Postdoc position available in our lab at Stanford

August 24th, 2016

Our lab is hiring a “sports neuroscience postdoc”. See the detail below. If you are interested, please contact Reiko Riley (mentioning that you heard about this position from Xu’s blog):


A sports neuroscience postdoctoral fellowship is available in the Division of Interdisciplinary Brain Sciences (CIBSR), Stanford University School of Medicine Department of Psychiatry, to study the neurobiology of cycling-based exercise using functional near-infrared spectroscopy (fNIRS).

The postdoctoral fellow will have the opportunity to develop and contribute to an innovative project in sports neuroscience, investigating the contribution of cycling exercise to brain function and cognition. The fellow will be involved in the development of a cycling exercise program protocol, brain-computer interfaces and computational methods to process and analyze data across multiple scientific levels. Successful candidates will have the opportunity to investigate whether cycling exercise can be used as a tool to improve attention in individuals with cognitive dysfunction such as ADHD, and the utility and feasibility of biometric tools to complement fNIRS. The trainee accepted into the program will work collaboratively with a program mentor (or mentors), who will help to define, enhance and monitor the trainee’s research program and career trajectory. The CIBSR team dedicated to fNIRS research includes Drs. Allan Reiss (CIBSR Director, Clinical Neuroscience and Neuropsychiatry), Hadi Hosseini and Ning Liu (Bioengineering), Jennifer Bruno (Developmental Neuropsychology), Manish Saggar and Xu Cui (Computational Neuroscience), and Joseph Baker (Experimental Psychology). The training program also offers didactic courses and activities (e.g., journal club and career lunches) as well as opportunities for diverse industry and academic collaborations to promote professional development. The Stanford School of Medicine is ranked #2 in the U.S. News & World Report rankings, with the highest NIH-funding-per-faculty ratio in the United States.

Requirements: M.D. or Ph.D. in neuroscience, cognitive science, computer science, biomedical engineering, biostatistics, physics, psychology, kinesiology or a related/relevant field. Applicants should have (or anticipate having) a Ph.D. and research background in computational neuroscience, cognitive neuroscience and/or functional brain imaging. Applicants with experience conducting Near Infrared Spectroscopy studies and data analysis procedures will receive preference. Experience in sports neuroscience is also a plus. Responsibilities will include manuscript preparation and grant preparation. The successful applicant will have well-developed problem solving skills, be able to manage several projects simultaneously, lead and mentor students and research assistants, have excellent computing as well as verbal and written English skills, and an aptitude for writing manuscripts and giving scientific presentations.

Application Materials Required - submit via email to our training coordinator Reiko Riley (

Current CV
Post Doctoral Application (link:
Research Statement (description on page 2 of the application form below)
2 - 3 Letters of Reference

Official announcement link:

Author: Xu Cui Categories: life Tags:


August 11th, 2016



1. 我的导师是否有经费?
2. 我在寻找博后的职位;我未来的老板是否有足够的经费支持我?
3. 有多少经费拨给了我的研究领域(比如NIRS)?谁得到了这些经费?他们将用这些经费做什么?



Stork 就是这样一个工具。

我在Stork里输入如下关键字,“pearl chiu”(我之前同事的名字)以及“NIRS brain”(我的研究领域)。以下是Stork发给我的邮件:

Stork notifies me of awarded grants


有了Stork提供的信息,我了解了在我的研究领域,谁得到了经费以及他们打算用这笔经费做什么研究。实际上邮件里的第三个基金是拨给我的同事Manish, 用于他进行利用NIRS对静息状态下的脑回路的研究。我还看到Pearl得到了很大一笔经费,所以我给她发送了一封祝贺邮件。与Stork的另一个功能论文提醒比起来,经费提醒让我更早的对自己研究领域的趋势了如指掌。得到经费支持的研究,通常需要几年之后才有相关论文发表出来。


Author: Xu Cui Categories: brain, programming, web, writing Tags:

A mistake in my False discovery rate (FDR) correction script

August 8th, 2016

I have posted an FDR script at I noticed that there is a small bug. In rare cases, this bug will cause the most significant voxel to be classified as ‘non-significant’ while other voxels are ’significant’.

Consider the following example:

p = [0.8147 0.9058 0.0030 0.9134 0.6324 0.0029 0.2785 0.5469 0.9575 0.9649 0.1576 0.9706 0.9572 0.4854 0.8003 0.1419 0.4218 0.9157];

The previous script will classify p(3) as significant but p(6) as non-significant.

