On the Validity of Neural Mass Models.
On the Validity of Neural Mass Models.
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DOI：
10.3389/fncom.2020.581040
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发表时间：
2020
影响因子：
3.2
通讯作者：
Daffertshofer A
中科院分区：
文献类型：
--
作者：
Deschle N;Ignacio Gossn J;Tewarie P;Schelter B;Daffertshofer A
对神经块的动力学进行建模是研究神经群体的常用方法。各种模型已被证明是有用的，以描述丰富的经验观测，包括自我维持的本地振荡和模式的远程同步。我们讨论了在何种程度上真正的质量模型类似的神经种群的平均动态。特别是，我们质疑神经质量模型的有效性，如果正在研究的人口包括一个混合物的兴奋性和抑制性神经元密集（相互）连接。从一个有噪声的泄漏积分和放电神经元网络开始，我们制定了两个不同的种群动力学，都属于开创性的弗里曼神经质量模型的范畴。推导包含了几个平均场假设和膜和突触动力学之间的时间尺度分离。这些神经质量模型的平均动态人口的比较揭示了兴奋性/抑制性神经元的分数以及整体网络的质量模型提供足够的估计程度的界限。对于大量的参数范围，我们的模型不能正确地模拟神经网络的动态，无论是在去同步还是在（高频）同步状态。只有在低频同步发生时，我们的模型才能对平均潜在动态进行适当的估计。虽然这显示了它们的潜力，例如，在研究由脑电描记术获得的静止状态动力学时，我们必须接受这样一个事实，即通过神经网络的质量动力学来预测其更一般的动力学结果需要非常小心。
Modeling the dynamics of neural masses is a common approach in the study of neural populations. Various models have been proven useful to describe a plenitude of empirical observations including self-sustained local oscillations and patterns of distant synchronization. We discuss the extent to which mass models really resemble the mean dynamics of a neural population. In particular, we question the validity of neural mass models if the population under study comprises a mixture of excitatory and inhibitory neurons that are densely (inter-)connected. Starting from a network of noisy leaky integrate-and-fire neurons, we formulated two different population dynamics that both fall into the category of seminal Freeman neural mass models. The derivations contained several mean-field assumptions and time scale separation(s) between membrane and synapse dynamics. Our comparison of these neural mass models with the averaged dynamics of the population reveals bounds in the fraction of excitatory/inhibitory neuron as well as overall network degree for a mass model to provide adequate estimates. For substantial parameter ranges, our models fail to mimic the neural network's dynamics proper, be that in de-synchronized or in (high-frequency) synchronized states. Only around the onset of low-frequency synchronization our models provide proper estimates of the mean potential dynamics. While this shows their potential for, e.g., studying resting state dynamics obtained by encephalography with focus on the transition region, we must accept that predicting the more general dynamic outcome of a neural network via its mass dynamics requires great care.
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DOI：
10.1177/1073858416667720
发表时间：
2017-10
期刊：
The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry
影响因子：
--
作者：
Bassett DS;Bullmore ET
通讯作者：
Bullmore ET
影响因子：
4.6
作者：
Deco, Gustavo;Kringelbach, Morten L.;Ritter, Petra
通讯作者：
Ritter, Petra
影响因子：
4.3
作者：
Deco, Gustavo;Jirsa, Viktor K.;Robinson, Peter A.;Breakspear, Michael;Friston, Karl J.
通讯作者：
Friston, Karl J.
影响因子：
1.9
作者：
JANSEN, BH;RIT, VG
通讯作者：
RIT, VG
影响因子：
3.3
作者：
Avila-Akerberg, O.;Krahe, R.;Chacron, M. J.
通讯作者：
Chacron, M. J.