Replication Data for: Computational Modelling of Cerebellar Magnetic Stimulation: the Effect of Washout

The data are related to the following article: Antonietti A., Casellato C., D'Angelo E. and Pedrocchi A. (2019) Computational Modelling of Cerebellar Magnetic Stimulation: the Effect of Washout Abstract Nowadays, clinicians have multiple tools that they can use to stimulate the brain, by mean of electric or magnetic fields that can interfere with the bio-electrical behaviour of neurons. However, it is not still clear what are the neural mechanisms that are involved and how the external stimulation changes the neural response at network-level. In this paper, we have exploited the simulations carried out using a spiking neural network model inspired to the cerebellar system to shed light on the effects of cerebellar Transcranial Magnetic Stimulation (TMS). Namely, two computational studies have been merged and compared to identify the role of the washout period that follows the TMS stimulation. The two studies employed a very similar experimental protocol: a first session of Pavlovian associative conditioning, the administration of the TMS (effective or sham), a washout period, and a second session of Pavlovian associative conditioning. In one study, the washout period between the two sessions was long (1 week), while the other study foresaw a very short washout (15 minutes). Computational models suggested a mechanistic explanation for the TMS effect on the cerebellum. In this work, we have found that the duration of the washout strongly changes the modification of plasticity mechanisms in the cerebellar network, that is then reflected by the behavioural response. Usage: The code has been tested with MATLAB 2019a 64-bit. With the following files you can reproduce the figures and findings of the referenced paper. All the files need to be in the directory where the simulation is launched. Open with MATLAB the file Analysis_TMS.m and run it. It will generate the three figures and the results reported in the manuscript. The following files are included: - Analysis_TMS.m is the MATLAB script that loads the data and generates figures and results presented in the manuscript. - TMS_Long.mat: includes the CRs in both the experimental study (Monaco et al., 2014) and the computational study (Antonietti et al., 2016) and the optimal parameters of the three different situations (session_1, session_2sham, session_2tms) found by the Genetic Algorithm optimization process. - TMS_Short.mat: includes the CRs in both the experimental study (Monaco et al., 2018) and the computational study (Antonietti et al., 2018) and the optimal parameters of the three different situations (session_1, session_2sham, session_2tms) found by the Genetic Algorithm optimization process. - figureFullScreen.m is used to plot the results. These model files were supplied by Alberto Antonietti. If you have any question/comments/feedback, please contact me.

本数据集关联以下学术论文：Antonietti A.、Casellato C.、D'Angelo E. 与 Pedrocchi A.（2019）《小脑磁刺激的计算建模：洗脱期效应》

摘要 当前，临床医师可借助电场或磁场干预神经元生物电活动的多种脑刺激工具。但目前仍未明确其所涉及的神经机制，以及外部刺激如何在网络层面改变神经响应。本文采用受小脑系统启发的脉冲神经网络（spiking neural network）开展仿真，以阐明小脑经颅磁刺激（Transcranial Magnetic Stimulation, TMS）的作用机制。具体而言，本研究整合两项计算研究并进行对比，以明确TMS刺激后洗脱期的作用。两项研究采用了高度相似的实验方案：首先开展一轮巴甫洛夫联想条件反射训练，随后施加TMS（有效刺激或伪刺激），经过洗脱期后，再开展第二轮巴甫洛夫联想条件反射训练。其中一项研究中两轮实验间的洗脱期为一周（较长时长），而另一项研究的洗脱期仅为15分钟（极短时长）。本研究通过计算模型为TMS对小脑的作用机制提供了合理解释。结果表明，洗脱期的时长会显著改变小脑网络内的可塑性机制变化，并最终反映在行为响应上。

使用说明 本代码已在MATLAB 2019a 64位版本中完成测试。通过下述文件即可复现上述引用论文中的图表与研究结果。所有文件需置于仿真启动所在的目录中。在MATLAB中打开Analysis_TMS.m并运行该脚本，即可生成论文中所述的三张图表与实验结果。

本次发布包含以下文件：
- Analysis_TMS.m：MATLAB脚本，用于加载数据并生成论文中展示的图表与实验结果。
- TMS_Long.mat：包含两项研究的条件反应（Conditioned Responses, CRs）数据，分别为实验研究（Monaco et al., 2014）与计算研究（Antonietti et al., 2016），同时包含通过遗传算法（Genetic Algorithm）优化得到的三种实验情境（第一轮实验、第二轮伪刺激实验、第二轮有效TMS刺激实验）的最优参数。
- TMS_Short.mat：包含两项研究的条件反应数据，分别为实验研究（Monaco et al., 2018）与计算研究（Antonietti et al., 2018），同时包含通过遗传算法优化得到的三种实验情境的最优参数。
- figureFullScreen.m：用于绘制实验结果的辅助脚本。

本模型文件由Alberto Antonietti提供。若有任何疑问、建议或反馈，请联系作者。