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2022, Neuron. DOI: 10.1016/j.neuron.2022.08.012
Automated optimization of TMS coil placement for personalized functional network engagement
Charles J. Lynch , Immanuel G. Elbau , Tommy H. Ng , Danielle Wolk , Shasha Zhu , Aliza Ayaz , Jonathan D. Power , Benjamin Zebley , Faith M. Gunning , Conor Liston
Abstract:
Transcranial magnetic stimulation (TMS) is used to treat multiple psychiatric and neurological conditions by manipulating activity in particular brain networks and circuits, but individual responses are highly variable. In clinical settings, TMS coil placement is typically based on either group average functional maps or scalp heuristics. Here, we found that this approach can inadvertently target different functional networks in depressed patients due to variability in their functional brain organization. More precise TMS targeting should be feasible by accounting for each patient’s unique functional neuroanatomy. To this end, we developed a targeting approach, termed targeted functional network stimulation (TANS). The TANS approach improved stimulation specificity in silico in 8 highly sampled patients with depression and 6 healthy individuals and in vivo when targeting somatomotor functional networks representing the upper and lower limbs. Code for implementing TANS and an example dataset are provided as a resource.
2022-10-26 15:51:00
#paper doi: https://doi.org/10.1016/j.neuron.2022.08.012,Automated optimization of TMS coil placement for personalized functional network engagement。本文提出了基于个体化的功能网络分区的TMS刺激方法(TANS)。TMS用于治疗多种精神和神经系统疾病,但由于个体的功能网络分布不同,所以个体反应是高度可变的。传统的基于组水平的TMS方法可能会无意中针对抑郁症患者的不同功能网络,导致疗效不佳。而作者开发的 TANS方法,选择的线圈位置则是使得个体目标功能网络受刺激占比最高的位置。作者从计算机和活体验证两方面,验证了TASN可以提高被试的刺激特异性。
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