Here is the updated version of the script:

function y = fdr0(p, q)
% y = fdr0(p, q)
% to calculate whether a pvalue survive FDR corrected q
% p: an array of p values. (e.g. p values for each channel)
% q: desired FDR threshold (typically 0.05)
% y: an array of the same size with p with only two possible values. 0
% means this position (channel) does not survive the threshold, 1 mean it
% survives
% Ref:
% Genovese et al. (2002). Thresholding statistical maps in functional
% neuroimaging using the false discovery rate. Neuroimage, 15:722-786.
% Example:
%   y = fdr0(rand(10,1),0.5);
% Xu Cui
% 2016/3/14

pvalue = p;
y = 0 * p;

[sortedpvalue, sortedposition] = sort(pvalue);
v = length(sortedposition);
for ii=1:v
    if q*ii/v >= sortedpvalue(ii)
        y(sortedposition(1:ii)) = 1;

Author: Xu Cui Categories: brain, matlab, nirs, programming Tags:

Remote Desktops

July 25th, 2016

I have quite a few devices now: one computer (PC) at Stanford, one (PC) at home, one Macbook Pro laptop, one iPhone and iPad. I am sometimes at work, sometime home, sometimes travelling, sometimes meeting people. One thing I always want to achieve is to be able to access the computers from anywhere.

I did some research and Google’s Chrome Remote Desktop is a good choice. It is also free. It is a plugin of Chrome browser. For iphone/iPad, Google also offers an app. I installed Chrome Remote Desktop on all my devices, and now I can access any computer from any other devices.

remote desktop

remote desktop

This is what I hoped for - a full connection. But at this particular moment I can’t use the home computer to remote others. I got the famous “some required components are missing” error and don’t know how to solve it. If you know a solution, please let me know.

Author: Xu Cui Categories: life Tags:

3 monitors

July 18th, 2016

To be more “productive”, I recently upgraded my work space. I used to have 2 monitors side by side. Both of them are View Sonic but they are of different size and one is old. So I purchased two monitors (Dell U2415). Together with one original View Sonic monitor, now I get 3 monitors on my desk.

3 monitors

3 monitors

The left one is the original view sonic one with resolution 1920 x 1080. I make it vertical because I write a lot of codes and a vertical placement allows me see more lines of codes at the same time. So this monitor is almost dedicated to writing codes.

The right two are Dell U2415 with resolution 1920 x 1200. According to some people, “Dell UltraSharp series is a gold standard in excellence which programmers have used and loved for years”. I myself do love it a lot. These monitors have a very thin bezel, which is ideal for side-by-side placement. I use the middle screen for the current job (Excel, browsing etc), and the right screen for supportive function (e.g. wechat, FileZilla, QQ, windows explorer etc).

Of course, to make the 3 monitor setup possible, I need a trip-monitor stand. The one I use is SIIG 13″-27″ Articulated Freestanding Triple Monitor Desk Stand. It does an OK job. One of the reason I chose it because it does not need a grommet. I am using varidesk and there is not much space under the table.

Overall, I like the 3 monitors a lot. I do feel I am more “productive” :)

Author: Xu Cui Categories: life, technology Tags:

MatLab tip, save data in compressed mode

June 29th, 2016

I have a mat file which is 100+M in size. It would be fine normally but since I was trying to upload it to github, it was rejected due to its big size. Fortunately there is a way to reduce the size: save it again in the compressed mode.

After I load the file, I save the variable again using the following command:

save filename variablename -v7

The parameter -v7 is the key. How does the compression perform? Originally the file (render_ch2bet) size is 103M, with -v7 parameter the file is 40.9M (render_ch2bet_compressed). By comparison, if we compress the original file using a third party program, we got ~40M ( If we use the -v7 option, not only we get a much smaller file and save a lot of space, we can also load it directly in MatLab.

Compressed MAT file

Author: Xu Cui Categories: matlab Tags:


June 27th, 2016

Manish Saggar in our lab brought something very cool - a helmet like EEG system. He called it “dry” EEG because it does not requite gel. The design is not polished, but it’s cheap, like $800. And it does not need long wires to transmit the signal to a computer, which is pretty nice. This product is manufactured by OpenBCI, an open source community.


Manish Saggar

I decided to give it a try and borrowed the device from Manish.

Wearing OpenBCI Biosensing Headset

Wearing OpenBCI Biosensing Headset

The headset does not fit my head perfectly, leaving most channels in the front untouched with my head. It’s also not comfortable to wear for a long time; the material is hard and exert a lot of pressure on my head. But it’s wireless and we can collect the data and display the signal on screen in real time. This part is cool.

