Transmission of delta band (0.5-4 Hz) oscillations from the globus pallidus to the substantia nigra pars reticulata in dopamine depletion.

IF 1.5 4区 医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Computational Neuroscience Pub Date : 2022-08-01 Epub Date: 2023-06-02 DOI:10.1007/s10827-023-00853-z
Timothy C Whalen, John E Parker, Aryn H Gittis, Jonathan E Rubin
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Abstract

Parkinson's disease (PD) and animal models of PD feature enhanced oscillations in several frequency bands in the basal ganglia (BG). Past research has emphasized the enhancement of 13-30 Hz beta oscillations. Recently, however, oscillations in the delta band (0.5-4 Hz) have been identified as a robust predictor of dopamine loss and motor dysfunction in several BG regions in mouse models of PD. In particular, delta oscillations in the substantia nigra pars reticulata (SNr) were shown to lead oscillations in motor cortex (M1) and persist under M1 lesion, but it is not clear where these oscillations are initially generated. In this paper, we use a computational model to study how delta oscillations may arise in the SNr due to projections from the globus pallidus externa (GPe). We propose a network architecture that incorporates inhibition in SNr from oscillating GPe neurons and other SNr neurons. In our simulations, this configuration yields firing patterns in model SNr neurons that match those measured in vivo. In particular, we see the spontaneous emergence of near-antiphase active-predicting and inactive-predicting neural populations in the SNr, which persist under the inclusion of STN inputs based on experimental recordings. These results demonstrate how delta oscillations can propagate through BG nuclei despite imperfect oscillatory synchrony in the source site, narrowing down potential targets for the source of delta oscillations in PD models and giving new insight into the dynamics of SNr oscillations.

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多巴胺耗竭时从苍白球到黑质网状部的δ带(0.5-4 Hz)振荡的传输。
帕金森病(PD)和帕金森病动物模型的特征是基底神经节(BG)中几个频带的振荡增强。过去的研究强调了13-30Hzβ振荡的增强。然而,最近,在PD小鼠模型中,δ带(0.5-4 Hz)的振荡已被确定为多巴胺损失和几个BG区域运动功能障碍的有力预测因子。特别是,黑质网状部(SNr)的δ振荡被证明会导致运动皮层(M1)的振荡,并在M1损伤下持续存在,但尚不清楚这些振荡最初是在哪里产生的。在本文中,我们使用一个计算模型来研究由于苍白球(GPe)的投影,SNr中可能会出现德尔塔振荡。我们提出了一种网络结构,该结构结合了振荡GPe神经元和其他SNr神经元对SNr的抑制。在我们的模拟中,这种配置在模型SNr神经元中产生的放电模式与体内测量的相匹配。特别是,我们在SNr中看到了近反相主动预测和非主动预测神经群体的自发出现,这些神经群体在基于实验记录的STN输入的情况下持续存在。这些结果表明,尽管震源位置的振荡同步性不完美,但德尔塔振荡如何通过BG核传播,缩小了PD模型中德尔塔振荡源的潜在目标,并对SNr振荡的动力学提供了新的见解。
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来源期刊
CiteScore
2.00
自引率
8.30%
发文量
32
审稿时长
3 months
期刊介绍: The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.
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