头皮
计算机科学
皮质(解剖学)
概率逻辑
大脑定位
人工智能
体素
模式识别(心理学)
神经科学
医学
生物
解剖
作者
fei liu,Zong Zhang,Yuanyuan Chen,Lijiang Wei,Yilong Xu,Zheng Li,Chaozhe Zhu
标识
DOI:10.1016/j.brs.2023.11.011
摘要
Synthesis of neural imaging information from many studies is valuable for identifying stable cortical targets for non-invasive brain stimulation (NIBS). Typically, these targets are specified in Montreal Neurological Institute (MNI) standard brain space. However, in practical NIBS applications, localizing MNI cortical targets often relies on the International 10-20 system or heuristic scalp approaches, which often lacks precision or applies only to specific targets.We aim to establish a probabilistic mapping from any cortical target in MNI space to continuous proportional coordinate (CPC) standard scalp space (MNI2CPC) and assess the performance of this mapping for NIBS targeting.The MNI2CPC mapping was calculated based on a large MRI dataset (n = 114). Its targeting error was evaluated via cross-individual validation using a leave-one-out approach, as well as through independent validation across race (n = 27) and across patient (n = 58) cohorts.The cross-individual validation demonstrated targeting errors of 4.03 ± 0.69 mm on the scalp and 3.30 ± 0.59 mm in the cortex. For independent cohorts, targeting errors were 4.71 ± 0.81 mm (scalp) and 3.85 ± 0.64 mm (cortex) across race, and 4.66 ± 0.77 mm (scalp) and 3.77 ± 0.61 mm (cortex) across patient. We publish a free online tool to enable querying of the CPC coordinate for any given MNI cortical target. The resulting CPC coordinates enable rapid and accurate manual localization on the scalp in a user-friendly manner.The MNI2CPC mapping developed in this study allows for manual localization of any MNI cortical target, which improves the accessibility and ease of application of NIBS in diverse settings.
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