol Med 2022; 144:105366. [PMID: 35305503 DOI: 10.1016/j.compbiomed.2022.105366] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 02/25/2022] [Accepted: 02/28/2022] [Indexed: 11/30/2022]
Abstract
In recent years, low-power and wearable biomedical testing devices have emerged as a key answer to the challenges associated with epilepsy disorders, which are prone to crises and require prolonged monitoring. The feature vector of the electroencephalographic (EEG) signal was extracted using the lifting wavelet transform algorithm, and the hardware of the lifting wavelet transform module was optimized using the canonic signed digit (CSD) coding method. A low-power EEG feature extraction circuit with a power consumption of 0.42 mW was constructed. This article employs the support vector machine (SVM) technique after feature extraction to categorize and identify epilepsy. A parallel SVM processing unit was constructed to accelerate classification and identification, and then a high-speed, low-power EEG epilepsy detection processor was implemented. The processor design was completed using TSMC 65 nm technology. The chip size is 0.98 mm2, operating voltage is 1 V, operating frequency is 1 MHz, epilepsy detection latency is 0.91 s, power consumption is 0.448 mW, and energy efficiency of a single classification is 2.23 μJ/class. The CHB-MIT database test results show that this processor has a sensitivity of 91.86% and a false detection rate of 0.17/h. Compared to other processors, this processor is more suitable for portable/wearable devices.
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Affiliation(s)
- Yongzhong Wen
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China.
| | - Yuejun Zhang
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China.
| | - Liang Wen
- Department of Electronic Technology, China Coast Guard Academy, Ningbo, Zhejiang, 315801, China.
| | - Haojie Cao
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China.
| | - Guangpeng Ai
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China.
| | - Minghong Gu
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China.
| | - Pengjun Wang
- Electrical and Electronic Engineering, Wenzhou University, Wenzhou, 325035, China.
| | - Huiling Chen
- Department of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China.
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Rao VR. Chronic electroencephalography in epilepsy with a responsive neurostimulation device: current status and future prospects. Expert Rev Med Devices 2021; 18:1093-1105. [PMID: 34696676 DOI: 10.1080/17434440.2021.1994388] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Implanted neurostimulation devices are gaining traction as therapeutic options for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable chronic electroencephalography (cEEG), which offers views of the dynamics of brain activity in epilepsy over unprecedented time horizons. AREAS COVERED This review focuses on clinical insights and basic neuroscience discoveries enabled by analyses of cEEG from an exemplar device, the NeuroPace RNS® System. Applications of RNS cEEG covered here include counting and lateralizing seizures, quantifying medication response, characterizing spells, forecasting seizures, and exploring mechanisms of cognition. Limitations of the RNS System are discussed in the context of next-generation devices in development. EXPERT OPINION The wide temporal lens of cEEG helps capture the dynamism of epilepsy, revealing phenomena that cannot be appreciated with short duration recordings. The RNS System is a vanguard device whose diagnostic utility rivals its therapeutic benefits, but emerging minimally invasive devices, including those with subscalp recording electrodes, promise to be more applicable within a broad population of people with epilepsy. Epileptology is on the precipice of a paradigm shift in which cEEG is a standard part of diagnostic evaluations and clinical management is predicated on quantitative observations integrated over long timescales.
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Affiliation(s)
- Vikram R Rao
- Associate Professor of Clinical Neurology, Chief, Epilepsy Division, Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
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Zhang F, Yang Y, Zheng Y, Zhu J, Wang P, Xu K. Combination of Matching Responsive Stimulations of Hippocampus and Subiculum for Effective Seizure Suppression in Temporal Lobe Epilepsy. Front Neurol 2021; 12:638795. [PMID: 34512497 PMCID: PMC8426572 DOI: 10.3389/fneur.2021.638795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 06/22/2021] [Indexed: 11/13/2022] Open
Abstract
Responsive neural stimulation (RNS) is considered a promising neural modulation therapy for refractory epilepsy. Combined stimulation on different targets may hold great promise for improving the efficacy of seizure control since neural activity changed dynamically within associated brain targets in the epileptic network. Three major issues need to be further explored to achieve better efficacy of combined stimulation: (1) which nodes within the epileptogenic network should be chosen as stimulation targets? (2) What stimulus frequency should be delivered to different targets? and (3) Could the efficacy of RNS for seizure control be optimized by combined different stimulation targets together? In our current study, Granger causality (GC) method was applied to analyze epileptogenic networks for finding key targets of RNS. Single target stimulation (100 μA amplitude, 300 μs pulse width, 5s duration, biphasic, charge-balanced) with high frequency (130 Hz, HFS) or low frequency (5 Hz, LFS) was firstly delivered by our lab designed RNS systems to CA3, CA1, subiculum (SUB) of hippocampi, and anterior nucleus of thalamus (ANT). The efficacy of combined stimulation with different groups of frequencies was finally assessed to find out better combined key targets with optimal stimulus frequency. Our results showed that stimulation individually delivered to SUB and CA1 could shorten the average duration of seizures. Different stimulation frequencies impacted the efficacy of seizure control, as HFS delivered to CA1 and LFS delivered to SUB, respectively, were more effective for shortening the average duration of electrographic seizure in Sprague-Dawley rats (n = 3). Moreover, the synchronous stimulation of HFS in CA1 combined with LFS in SUB reduced the duration of discharge significantly in rats (n = 6). The combination of responsive stimulation at different targets may be an inspiration to optimize stimulation therapy for epilepsy.
