Blenkinsop Alexander, Anderson Sean, Gurney Kevin
Department of Psychology, University of Sheffield, Sheffield, S10 2TP, UK.
Automatic Control & Systems Engineering, University of Sheffield, Sheffield, S1 3JD, UK.
J Physiol. 2017 Jul 1;595(13):4525-4548. doi: 10.1113/JP273760. Epub 2017 Jun 5.
Neuronal oscillations in the basal ganglia have been observed to correlate with behaviours, although the causal mechanisms and functional significance of these oscillations remain unknown. We present a novel computational model of the healthy basal ganglia, constrained by single unit recordings from non-human primates. When the model is run using inputs that might be expected during performance of a motor task, the network shows emergent phenomena: it functions as a selection mechanism and shows spectral properties that match those seen in vivo. Beta frequency oscillations are shown to require pallido-striatal feedback, and occur with behaviourally relevant cortical input. Gamma oscillations arise in the subthalamic-globus pallidus feedback loop, and occur during movement. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the basal ganglia and lays the foundation for an integrated approach to study basal ganglia pathologies such as Parkinson's disease in silico.
Neural oscillations in the basal ganglia (BG) are well studied yet remain poorly understood. Behavioural correlates of spectral activity are well described, yet a quantitative hypothesis linking time domain dynamics and spectral properties to BG function has been lacking. We show, for the first time, that a unified description is possible by interpreting previously ignored structure in data describing globus pallidus interna responses to cortical stimulation. These data were used to expose a pair of distinctive neuronal responses to the stimulation. This observation formed the basis for a new mathematical model of the BG, quantitatively fitted to the data, which describes the dynamics in the data, and is validated against other stimulus protocol experiments. A key new result is that when the model is run using inputs hypothesised to occur during the performance of a motor task, beta and gamma frequency oscillations emerge naturally during static-force and movement, respectively, consistent with experimental local field potentials. This new model predicts that the pallido-striatum connection has a key role in the generation of beta band activity, and that the gamma band activity associated with motor task performance has its origins in the pallido-subthalamic feedback loop. The network's functionality as a selection mechanism also occurs as an emergent property, and closer fits to the data gave better selection properties. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the BG and therefore lays the foundation for an integrated approach to study BG pathologies such as Parkinson's disease in silico.
尽管基底神经节中的神经元振荡与行为之间的因果机制和功能意义尚不清楚,但已观察到它们与行为相关。我们提出了一种健康基底神经节的新型计算模型,该模型受非人类灵长类动物的单单元记录约束。当使用运动任务执行过程中可能出现的输入来运行该模型时,网络会出现一些涌现现象:它作为一种选择机制发挥作用,并显示出与体内观察到的频谱特性相匹配的频谱特性。研究表明,β频率振荡需要苍白球-纹状体反馈,并在与行为相关的皮层输入时出现。γ振荡出现在丘脑底核-苍白球反馈回路中,并在运动过程中出现。该模型为基底神经节的频谱、时间和功能分析研究提供了一个连贯的框架,并为在计算机上研究帕金森病等基底神经节疾病的综合方法奠定了基础。
基底神经节(BG)中的神经振荡已得到充分研究,但仍了解甚少。频谱活动与行为的相关性已有详细描述,但缺乏一个将时域动态和频谱特性与BG功能联系起来的定量假设。我们首次表明,通过解释描述苍白球内侧核对皮层刺激反应的数据中先前被忽略的结构,可以实现统一描述。这些数据被用于揭示一对对刺激的独特神经元反应。这一观察结果构成了一个新的BG数学模型的基础,该模型经过定量拟合数据,描述了数据中的动态,并通过其他刺激方案实验进行了验证。一个关键的新结果是,当使用假设在运动任务执行过程中出现的输入来运行该模型时,β和γ频率振荡分别在静力和运动过程中自然出现,这与实验局部场电位一致。这个新模型预测,苍白球-纹状体连接在β波段活动的产生中起关键作用,与运动任务表现相关的γ波段活动起源于苍白球-丘脑底核反馈回路。网络作为一种选择机制的功能也作为一种涌现特性出现,与数据的拟合度越高,选择特性越好。该模型为BG的频谱、时间和功能分析研究提供了一个连贯 的框架,因此为在计算机上研究帕金森病等BG疾病的综合方法奠定了基础。