The (hyper)excitable brain: what can a ubiquitous TMS measure reveal about cognitive aging?
The (hyper)excitable brain: what can a ubiquitous TMS measure reveal about cognitive aging?
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DOI：
10.1016/j.neurobiolaging.2023.09.007
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发表时间：
2023-09
影响因子：
4.2
通讯作者：
M. Sundman;Bernadette Elise Avila De Vault;Allison Yu-Chin Chen;Lalitha Madhavan;A. Fuglevand;Ying-hui Chou
中科院分区：
文献类型：
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作者：
M. Sundman;Bernadette Elise Avila De Vault;Allison Yu-Chin Chen;Lalitha Madhavan;A. Fuglevand;Ying-hui Chou
在他们富有洞察力的工作中，Zadey及其同事（2021）对来自先前经颅磁刺激（TMS）试验的辅助静息运动阈值（rMT）数据进行了重新检查，包括认知正常对照组（n= 26），发现AD队列（n= 22）和更大的验证AD队列（n= 129）。尽管其良好的生理相关性，rMT数据通常被忽视的后续TMS协议的组成元素，因为它的基本功能作为一个校准参数，用于确定个性化的TMS强度。该参数的强制性普遍存在产生了相当大的rMT数据缓存，作者利用这些未充分利用的数据在他们的发现和验证队列中建立了一致的发现。具体而言，整体认知功能障碍与rMT降低显著相关，这反映了皮质兴奋性增加。这一发现仅适用于AD患者，并且与记忆障碍有关。Zadey等人“的工作为其他研究人员提供了一个令人信服的提示，以类似地检查以前未开发的rMT数据库，以揭示认知老化的神经生物学特征。在这个简短的交流中，我们将简要地1）将他们的发现置于更广泛的文献中，2）阐明rMT询问的神经成分，3）分享我们自己数据的确证性发现。
In their insightful work, Zadey and colleagues (2021) undertook a discerning re-examination of auxiliary resting motor threshold (rMT) data from previous Transcranial Magnetic Stimulation (TMS) trials encompassing a cognitively normal control group (n= 26), a discovery AD cohort (n= 22), and a larger validation AD cohort (n= 129). Despite its well-described physiological relevance, rMT data are commonly overlooked as a constituent element of subsequent TMS protocols given its essential function as a calibration parameter for the determination of individualized TMS intensity. The obligatory ubiquity of this parameter has generated a sizeable cache of rMT data, and the authors have leveraged this underutilized data to establish a consistent finding across both their discovery and validation cohorts. Specifically, global cognitive dysfunction was significantly associated with reduced rMT, which reflects increased cortical excitability. This finding was exclusive to AD patients and was particularly robust in relation to memory impairment. Zadey et al.’s work serves as a compelling prompt for fellow researchers to similarly examine repositories of previously untapped rMT data to reveal insights into the neurobiological features of cognitive aging. In this short communication, we will briefly 1) contextualize their findings in the broader body of literature, 2) illuminate the neural components interrogated by rMT, and 3) share corroborative findings from our own data.