Research Group Neuroscience, Interdisciplinary Center for Clinical Research Within the Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany; Institute of Physiology, Medical Faculty, RWTH Aachen University, Aachen, Germany.
Comput Methods Programs Biomed. 2024 Oct;255:108319. doi: 10.1016/j.cmpb.2024.108319. Epub 2024 Jul 6.
The increasing amount of open-access medical data provides new opportunities to gain clinically relevant information without recruiting new patients. We developed an open-source computational pipeline, that utilizes the publicly available electroencephalographic (EEG) data of the Temple University Hospital to identify EEG profiles associated with the usage of neuroactive medications. It facilitates access to the data and ensures consistency in data processing and analysis, thus reducing the risk of errors and creating comparable and reproducible results. Using this pipeline, we analyze the influence of common neuroactive medications on brain activity.
The pipeline is constructed using easily controlled modules. The user defines the medications of interest and comparison groups. The data is downloaded and preprocessed, spectral features are extracted, and statistical group comparison with visualization through a topographic EEG map is performed. The pipeline is adjustable to answer a variety of research questions. Here, the effects of carbamazepine and risperidone were statistically compared with control data and with other medications from the same classes (anticonvulsants and antipsychotics).
The comparison between carbamazepine and the control group showed an increase in absolute and relative power for delta and theta, and a decrease in relative power for alpha, beta, and gamma. Compared to antiseizure medications, carbamazepine showed an increase in alpha and theta for absolute powers, and for relative powers an increase in alpha and theta, and a decrease in gamma and delta. Risperidone compared with the control group showed a decrease in absolute and relative power for alpha and beta and an increase in theta for relative power. Compared to antipsychotic medications, risperidone showed a decrease in delta for absolute powers. These results show good agreement with state-of-the-art research. The database allows to create large groups for many different medications. Additionally, it provides a collection of records labeled as "normal" after expert assessment, which is convenient for the creation of control groups.
The pipeline allows fast testing of different hypotheses regarding links between medications and EEG spectrum through ecological usage of readily available data. It can be utilized to make informed decisions about the design of new clinical studies.
越来越多的开放获取医学数据为在不招募新患者的情况下获取临床相关信息提供了新的机会。我们开发了一个开源的计算管道，该管道利用坦普尔大学医院公开的脑电图（EEG）数据来识别与使用神经活性药物相关的 EEG 图谱。它便于访问数据，并确保数据处理和分析的一致性，从而降低错误风险并创建可比较和可重现的结果。使用该管道，我们分析了常见神经活性药物对大脑活动的影响。
该管道使用易于控制的模块构建。用户定义感兴趣的药物和对照组。下载并预处理数据，提取频谱特征，并通过拓扑脑电图图进行统计组比较和可视化。该管道可调节以回答各种研究问题。在这里，卡马西平与对照组相比，与同一类别的其他药物（抗惊厥药和抗精神病药）相比，统计学上比较了 risperidone 的效果。
卡马西平与对照组相比，绝对和相对 delta 和 theta 功率增加，alpha、beta 和 gamma 相对功率降低。与抗惊厥药物相比，卡马西平的绝对功率增加了 alpha 和 theta，相对功率增加了 alpha 和 theta，降低了 gamma 和 delta。与对照组相比，risperidone 的 alpha 和 beta 绝对功率和 theta 相对功率降低。与抗精神病药物相比，risperidone 的 delta 绝对功率降低。这些结果与最新研究结果吻合良好。该数据库允许为许多不同的药物创建大型群组。此外，它还提供了经过专家评估标记为“正常”的记录集合，这对于创建对照组非常方便。
该管道允许通过对易于获取的数据进行生态利用，快速测试关于药物和 EEG 谱之间联系的不同假设。它可以用于为新的临床研究设计做出明智的决策。