To collect data, we need two pieces of software and a USB dongle.

USB dongle

USB dongle

First, let’s download the dongle driver. The driver of the dongle can be found at Since I am using Windows 7, I download the Windows executable setup version. You can download the file ( directly from Then unzip and install it.

Then, let’s plugin the dongle into a USB. Make sure you plug it the right way. If you do, the dongle will emit blue lights. I did it wrong in the first place and have to reverse the side and try again.

We also need to download the OpenBCI software which can collect and visualize the data in real time. You can download it at I downloaded the Windows 64bit version.

Now it is time to play with it. First let’s open OpenBCI software.



The dongle acts as COM3 port on my computer, so I select COM3. I also switch my headset power on. Then I click “START SYSTEM”.



At this time I click the round “head” bring up the signal panel. Then I click “Start data stream” to collect the data. The figure below shows my brain wave in real time!

OpenBCI data collection

OpenBCI data collection

So far it’s all impressive. The setup is easy. But the question is if the signal is reliable. What we found is that it’s highly motion sensitive. If I move my head, or blink my eye, the signal will change. At this point, I hesitate to draw any conclusion on the quality of the signal.

In the past few years a number of companies have produced consumer-use brain signal recording devices. Check out this list in wikipedia. A few NIRS companies (e.g. Hitachi) are also working on a consumer NIRS device. There is no doubt that we will have a reliable personal brain sensor in the near future.

Author: Xu Cui Categories: brain Tags:

Some tips to use wavelet toolbox

June 13th, 2016

Wavelet toolbox is a useful tool to study hyperscanning data. Many recent publications on NIRS hyperscanning use wavelet coherence to quantify the relationship between two interacting brains (e.g. Baker et al 2016, Nozawa et al 2016). You can see more information about wavelet coherence at



Here are some tips to use the toolbox:

1. It often takes a long time to run Monte Carlo simulation. You may use ‘mcc’=0 to disable it.


2. If you need to get the values of the result (instead of the graphic), you may specify the return value

[Rsq,period,scale,coi,sig95] = wtc(signal1,signal2,'mcc',0); %Rsq is a complex matrix

3. If you are only interested in a certain band, you can specify the MaxScale (i.e. ms) parameter. More information at

[Rsq,period,scale,coi,sig95] = wtc(signal1,signal2,'mcc',0, 'ms', 128);

4. If you are interested in finding the “phase” information (visualized by the arrows), you may use xwt function. The returned value is a complex matrix and you can calculate the phase.

[Rsq,period,scale,coi,sig95] = xwt(signal(:,jj),signal(:,jj+22));

5. To visualize the power of a single signal, you may use wt, which I personally feel much better than FFT.


6. To change the density of the arrows, you may specify the ArrowDensity parameter

figure;wtc(signal(:,jj),signal(:,jj+22),'mcc',0,'ArrowDensity',[30 30]);

Do you have any tips? Please let me know.

Author: Xu Cui Categories: brain, matlab, nirs, programming Tags:

Just published a paper: Men vs Women, are they different in cooperation?

June 13th, 2016

We just published a big and long study. It is a NIRS hyperscanning study aiming to investigate the brain difference between men and women during cooperation. We have scanned 222 people! And it is one of the largest NIRS study I have seen. And it is a long study. The project started in 2012 (today is 2016/6/13). You can imagine how long it took to collect and analyze the data, and to get the paper published!

After a series of rejections (Nature -> Journal of Neuroscience -> PNAS -> NeuroImage), this paper was finally published in Scientific Reports this month (2016/06). The full-text of this paper is accessible via PubMed Central.

A cooperation game

Two lab members are playing the cooperation game

After the paper was published, it has attracted a lot of media attention. For example, Stanford news center has reported “Study finds differences in male, female brain activity when it comes to cooperation” (below).

Stanford News Center

Stanford News Center

Two major contributors of this study are Ning Liu and Joe Baker.

Ning Liu

Ning Liu

Joe Baker

Joe Baker

Author: Xu Cui Categories: brain, nirs Tags:

Hitachi ETG4000 on ebay, for less than $10,000

June 6th, 2016

In our lab meeting today we accidentally discovered that you can actually purchase a used ETG4000 on ebay! The seller asked for $9,995. When we purchased ETG4000 back in 2007, it costed us about half million!

Check it out:

Author: Xu Cui Categories: brain, nirs Tags: