How to find NIRS experts using “Find Experts” app

January 12th, 2018

If you are a newcomer in the NIRS field, you may wonder who are the experts in this field. You might know a few already - for example your boss. But who else are there and where they are?

We developed “Find Experts” app to quickly find experts based on scientific publications in any biomedical field. Let’s see who are experts in the NIRS field.

Use "Find Experts" to find experts in NIRS field

Website: Find Experts of Stork

Author: Xu Cui Categories: programming, stork Tags:

近红外脑功能成像技术 小型私人辅导培训

January 3rd, 2018

代朋友发布这个培训信息。有兴趣直接联系 fnirs_studio@outlook.com

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近红外脑功能成像技术 小型私人辅导培训

培训单元:

(一) 近红外脑功能成像技术原理及理论基础

关键词:连续波(CW),时域(time domain),频域(frequency domain), 吸收系数,散射系数,消光系数,修正的朗伯-比尔定律(Modified Beer-Lambert Law, MBLL), 辐射传输方程的扩散近似

(二) 数据采集基本流程

关键词:实验设计,脑区定位,Eprime,Matlab,定位仪Digitizer  (以一个单人或双人数据采集为例).

(三) 单人脑部扫描数据前期处理(去噪音及脑部定位)

关键词: 生理干扰(cardiac and respiratory),机器噪音(signal draft), 带通滤波器 (bandpass filter), 运动伪迹(motion artifact), CBSI correction,脑区定位

(四) 任务态数据处理及结果呈现 (以手指敲击实验为例)

关键词:一般线性模型 (GLM),xjview

(五) 双人同步扫描(超扫描)实验数据处理步骤

关键词:小波相干分析(wavelet correlation analysis), 重叠脑区定位

每个培训单元包括两个课时,每个课时包括30 分钟教学式辅导+ 5分钟问答时间。

培训老师简历: 生物医学工程博士(美),有十年以上近红外成像领域科研经验。对近红外脑功能成像有深入研究和丰富实践经验。进行过的科研项目包括:单人和双人,成人和儿童,正常人和特殊人群 脑功能成像。 并发展了近红外成像神经反馈技术,和应用近红外学习深层脑部信号等技术。

咨询详情,请联系:fnirs_studio@outlook.com

Author: Xu Cui Categories: brain, nirs Tags:

Number of PubMed papers

December 7th, 2017

From 2000 and 2010, the number of PubMed citations had grown from half million to 1 million. Today we see ~3,000 new papers everyday!

PubMed citations doubles in 10 years

PubMed citations doubles in 10 years

Year Number
2016 1258608
2015 1253004
2014 1201621
2013 1146180
2012 1085504
2011 1017939
2010 940347
2009 875631
2008 835283
2007 784836
2006 746487
2005 699162
2004 638433
2003 593404
2002 564380
2001 546100
2000 531703
1999 492961
1998 473304
1997 455641
1996 457788
1995 448124
1994 437709
1993 426674
1992 417191
1991 412490
1990 410185
1989 402163
1988 386534
1987 367462
1986 349127
1985 334843
1984 317837
1983 309102
1982 295041
1981 283253
1980 280186
Author: Xu Cui Categories: writing Tags:

How to track new NIRS publications and grants?

October 27th, 2017

Near infrared spectroscopy (NIRS) is an increasingly popular technology in brain imaging research. Compared to fMRI, NIRS can be used for more naturalistic experiments, including face to face communication, natural body movements, sports, infants, and is well suited for real-time applications.

If we count the number of NIRS publications using keyword (NIRS OR fNIRS) AND brain, we find the number increases steadily over the past 10 years:

With this trend, it’s expected that we will reach a speed of 1 new paper every day in the year of 2018 or 2019. This is a fast field, and it’s nearly impossible for us to search (NIRS OR fNIRS) AND brain every day or even every week. For a student who does not follow literature proactively, he might know of a paper a year after its publication.

The easiest way to solve this problem is to use an app to notify us of the new publications. The one I use is called Stork . All I need to do is to enter a few keywords I am interested in, e.g.:

(NIRS OR fNIRS) AND brain

But what if I want to follow more specific fields, such as hyperscanning, or comparison with fMRI etc? We can enter the following keywords:
(NIRS OR fNIRS) AND brain AND hyperscanning
(NIRS OR fNIRS) AND brain AND fMRI
(NIRS OR fNIRS) AND brain AND "deep learning"
(NIRS OR fNIRS) AND brain AND social

What if I want to follow some scientists in the field? We may enter their names, such as:
David Boas
Allan Reiss (NIRS or fNIRS)

After we setup the keywords, Stork, like a diligent assistant, will search for us every day. If she finds something, she will send an email to us, listing the new publications. A recent example is shown below:

fmri nirs

Papers
The Temporal Muscle of the Head Can Cause Artifacts in Optical Imaging Studies with Functional Near-Infrared Spectroscopy. by Martin Schecklmann, Alexander Mann, …, Florian B Haeussinger (2017) Front Hum Neurosci (impact factor: 3.6) Free full text

nirs brain

Papers
Enhancing Performance of a Hybrid EEG-fNIRS System Using Channel Selection and Early Temporal Features. by Rihui Li, Thomas Potter, Weitian Huang, Yingchun Zhang (2017) Front Hum Neurosci (impact factor: 3.6)Free full text

Not only does Stork search scientific publications for you, she also searches NIH grant database (this is an advanced feature). That means whenever some researchers receive a grant on NIRS, you will know it. You will know what is his research direction in the next few years, how much money he received etc. This feature is mostly useful for professors and senior graduate students and postdocs.

The link of Stork is: storkapp.me and it’s very easy to use.

Stork

Stork

Author: Xu Cui Categories: nirs, stork Tags:

xjview 9.6 released

October 12th, 2017

In this version, we modified the templates for 3-D render view and use a high-resolution template. It also includes a few scalp view. You may pick up your favorite display for your paper (or presentation). Please go to the download page to download.

xjview 9.6 Render View xjview 9.6 Render View

The render view for the previous version is shown below to compare.

xjview 9 Render View xjview 9 Render View

This update is brought to you by Dr. Weiwei Men (email: wmen AT pku.edu.cn) from Center for Magnetic Resonance Imaging Research, Peking University, China. Weiwei has been using xjView for 10 years. He noticed that the image resolution of the render view in xjView 9 is low, and took the effort to create a new view using a high resolution template (ICBM152_asys_2009C). Thank him for his excellent work!
Weiwei Men

Author: Xu Cui Categories: matlab, programming Tags:

How much do we know about the universe? Hubble’s Ultra Deep Field Experiment

September 13th, 2017

When we looked at the space at night, we see a lot of stars, dotted on a vast dark space. But is there anything in the dark area?

Guess, in the photo below, how many stars are in the red circle? None? A few? A few thousand? Billions of stars?

How many starts in the red circle?

How many starts in the red circle?

In 2002-2004, Hubble telescope zoomed in this region and found, in this seemingly empty space, there are not 10 stars, 1000 stars, but at least 3,000 galaxies each with hundreds of billions of stars!

There are 3 thousand galaxies with trillions of stars

There are 3 thousand galaxies with trillions of stars

What do we know about the universe?

Author: Xu Cui Categories: opinion, writing Tags:

What is reality?

September 9th, 2017

David Eagleman was my co-advisor during my Ph.D study in Baylor College of Medicine. He produced a documentary movie last year with BBS addressing an important question “What is reality?” based on advances in neuroscience. I personally find it eye-opening and provoke deeper thinking of our own existence.

Here is the video:

Author: Xu Cui Categories: brain Tags:

[Tool] How To Convert Image To Text (OCR)

September 9th, 2017

You are reading a book or article online, and want to copy/paste a few sentences. But then you realize the book or article prevents you to copy, or maybe the book/article is an image. Instead of typing the sentences, you can use a tool to automatically recognize texts in image and convert for you.

“structurise” is such a tool. Unlike other online tools, you can paste your image into structurise directly, instead of saving the image to a file and uploading it. So it really make your workflow fast:

http://www.structurise.com/screenshot-ocr/

A short demo recorded by myself (in Chinese)

Author: Xu Cui Categories: web, writing Tags:

3 ways to check NIRS data quality

August 31st, 2017

Before performing any data analysis, we should check the data quality first. Below are 3 ways to do so.

1. Visual check of the time series

The best pattern detector is our eyes and brains! In many cases, if we visually see the data, we know what is wrong. You may use the method and program in this post to plot the time courses of all channels (not just one).