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Affiliation(s)
- Fang Zhang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering Zhejiang University, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China
| | - Yufang Yang
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering Zhejiang University, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China
| | - Yongte Zheng
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering Zhejiang University, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China
| | - Junming Zhu
- Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China.,Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University, Hangzhou, China
| | - Ping Wang
- Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering Zhejiang University, Hangzhou, China
| | - Kedi Xu
- Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, China.,Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering Zhejiang University, Hangzhou, China.,Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China
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Hamavar R, Asl BM. Seizure onset detection based on detection of changes in brain activity quantified by evolutionary game theory model. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 199:105899. [PMID: 33360360 DOI: 10.1016/j.cmpb.2020.105899] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 12/01/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND OBJECTIVE Epilepsy is one of the most common diseases of the nervous system, affecting about 1% of the world's population. The unpredictable nature of the epilepsy seizures deprives the patients and those around them of living a normal life. Therefore, the development of new methods that can help these patients will increase the life quality of these people and can bring a lot of economic savings in the health sector. METHODS In this study, we introduced a new framework for seizure onset detection. Our framework provides a new modelling for brain activity using evolutionary game theory and Kalman filter. If the patterns in the electroencephalogram (EEG) signal violate the predicted patterns by the proposed model, using a novel detection algorithm that has been also introduced in this paper, it can be determined whether the observed violation is the result of the onset of an epileptic seizure or not. RESULTS The proposed approach was able to detect the onset of all the seizures in CHB-MIT dataset with an average delay of -0.8 s and a false alarm of 0.39 per hour. Also, our proposed approach is about 20 times faster compared to recent studies. CONCLUSIONS The experimental results of applying the proposed framework on the CHB-MIT dataset show that our framework not only performed well with respect to the sensitivity, delay, and false alarm metrics but also performed much better in terms of run time compared to recent studies. This appropriate run time, along with other suitable metrics, makes it possible to use this framework in many cases where processing power or energy is limited and to think about creating new and inexpensive solutions for the treatment and care of people diagnosed with epilepsy.
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Affiliation(s)
- Ramtin Hamavar
- Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
| | - Babak Mohammadzadeh Asl
- Department of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.
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Yang Y, Zhang F, Zhu J, Wang Y, Xu K. Time-variant Epileptic Brain Functional Connectivity of Focal and Generalized Seizure in Chronic Temporal Lobe Epilepsy Rat . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:2833-2836. [PMID: 33018596 DOI: 10.1109/embc44109.2020.9175924] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Seizure types and characteristics may vary with time in a patient with distinct mechanisms underlying the propagation of ictal activity. Similarly, we found that both focal and generalized seizures coexist in some pilocarpine-induced chronic temporal lobe epilepsy (TLE) rats. In different seizure patterns, mapping complex networks and analyzing epileptic characteristics involved in seizure propagation are likely to reflect seizure propagation mechanisms, and indicate the establishment of stimulation strategy for epilepsy treatment, especially on the selection of stimulation targets. In our study, we used Granger causality method to track the time-variant epileptic brain functional connectivity in focal and generalized seizures from multi-site local field potentials (LFPs). Results showed that these two major types of seizures had different propagation patterns during ictal period. When comparing them, generalized seizures involved in a network with more complex relationships and spread to more extensive brain regions than in local seizures at mid-ictal stage. Moreover, we observed that focal seizures had a focused causal hub with strong interactions, while generalized seizures had relative distributed causal hubs to drive the development of seizure during seizure-onset stage. These findings suggest that stimulation strategy might need to be adapted to different seizure types thus allowing for retuning abnormal epileptic brain network and obtaining better treatment effect on seizure suppression.
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