Faculty of Biology, University of Freiburg, Freiburg, D-79104, Germany.
Bernstein Center Freiburg, University of Freiburg, Freiburg, D-79104, Germany.
eNeuro. 2017 Aug 23;4(4). doi: 10.1523/ENEURO.0348-16.2017. eCollection 2017 Jul-Aug.
The striatum is the main input nucleus of the basal ganglia. Characterizing striatal activity dynamics is crucial to understanding mechanisms underlying action selection, initiation, and execution. Here, we studied the effects of spatial network connectivity on the spatiotemporal structure of striatal activity. We show that a striatal network with nonmonotonically changing distance-dependent connectivity (according to a gamma distribution) can exhibit a wide repertoire of spatiotemporal dynamics, ranging from spatially homogeneous, asynchronous-irregular (AI) activity to a state with stable, spatially localized activity bumps, as in "winner-take-all" (WTA) dynamics. Among these regimes, the unstable activity bumps [transition activity (TA)] regime closely resembles the experimentally observed spatiotemporal activity dynamics and neuronal assemblies in the striatum. In contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can exhibit only an AI state. Thus, given the observation of spatially compact neuronal clusters in the striatum, our model suggests that recurrent connectivity among striatal projection neurons should vary nonmonotonically. In brain disorders such as Parkinson's disease, increased cortical inputs and high striatal firing rates are associated with a reduction in stimulus sensitivity. Consistent with this, our model suggests that strong cortical inputs drive the striatum to a WTA state, leading to low stimulus sensitivity and high variability. In contrast, the AI and TA states show high stimulus sensitivity and reliability. Thus, based on these results, we propose that in a healthy state the striatum operates in a AI/TA state and that lack of dopamine pushes it into a WTA state.
纹状体是基底神经节的主要输入核。对纹状体活动动力学进行特征描述对于理解动作选择、启动和执行的机制至关重要。在这里,我们研究了空间网络连通性对纹状体活动时空结构的影响。我们表明,具有非单调变化的距离相关连通性(根据伽马分布)的纹状体网络可以表现出广泛的时空动力学范围,从空间均匀、异步不规则(AI)活动到具有稳定、空间局部活动峰的状态,如“胜者通吃”(WTA)动力学。在这些状态中,不稳定的活动峰[过渡活动(TA)]状态与实验观察到的纹状体中的时空活动动力学和神经元集合非常相似。相比之下,具有单调下降的距离相关连通性(呈高斯方式)的纹状体网络只能表现出 AI 状态。因此,鉴于在纹状体中观察到空间紧凑的神经元簇,我们的模型表明,纹状体投射神经元之间的递归连通性应该是非单调变化的。在帕金森病等脑部疾病中,皮质输入增加和纹状体放电率升高与刺激敏感性降低有关。与这一观点一致,我们的模型表明,强大的皮质输入将纹状体驱动到 WTA 状态,导致低刺激敏感性和高变异性。相比之下,AI 和 TA 状态表现出高刺激敏感性和可靠性。因此,基于这些结果,我们提出在健康状态下,纹状体处于 AI/TA 状态,而缺乏多巴胺会将其推向 WTA 状态。