Weise Konstantin, Worbs Torge, Kalloch Benjamin, Souza Victor H, Jaquier Aurélien Tristan, Van Geit Werner, Thielscher Axel, Knösche Thomas R
Methods and Development Group "Brain Networks", Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
Faculty of Engineering, Leipzig University of Applied Sciences, Leipzig, Germany.
Imaging Neurosci (Camb). 2023 Dec 4;1. doi: 10.1162/imag_a_00036. eCollection 2023.
We derived computationally efficient average response models of different types of cortical neurons, which are subject to external electric fields from Transcranial Magnetic Stimulation. We used 24 reconstructions of pyramidal cells (PC) from layer 2/3, 245 small, nested, and large basket cells from layer 4, and 30 PC from layer 5 with different morphologies for deriving average models. With these models, it is possible to efficiently estimate the stimulation thresholds depending on the underlying electric field distribution in the brain, without having to implement and compute complex neuron compartment models. The stimulation thresholds were determined by exposing the neurons to TMS-induced electric fields with different angles, intensities, pulse waveforms, and field decays along the somato-dendritic axis. The derived average response models were verified by reference simulations using a high-resolution realistic head model containing several million neurons. The relative errors of the estimated thresholds between the average model and the reference model ranged between -3% and 3.7% in 98% of the cases, while the computation time was only a fraction of a second compared to several weeks. Finally, we compared the model behavior to TMS experiments and observed high correspondence to the orientation sensitivity of motor evoked potentials. The derived models were compared to the classical cortical column cosine model and to simplified ball-and-stick neurons. It was shown that both models oversimplify the complex interplay between the electric field and the neurons and do not adequately represent the directional sensitivity of the different cell types. The derived models are simple to apply and only require the TMS-induced electric field in the brain as input variable. The models and code are available to the general public in open-source repositories for integration into TMS studies to estimate the expected stimulation thresholds for an improved dosing and treatment planning in the future.
我们推导了不同类型皮质神经元的计算效率高的平均反应模型，这些神经元会受到经颅磁刺激产生的外部电场的影响。我们使用了来自第2/3层的24个锥体细胞（PC）重建模型、来自第4层的245个小的、嵌套的和大的篮状细胞以及来自第5层的30个具有不同形态的PC来推导平均模型。利用这些模型，可以根据大脑中潜在的电场分布有效地估计刺激阈值，而无需实现和计算复杂的神经元隔室模型。通过将神经元暴露于具有不同角度、强度、脉冲波形以及沿体-树突轴的场衰减的经颅磁刺激诱导电场来确定刺激阈值。通过使用包含数百万个神经元的高分辨率真实头部模型进行参考模拟，验证了推导得到的平均反应模型。在98%的情况下，平均模型和参考模型之间估计阈值的相对误差在-3%至3.7%之间，而计算时间与数周相比仅为几分之一秒。最后，我们将模型行为与经颅磁刺激实验进行了比较，观察到与运动诱发电位的方向敏感性高度一致。将推导得到的模型与经典的皮质柱余弦模型以及简化的球棒神经元模型进行了比较。结果表明，这两种模型都过度简化了电场与神经元之间的复杂相互作用，并且没有充分体现不同细胞类型的方向敏感性。推导得到的模型易于应用，只需要大脑中经颅磁刺激诱导的电场作为输入变量。这些模型和代码在开源存储库中向公众开放，以便集成到经颅磁刺激研究中，以估计预期的刺激阈值，为未来改进给药和治疗计划提供依据。
