Test dataset for "Rapid estimation of cortical neuron activation thresholds by transcranial magnetic stimulation using convolutional neural networks"

Data corresponding to test dataset used in Aberra AS, Lopez A, Grill WM, Peterchev AV. (2022). "Rapid estimation of cortical neuron activation thresholds by transcranial magnetic stimulation using convolutional neural networks". bioRxiv. Dataset includes: simnibs/ - SimNIBS mesh and E-field solution file used in test dataset (posterior-anterior TMS of M1 in ernie example mesh, meshed with mri2mesh pipeline) layer_data/ - surface meshes used for placing and orienting neuron models and corresponding sampling grids for CNNs nrn_sim_data/ - Thresholds from NEURON simulations for all 25 model neurons included in the study, each at 4,999-5,000 positions and 12 azimuthal orientations ("ground truth" for CNN) cell_data/ - Coordinates and morphology information for all model neurons weights/ - Trained 3D convolutional neural networks for estimating neuron model-specific TMS thresholds given input E-field distributions on a 3D grid (see code/manuscript for dimensions) est_data/ - Output of trained CNNs on all E-field data for test dataset本数据集为Aberra AS、Lopez A、Grill WM与Peterchev AV于2022年发表于预印本平台bioRxiv的论文《基于卷积神经网络的经颅磁刺激皮层神经元激活阈值快速估算》（Rapid estimation of cortical neuron activation thresholds by transcranial magnetic stimulation using convolutional neural networks）中所使用的测试数据集配套数据。数据集包含以下内容： `simnibs/`：测试数据集所用的SimNIBS网格与电场求解文件，对应Ernie标准示例网格中初级运动皮层（M1）的后前向经颅磁刺激，采用mri2mesh流程完成网格剖分。 `layer_data/`：用于放置与定向神经元模型的表面网格，以及卷积神经网络（Convolutional Neural Network, CNN）采样所需的对应网格数据。 `nrn_sim_data/`：本研究纳入的全部25个模型神经元的NEURON模拟阈值数据，每个神经元对应4999至5000个采样位置与12种方位角方向的阈值，为卷积神经网络的基准真值（ground truth）数据。 `cell_data/`：全部模型神经元的坐标与形态学信息。 `weights/`：经训练的三维卷积神经网络（3D Convolutional Neural Network, 3D CNN）权重文件，可基于三维网格上的输入电场分布，估算特定神经元模型的经颅磁刺激阈值，详细维度信息见代码与论文。 `est_data/`：测试数据集全部电场数据经训练卷积神经网络处理后的输出结果。