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      Linear Predictive Approaches Separate Field Potentials in Animal Model of Parkinson's Disease

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          Abstract

          Parkinson's disease (PD) causes impaired movement and cognition. PD can involve profound changes in cortical and subcortical brain activity as measured by electroencephalography or intracranial recordings of local field potentials (LFP). Such signals can adaptively guide deep-brain stimulation (DBS) as part of PD therapy. However, adaptive DBS requires the identification of triggers of neuronal activity dependent on real time monitoring and analysis. Current methods do not always identify PD-related signals and can entail delays. We test an alternative approach based on linear predictive coding (LPC), which fits autoregressive (AR) models to time-series data. Parameters of these AR models can be calculated by fast algorithms in real time. We compare LFPs from the striatum in an animal model of PD with dopamine depletion in the absence and presence of the dopamine precursor levodopa, which is used to treat motor symptoms of PD. We show that in dopamine-depleted mice a first order AR model characterized by a single LPC parameter obtained by LFP sampling at 1 kHz for just 1 min can distinguish between levodopa-treated and saline-treated mice and outperform current methods. This suggests that LPC may be useful in online analysis of neuronal signals to guide DBS in real time and could contribute to DBS-based treatment of PD.

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          Most cited references35

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          Linear prediction: A tutorial review

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            Measuring phase-amplitude coupling between neuronal oscillations of different frequencies.

            Neuronal oscillations of different frequencies can interact in several ways. There has been particular interest in the modulation of the amplitude of high-frequency oscillations by the phase of low-frequency oscillations, since recent evidence suggests a functional role for this type of cross-frequency coupling (CFC). Phase-amplitude coupling has been reported in continuous electrophysiological signals obtained from the brain at both local and macroscopic levels. In the present work, we present a new measure for assessing phase-amplitude CFC. This measure is defined as an adaptation of the Kullback-Leibler distance-a function that is used to infer the distance between two distributions-and calculates how much an empirical amplitude distribution-like function over phase bins deviates from the uniform distribution. We show that a CFC measure defined this way is well suited for assessing the intensity of phase-amplitude coupling. We also review seven other CFC measures; we show that, by some performance benchmarks, our measure is especially attractive for this task. We also discuss some technical aspects related to the measure, such as the length of the epochs used for these analyses and the utility of surrogate control analyses. Finally, we apply the measure and a related CFC tool to actual hippocampal recordings obtained from freely moving rats and show, for the first time, that the CA3 and CA1 regions present different CFC characteristics.
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              Modeling Parkinson's disease in rats: an evaluation of 6-OHDA lesions of the nigrostriatal pathway.

              Human idiopathic Parkinson's disease (PD) is a progressive neurodegenerative disorder that is primarily characterized by degeneration of the dopaminergic neurons of the nigrostriatal pathway. Different 6-OHDA rat models of PD have been developed in which this toxin has been injected into different parts of the nigrostriatal pathway: (a) the medial forebrain bundle which leads to extensive dopamine (DA) depletion; (b) the substantia nigra pars compacta, which leads to more specific and moderate DA depletions; and (c) subregions of the caudate-putamen complex (CPu), which also leads to specific DA depletions. In this article we review the dopaminergic depletion and behavioral consequences of 6-OHDA lesions in the rat. It was examined whether the relation between DA depletion and behavioral deficits mimic idiopathic PD. In addition, it was evaluated which model most closely approximates the human situation, especially in relation to the stage of this progressive disease. It was concluded that with respect to the site of the lesion, rats with partial lesions of the ventrolateral CPu are the most appropriate models to study early and late stages of PD. The choice of the behavioral parameters determines the use of unilateral or bilateral lesions, although it is obvious that the bilateral model mimics the human situation more closely. (c) 2002 Elsevier Science (USA).
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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
                24 April 2020
                2020
                : 14
                : 394
                Affiliations
                [1] 1Department of Electrical and Computer Engineering, The University of Iowa , Iowa City, IA, United States
                [2] 2DISTek Integration Inc. , Cedar Falls, IA, United States
                [3] 3Department of Neurology, Medical School, University of Minnesota , Minneapolis, MN, United States
                [4] 4Shandong Provincial Key Laboratory of Computer Networks, Shandong Computer Science Center , Jinan, China
                [5] 5Department of Neurology, Papajohn Biomedical Institute, The University of Iowa , Iowa City, IA, United States
                Author notes

                Edited by: Olivier David, Institut National de la Santé et de la Recherche Médicale (INSERM), France

                Reviewed by: Rafael Naime Ruggiero, University of São Paulo, Brazil; Alina Voda, Université Grenoble Alpes, France

                *Correspondence: Md Fahim Anjum mdfahim-anjum@ 123456uiowa.edu

                This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2020.00394
                7193738
                32390797
                00abf7aa-248a-4ade-a163-62015c90ff30
                Copyright © 2020 Anjum, Haug, Alberico, Dasgupta, Mudumbai, Kennedy and Narayanan.

                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) and the copyright owner(s) 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
                : 18 September 2019
                : 30 March 2020
                Page count
                Figures: 12, Tables: 2, Equations: 12, References: 51, Pages: 15, Words: 8782
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: MH116043
                Categories
                Neuroscience
                Original Research

                Neurosciences
                levodopa,linear predictive coding,local field potential,mice,parkinson's disease
                Neurosciences
                levodopa, linear predictive coding, local field potential, mice, parkinson's disease

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