NIRS can’t measure deep brain, … maybe it can!

1 min read

Is NIRS able to measure signal from deep brain structure, such as amygdala? The short answer is no. NIRS is only able to measure the surface of the brain. This is a serious limitation of NIRS compared to fMRI which is able to measure the entire brain.

However, brain is a highly connected network. Deep brain is not isolated from the surface. So maybe we can infer the deep brain activity based on the surface. And this is exactly what we have done.

In a recent publication titled “Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy”, we used concurrent fMRI-NIRS technology to measure both deep and surface brain activity and explored the possibility to infer deep brain based on surface brain activity measure by NIRS. The result is very encouraging – we are able to infer deep brain from surface activity (correlation ~0.7).

This paper is published in Biomedical Optics Express with Dr Ning Liu, a NIRS expert, as the first author. You can find the paper at http://www.opticsinfobase.org/boe/fulltext.cfm?uri=boe-6-3-1074&id=312512

Abstract:

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research.


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fNIRS Journal Club 视频

546个被试的大型实验是怎么做的?近红外超扫描技术如何揭开群体冲突的神经机制?北京时间2020年5月29日周五上午11点,北京师范大学的马燚娜教授(Yina Ma)为大家讲解了她们组刚刚在Nature Neuroscience发表的文章。下面是报告视频。第一个是在Youtube,第二个是在youku。 Youtube:https://www.youtube.com/watch?v=4qZ7zP-BGz4Youku:https://v.youku.com/v_show/id_XNDY5MTc0MjAxMg==.html 她讲的文献如下: Within-group synchronization in the prefrontal cortex associates with intergroup conflict. Nature neuroscience https://www.storkapp.me/pubpaper/32341541 中文摘要(人工智能翻译,仅供参考):陷入群体的个人有时会失去自己的个性,冒着通常会避免的风险,以无端的敌对态度与外界接触。在这项研究中,我们确定了右侧背外侧前额叶皮层(rDLPFC)和右侧颞顶交界处(rTPJ)的组内神经同步是组间敌对性的潜在机制。我们将546个人组织为91个三对三人小组间比赛,诱导了组内亲和,并使用功能性近红外光谱仪测量了神经活动和组内同步。在组内亲和之后,个人给组内成员的钱比给组外成员的钱多,并且捐出更多的钱来击败竞争对手。组内亲和减少了rDLPFC的活动,并增加了rDLPFC和rTPJ之间的功能连接。尤其是在组外攻击期间,组内亲和还增加了rDLPFC和rTPJ中的组内同步,并且组内rDLPFC同步与组间敌对性正相关。组内同步减少前额活动可能可以解释组内联结如何导致对外界的冲动和集体敌视。
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fNIRS Journal Club 通知 2020/5/29, 11am

546个被试的大型实验是怎么做的?近红外超扫描技术如何揭开群体冲突的神经机制?北京时间2020年5月29日周五上午11点,北京师范大学的马燚娜教授(Yina Ma)将为大家讲解她们组刚刚在Nature Neuroscience发表的文章。 欢迎大家参加并参与讨论。 时间: 北京时间2020年5月29日周五上午11点 地点: https://zoom.com/j/84320310196房间号: 843 2031 0196 密码: 600516 她要讲的文献如下: Within-group synchronization in the prefrontal cortex associates with intergroup conflict....
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