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      Decreased Power but Preserved Bursting Features of Subthalamic Neuronal Signals in Advanced Parkinson's Patients under Controlled Desflurane Inhalation Anesthesia

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          Abstract

          Deep brain stimulation (DBS) surgery of the subthalamic nucleus (STN) under general anesthesia (GA) had been used in Parkinson's disease (PD) patients who are unable tolerate awake surgery. The effect of anesthetics on intraoperative microelectrode recording (MER) remains unclear. Understanding the effect of anesthetics on MER is important in performing STN DBS surgery with general anesthesia. In this study, we retrospectively performed qualitive and quantitative analysis of STN MER in PD patients received STN DBS with controlled desflurane anesthesia or LA and compared their clinical outcome. From January 2005 to March 2006, 19 consecutive PD patients received bilateral STN DBS surgery in Hualien Tzu-Chi hospital under either desflurane GA ( n = 10) or LA ( n = 9). We used spike analysis (frequency and modified burst index [MBI]) and the Hilbert transform to obtain signal power measurements for background and spikes, and compared the characterizations of intraoperative microelectrode signals between the two groups. Additionally, STN firing pattern characteristics were determined using a combined approach based on the autocorrelogram and power spectral analysis, which was employed to investigate differences in the oscillatory activities between the groups. Clinical outcomes were assessed using the Unified Parkinson's Disease Rating Scale (UPDRS) before and after surgery. The results revealed burst firing was observed in both groups. The firing frequencies were greater in the LA group and MBI was comparable in both groups. Both the background and spikes were of significantly greater power in the LA group. The power spectra of the autocorrelograms were significantly higher in the GA group between 4 and 8 Hz. Clinical outcomes based on the UPDRS were comparable in both groups before and after DBS surgery. Under controlled light desflurane GA, burst features of the neuronal firing patterns are preserved in the STN, but power is reduced. Enhanced low-frequency (4–8 Hz) oscillations in the MERs for the GA group could be a characteristic signature of desflurane's effect on neurons in the STN.

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            Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering.

            This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods.
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              Large-scale recording of neuronal ensembles.

              How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron-electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                12 December 2017
                2017
                : 11
                : 701
                Affiliations
                [1] 1Institute of Biomedical Engineering, National Taiwan University , Taipei, Taiwan
                [2] 2Department of Neurology, Tzu Chi General Hospital, Tzu Chi University , Hualien, Taiwan
                [3] 3Interdisciplinary Institute of Neuroscience and Technology, Qiushi Academy for Advanced Studies, Zhejiang University , Hangzhou, China
                [4] 4The Ph.D. Program for Neural Regenerative Medicine, College of Medical Science and Technology, Taipei Medical University , Taipei, Taiwan
                [5] 5Department of Biomedical Engineering, National Yang Ming University , Taipei, Taiwan
                [6] 6Department of Mechanical and Computer Aided Engineering, Feng Chia University , Taichung, Taiwan
                [7] 7Department of Life Sciences, Institute of Genome Sciences, National Yang Ming University , Taipei, China
                [8] 8Department of Medicine, National Yang Ming University , Taipei, Taiwan
                [9] 9Department of Neurosurgery, Tzu Chi General Hospital, Tzu Chi University , Hualien, Taiwan
                Author notes

                Edited by: Sergey M. Plis, Mind Research Network, United States

                Reviewed by: Nima Dehghani, Massachusetts Institute of Technology, United States; Li-Wei Kuo, National Health Research Institutes, Taiwan

                *Correspondence: Shin-Yuan Chen william.sychen@ 123456msa.hinet.net

                This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2017.00701
                5733027
                4767c86e-bb6d-4c39-acfe-035815046528
                Copyright © 2017 Lin, Lai, Lo, Chou, Chou, Yang, Sun, Chen, Wang, Liu, Jaw, Chen and Chen.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 30 June 2017
                : 28 November 2017
                Page count
                Figures: 3, Tables: 2, Equations: 9, References: 57, Pages: 10, Words: 7993
                Funding
                Funded by: Ministry of Science and Technology, Taiwan 10.13039/501100004663
                Award ID: 105-2221-E-010-014-MY2
                Award ID: 102-2221-E-010-011-MY3
                Categories
                Neuroscience
                Clinical Trial

                Neurosciences
                parkinson's disease,subthalamic nucleus,deep brain stimulation,microelectrode recording,desflurane general anesthesia,low frequency oscillation

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