第十六期 fNIRS Journal Club 通知 2021/01/23,1pm

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潘亚峰

瑞典 Karolinska Institutet的潘亚峰博士将为大家讲解他们最近发布的一篇用超扫描研究教师学生关系的文章。热烈欢迎大家参与讨论。潘博士为了这次报告,需要一大早就起床。因此本次报告的时间比过去要稍晚一点。

时间: 北京时间2021年1月23日周六下午1点
地点: https://zoom.com
房间号: 815 4986 9861
密码: 796475

Pan, Guyon, Borragán, Hu, Peigneux (2020) Interpersonal brain synchronization with instructor compensates for learner’s sleep deprivation in interactive learning Biochemical pharmacology () 114111. 点击查看

该文献的PUBMED信息
PMID: 32569629
DOI: 10.1016/j.bcp.2020.114111

Abstract: Recent advances shifted the focus on single-brain functioning toward two-brain communication during learning interactions, following the demonstration that interpersonal brain synchronization (IBS) can track instructor-learner information exchange. Here, we investigated (i) whether sleep deprivation (SD) that potentially impacts both social interactions and learning abilities modulates IBS, and (ii) conversely whether and to what extent IBS might compensate for SD-related learning deficits. Instructors (always with regular sleep, RS) were asked to teach numerical reasoning strategies to learners (either SD or RS), during which the activity of both brains was simultaneously recorded using functional near-infrared spectroscopy (fNIRS). SD learners initially performed below their baseline level, worse than RS learners, but learning improvement was comparable between RS and SD conditions after learning with the instructor. IBS within the instructor-learner dyads was higher in the SD (vs. RS) condition in the left inferior frontal cortex. In addition, clustered IBS (estimated by nonnegative matrix factorization) was correlated with performance improvement. Finally, Granger Causality analyses revealed biased causality with higher instructor-to-learner than learner-to-instructor directionality in brain signal processing. Together, these results indicate that SD-related learning deficits can to some extent be compensated via interactions with an instructor, as reflected by increased IBS and preserved learning ability. It suggests an essential role of the instructor in driving synchrony between teaching and SD learning brains during interactions.

采用基于频率簇(Cluster)的置换检验(Permutation)方法选取感兴趣频段

作者:北京师范大学 龙宇航,longyuhangwork@163.com代码来源(见本页底部):周思远 在使用wtc计算脑间神经同步后,我们需要在多个频率段、多个通道组合上对神经同步值进行统计检验,因此当进行频段选择时,面临多重比较的问题。为了解决多重比较的问题,可以采取基于参数或非参数检验的多重比较矫正的方法。由于基于非参数检验的多重比较矫正对数据的分布形态没有严格要求,因此具有更广泛的应用场景 (Maris and Oostenveld, 2007)。本文即介绍基于随机置换的非参数检验的方法 (Zheng et al., 2020; Long et al., 2021)。 在寻找感兴趣的效应时,我们采取了基于频率簇(Cluster)的方法,即在频率方向寻找连续显著的Cluster,该方法比基于最强效应点的方法具有更为优秀的抗噪音能力。值得注意的是,我们并没有沿着通道的方向去寻找连续显著的通道簇,这是因为沿着通道方向寻找Cluster容易受到生理噪音的影响。 下面进入具体的实操部分。假设本例招募了22对组1被试及22对组2被试,每对被试分别进行3种条件的任务,因此本例是2(组别,被试间因素)*3(条件,被试内因素)的实验设计。本例对神经同步值进行2*3的混合方差分析,并关注交互作用。 具体来讲,进行置换检验需要进行以下几个步骤:1. 重采样;2. 对随机样本进行计算及统计;3. 计算真实样本的统计量;4. 真实样本与随机样本的对比。下面依次进行介绍。 1. 重采样...
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第二十期 fNIRS Journal Club 通知 2021/06/26,10:00am

同时用fNIRS和EEG测量脑信号有哪些好处?技术上应该注意什么?美国斯坦福大学李日辉博士,将为大家讲解他做过的一个同时用fNIRS和EEG测量的实验。热烈欢迎大家参与讨论。 时间: 北京时间2021年6月26日上午10:00地点: https://zoom.com房间号: 856 9352 0230密码: 695930 李博士要讲解的文章如下: Li, Li, Roh, Wang, Zhang (2020) Multimodal Neuroimaging Using Concurrent EEG/fNIRS for Poststroke Recovery Assessment:...
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Calculate phase difference between two general signals (e.g. HbO…

In a recent fNIRS journal club (vedio recorded here), Dr. Tong talked about their work on the phase difference between oxy and deoxy Hb,...
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