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用于导航神经调节的个体化脑图谱

Individualized brain mapping for navigated neuromodulation.

作者信息

Gao Chaohong, Wu Xia, Cheng Xinle, Madsen Kristoffer Hougaard, Chu Congying, Yang Zhengyi, Fan Lingzhong

机构信息

Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100190, China.

Brainnetome Center, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

出版信息

Chin Med J (Engl). 2024 Mar 5;137(5):508-523. doi: 10.1097/CM9.0000000000002979. Epub 2024 Jan 24.

DOI:10.1097/CM9.0000000000002979
PMID:38269482
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10932519/
Abstract

The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

摘要

大脑是一个复杂的器官,需要精确的图谱来了解其结构和功能。脑图谱为研究脑回路、发现早期诊断的生物标志物以及开发神经精神疾病的个性化治疗方法提供了一个强大的工具。神经调节技术,如经颅磁刺激和深部脑刺激,已经彻底改变了神经精神疾病的临床治疗方法。然而,缺乏精细尺度的脑图谱限制了这些技术的精度和有效性。神经成像和机器学习技术的进步导致了立体定向辅助神经外科手术和导航系统的出现。尽管如此,患者之间的个体差异和脑部疾病的多样性使得开发个性化解决方案成为必要。本文概述了个性化脑图谱和导航神经调节的最新进展,并讨论了这些技术的方法概况、优点、缺点和未来趋势。文章最后提出了关于个性化脑图谱和导航神经调节未来发展的开放性问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/5e3e58ebe26e/cm9-137-508-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/cab02dce23a1/cm9-137-508-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/e5cbc303313c/cm9-137-508-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/5e3e58ebe26e/cm9-137-508-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/cab02dce23a1/cm9-137-508-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/e5cbc303313c/cm9-137-508-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b1/10932519/5e3e58ebe26e/cm9-137-508-g003.jpg

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本文引用的文献

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Computing personalized brain functional networks from fMRI using self-supervised deep learning.使用自监督深度学习从 fMRI 计算个性化脑功能网络。
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