Visual data quality check of NIRS time courses

Visual data quality check of NIRS time courses

In the plot above, all 48 channels are plotted together (the y-axis). We can clearly see two types of noise:

  1. The spikes which occur in most channels after time point 7000. These spikes are caused by head motion.
  2. The high noise level in the “red” channels (channels 39, 34, 31). This is more evident if we plot the variance of each channel (figure below). As we can easily see, the variance of channels 39, 34 and 31 is much higher than other channels.

    Variance vs Channel

    Variance vs Channel

2. Existence of the “heart-beat” band

If the NIRS signal was acquired well, then the heart beating signal should be captured, leaving a bright brand in the frequency ~1Hz in the wavelet transform plot, just like the left plot in the figure below (the band close to period 8). If there is no such band, it does not necessarily mean the signal is trash, but you need to be cautious. To use the wavelet transform toolbox, please download here: http://www.alivelearn.net/?p=1561


NIRS wavelet

NIRS wavelet

Example:
figure;wt(hbo(:,1))

3. Correlation between hbo and hbr

The third way is to check the correlation between hbo and hbr. They are supposed to have negative correlation, at least in young healthy subjects. If not, or if they have perfect negative correlation (-1), then they might contain too much noise. We have a separate article on this method. Please check out http://www.alivelearn.net/?p=1767

Correlation between oxy and deoxy-Hb

Correlation between oxy and deoxy-Hb

Below is the scripts used for the 3 methods.

[hbo,hbr,mark]=readHitachData('SA06_MES_Probe1.csv');

figure;plotTraces(hbr,1:52,mark)

figure;wt(hbo(:,1))

for ii=1:52; wt(hbo(:,ii)); pause; end

[badchannels] = checkDataQuality(hbo,hbr);

Do you have other ways to check data quality? Please let me know!

Author: Xu Cui Categories: brain, nirs Tags:

[培训信息] 第一届近红外脑功能数据处理培训班 NIRS training course in China

August 23rd, 2017

重庆思影科技有限公司将于2017年10月16日– 2017年10月18日(周一至周三)举办第一届近红外脑功能数据处理培训班(详见课表安排)。欢迎大家前来咨询。

培训班依然坚持小班教学,手把手带教的教学模式,争取使每一位参加培训的学员能够在近红外脑功能数据处理方法上取得进步。

1、培训简介

功能性近红外光谱技术(functionalnear-infrared spectroscopy, fNIRS)技术是一项利用近红外光穿过皮层组织时的衰减程度定量化地测量大脑局部氧合血红蛋白和脱氧血红蛋白浓度变化的技术。该技术相对fMRI和PET等技术具有更高的时间分辨率(最高可达数十Hz)、便捷性高等优点;相对EEG/ERP技术具有相对更高的空间分辨率。该技术自问世以来,在基础研究、工程与临床实践中有广泛的应用,而且其普及性仍在增长。使用该技术的专业领域涉及心理学、医学、神经科学、脑机接口、运动科学和教育学等。

fNIRS信号的数据处理与fMRI和EEG/ERP等相比既有很多相同点也有很多其独有的方法。准确掌握fNIRS相关数据处理技能对于我们设计fNIRS实验、分析fNIRS数据至关重要。由于fNIRS技术专业性较强,需要系统的培训才能掌握,因此,我们拟举办fNIRS信号数据处理分析培训班,本培训班将在实验设计、数据分析方法原理以及常用开源软件操作等方面对学员展开系统培训,旨在帮助刚刚接触fNIRS技术的人员,如心理、运动科学、生物医学工程等专业研究生,精神、神经内外科、康复科、儿科等医生或临床科研人员及快速了解本领域及掌握fNIRS实验设计及编程、数据处理及分析的相关方法。

2、培训对象

本次培训班面向的对象是一些希望利用近红外技术进行科研和临床研究的医生、研究人员等,为了使数据处理不再成为脑科学研究的拦路虎,培训班实行小范围的理论与实践相结合,授课、操作、指导及问题解决一体化,最终达到独立操作。

培训内容主要包括:fNIRS基本原理及实验设计,SPM 操作及批处理流程,多人脑间功能连接数据分析原理,Homer软件数据处理基础,Homer软件数据处理进阶。

注:如方便,请于会议开始前一天到达会场(9:00 - 20:00)熟悉场地及安装软件、拷贝资料等事宜。

课程安排:

时间

课程名

主要内容

第一天

胡志善

10月16日

上午

fNIRS基本原理及实验设计

-fNRIS成像原理简介

-Block与Event实验设计及其变式

-fNIRS原始数据结构简介

-fNIRS设备信号调试技巧(根据授课进度穿插)

下午

SPM 操作及批处理流程

-NIRS SPM GUI界面介绍

-数据转换(data conversion)

-通过GUI界面逐步处理过程(含数据转换conversion、选择GLM所需参数、滤波filter、去漂移detrending等)

-通过脚本文件编写批处理程序

-数据结果的解释

第二天

张明明

10月17号

上午

多人脑间功能连接

数据分析原理

-傅里叶变换及小波分析原理

-小波相干分析原理

-格兰杰因果分析原理

下午

多人脑间功能连接

数据分析操作

-小波相干分析个体操作

-小波相干分析批处理操作

-格兰杰因果分析操作

第三天

王乾东

10月18日

上午

Homer软件数据处理基础

-NIRS一般数据处理步骤介绍

-Homer软件介绍

-通过Homer软件的GUI界面处理数据

下午

Homer软件数据处理进阶

-Matlab编程快速入门

-了解Homer处理的数据的结构与含义

-编写Matlab脚本更加自由地处理NIRS数据

4、培训人数

为保证培训质量,此次培训限定人数20人左右,报名敬请从速。

5、培训地点

重庆市渝中区青年路38号重庆国贸中心2004#,具体见会议指南。

6、培训费用

所有参会人员2000/人(含资料费、培训费和午餐费,交通及住宿费自理)。

7、报名方式

请将报名回执发送至:syfmri@163.com。

8、缴费方式

银行转账或者支付宝(18580429226,户名:杨晓飞),不接受现场缴费,谢绝录像,主办方提供发票。

9、联系方式

联系人:彭庭烨。电话:023-63084468/15123187262。

10、备注

请各位培训学员自带笔记本电脑(windows 64位系统、i3、4G内存等基本配置);学员自己有数据的可以带3-5例进行现场处理;并在10月1日前进行缴费及将回执表发给彭小姐,便于培训安排。

报名回执表

单位名称

(发票抬头)

姓名

性别

QQ

电话号码

科室/专业

缴费方式

□转帐  □支付宝 (请选择在□打√)

银行信息

户名:重庆思影科技有限公司

账号:123909127710102

开户银行:招商银行重庆分行渝中支行

汇款备注

第一届近红外脑功能数据处理培训班

注:请完整填写回执表后回传给我们,以便给你发送确认函,谢谢支持!

11、在线支持服务

参加培训学员将得到在线技术支持服务,伴随参加培训班的学员共同成长。

12、培训人员简介:

胡志善,澳门大学博士研究生。在心理科学进展及JECP各发文一篇。专注于使用fNIRS进行认知神经方面的研究,有近5年fNIRS的实验设计、执行及数据分析经验。能够熟练运用Python进行fNIRS的实验编程,使用NIRSport 及 CW6 等设备进行认知方面的研究,已完成决策、说谎、执行功能、数字计算、语言、运动等认知功能等多项实验;能够熟练运用NIRS SPM 及 Homer2 进行数据分析,并能够熟练运用MATLAB进行数据的批处理,代码风格良好。

张明明,博士研究生。东南大学神经信息工程专业在读博士研究生。目前研究方向为近红外超扫描(hyperscanning)技术支持下的多人社会交互行为研究,擅长多人社会互动中的近红外数据分析,做过多个近红外实验具有丰富数据分析经验。已在相关领域学术杂志期刊发表学术论文若干,其中SCI收录学术论文2篇。

王乾东,北京大学前沿交叉学科研究院在读博士研究生。目前研究主要采用近红外、眼动、多导生理和行为技术探究自闭症儿童的认知发展。能够熟练运用Matlab进行近红外和眼动的实验编程及数据处理。目前正进行一项多模态的实验(同时采集近红外、眼动和多道生理仪的数据)。已有多篇文章发表在国外SCI以及国内权威和一级心理学期刊上。

Author: Xu Cui Categories: nirs Tags: