Cortical Resonance Frequencies Emerge from Network Size and Connectivity.
Cortical Resonance Frequencies Emerge from Network Size and Connectivity.
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DOI：
10.1371/journal.pcbi.1004740
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发表时间：
2016-02
影响因子：
4.3
通讯作者：
El-Deredy W
中科院分区：
文献类型：
--
作者：
Lea-Carnall CA;Montemurro MA;Trujillo-Barreto NJ;Parkes LM;El-Deredy W
神经振荡发生在很宽的频率范围内，不同的大脑区域在频谱中的特定点处表现出类似共振的特征。在微观尺度上，单个神经元具有内在的振荡特性，因此还不知道皮层共振是神经振荡的结果还是将它们互连的网络的涌现特性。使用网络模型的松耦合的威尔逊-考恩振荡器来模拟一片皮层片，我们证明了激活网络的大小与其谐振频率成反比。参数空间的进一步分析表明，兴奋性和抑制性连接的数量，以及单位之间的平均传输延迟，决定了共振频率。该模型预测，如果视觉皮层内的激活网络的大小增加，则网络的共振频率会降低。我们使用稳态视觉诱发电位实验测试了这一预测，我们在一系列驱动频率下用不同大小的刺激刺激视觉皮层。我们证明了对应于峰值稳态响应的频率与网络的大小成反比。我们的结论是，虽然个别神经元具有共振特性，振荡活动在宏观层面上的强烈影响网络的相互作用，稳态响应可以用来调查功能网络。当受到重复刺激时，感觉皮层似乎在不同的驱动频率下产生最大的反应或共振：视觉皮层为10 Hz;体感和听觉皮层分别为20 Hz和40 Hz。共振频率与相应区域的皮质体积呈负相关，但目前还不清楚是什么驱动了这种关系。在这里，我们使用计算和经验数据来证明，共振频率是底层网络的连接参数的涌现属性。实验范例用不同大小的由闪烁的点组成的物体刺激视觉皮层的大小区域，并改变驱动频率。较大的皮质区表现出最大的反应，在较低的频率比较小的地区，这表明皮质大小和共振频率之间的反比关系，即使在相同的感觉方式。在计算上，我们模拟了不同大小的皮层补丁，并改变了它们的连接参数。我们证明了激活网络的大小与其谐振频率成反比，并且这种变化是由于较大网络内的传输延迟增加和节点度更大。这些结果对于理解振荡过程的功能意义以及作为探测功能连接变化的工具是很重要的。
Neural oscillations occur within a wide frequency range with different brain regions exhibiting resonance-like characteristics at specific points in the spectrum. At the microscopic scale, single neurons possess intrinsic oscillatory properties, such that is not yet known whether cortical resonance is consequential to neural oscillations or an emergent property of the networks that interconnect them. Using a network model of loosely-coupled Wilson-Cowan oscillators to simulate a patch of cortical sheet, we demonstrate that the size of the activated network is inversely related to its resonance frequency. Further analysis of the parameter space indicated that the number of excitatory and inhibitory connections, as well as the average transmission delay between units, determined the resonance frequency. The model predicted that if an activated network within the visual cortex increased in size, the resonance frequency of the network would decrease. We tested this prediction experimentally using the steady-state visual evoked potential where we stimulated the visual cortex with different size stimuli at a range of driving frequencies. We demonstrate that the frequency corresponding to peak steady-state response inversely correlated with the size of the network. We conclude that although individual neurons possess resonance properties, oscillatory activity at the macroscopic level is strongly influenced by network interactions, and that the steady-state response can be used to investigate functional networks. When entrained using repetitive stimulation, sensory cortices appear to respond maximally, or resonate, at different driving frequencies: 10Hz in visual cortex; 20Hz and 40Hz in somatosensory and auditory cortices, respectively. The resonance frequencies are inversely correlated to the cortical volume of the respective regions, but it is unclear what drives this relationship. Here we used both computational and empirical data to demonstrate that resonance frequencies are emergent properties of the connectivity parameters of the underlying networks. The experimental paradigm stimulated large and small areas of visual cortex with different size objects made of flickering dots, and varied the driving frequency. Larger cortical areas exhibited maximum response at lower frequency than smaller areas, suggesting the inverse relationship between cortical size and resonance frequency holds, even within the same sensory modality. Computationally, we simulated cortical patches of different sizes and varied their connectivity parameters. We demonstrate that the size of the activated network is inversely related to its resonance frequency and that this change is due to the increased transmission delay and greater node degree within the larger network. The results are important for understanding the functional significance of oscillatory processes, and as a tool for probing changes in functional connectivity.