Archive for the ‘brain’ Category

Communications between two MatLabs (1) over file

October 3rd, 2016

Ref to: Communications between two MatLabs (2): over socket

It’s common that two MatLab programs needs to communicate. For instance, one program is collecting the brain imaging data but not display them, and the other program is to display the data. (Another case is at Sometimes it is not practical to merge the two program together (e.g. to keep the code clean). In this case we can run two MatLabs simultaneously. One keeps saving the data to a file, and the other keep reading the file.

Here I played with such a setup, and find they communicate well with small delay (small enough for hemodynamic responses). Check out the video below:


for ii=1:100
    disp(['write ' num2str(ii)])

last_ii = 0;
        load data
        if(ii ~= last_ii)
            disp(['get data. i=' num2str(ii)])
        last_ii = ii;

Caveat: writing/reading to/from disc is slow. So if your experiment requires real time communication without any delay (say <1ms), this method may not work. Also, the amount of data to write/read each time should be very small, and the frequency of write should be small too. The file needs to locate in your local hard drive instead of a network drive.

———- Comments ———–
Paul Mazaika from Stanford:
Cool piece of code! There may be a way to do this with one umbrella Matlab program that calls both components as subroutines. The potential advantage is that one program will keep memory in cache, not at disk, which can support rapidly updating information. For high speeds, it may be better to only occasionally update the graphical display, which otherwise may be a processing bottleneck.

Aaron Piccirilli from Stanford:
There is, sort’ve! I think Xu’s little nugget is probably best choice for many applications, but if speed is an especially big concern then there are a couple of options that I’ve come across that will maintain some sort of shared memory.

Perhaps the easiest is to use sockets to communicate data, via UDP or TCP/IP, just like you use over the internet, but locally. You write some data to a socket in one program, and read it from that same socket in another program. This keeps all of your data in memory as opposed to writing it to disk, but there is definitely some overhead for housekeeping and to move the data from one program’s memory into the operating system’s memory then back into the other program’s memory. An added bonus here: you can communicate between different languages. If you have a logging function written in Python and a visualization program in MATLAB, they can pretty easily communicate with each other via sockets.

MATLAB doesn’t have explicit parallel computing built-in like many other languages, sadly, but we all have access here to the Parallel Computing Toolbox, which is another option for some more heavy-duty parallel processing where you have a problem you can easily distribute to multiple workers.

Finally, true shared memory might be more trouble than it’s worth for most applications, as you then have to deal with potential race conditions of accessing the same resource at the same time.


More on this topic: Please continue to read Communications between two MatLabs (2): over socket

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


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:

fNIRS 2016

June 6th, 2016

fNIRS 2016 conference will be held in Paris, October 13 – 16, Université Paris Descartes, 12 rue de l’Ecole de Médecine, Paris 75006, FRANCE

Check out the society’s home page:

The 2016 conference will take place in central Paris, October 13 – 16, 2016.

As with past meetings, there will be a day-long course prior to the start of the conference, on Thursday, October 13.

The conference is co-chaired by Judit Gervain and Joseph Culver.

Maria Angela Franceschini (MGH, Harvard Medical School, Boston, USA) – Keynote
Sol Diamond (Dartmouth College, USA)
Frédéric Dehais (ISAE, Toulouse, France)
Ursula Wolf (Bern University, Switzerland)
Frédéric Lesage (McGill University, Canada)
Gorm Greisen (University of Copenhagen, Danemark)
Yasuyo Minagawa (Keio University, Japan)
Ippeita Dan (Jichi Med. University, Japan)
Chuck Nelson (BCH, Harvard Medical School, Boston, USA)

Abstract submission opens: May 1st, 2016
Abstract submission ends: June 10th, 2016 (midnight GMT)
Notification to authors: Late July 2016
Early registration ends: Sept 10th, 2016

Author: Xu Cui Categories: nirs Tags:

Who cited my paper?

May 9th, 2016

Back in 2010 we published a paper titled “Functional Near Infrared Spectroscopy (NIRS) signal improvement based on negative correlation between oxygenated and deoxygenated hemoglobin dynamics“. It is about a really simple method which surprisingly works well in reducing motion artifact (noise) in NIRS data. As of today (2016-05-09), the paper has been cited by more than 130 times.

Who cited this paper? Well, we created this map to show where the authors are:

If you clicks the red dots you will find the detailed information about the paper, such as the author name and journal.

Then who are the top researchers who cited this paper? We count the number of citation for each author, and rank them by the number of papers. Here are the top authors who cited our 2010 paper:

Author Number of Papers
Fallgatter, AJ 9
Ehlis, AC 8
Hong, KS 8
Dresler, T 8
Herrmann, MJ 7
Scheutz, M 6
Strait, M 5
Boas, DA 5
Sato, H 4
Scholkmann, F 4
Herff, C 4
Seghouane, AK 4
Ge, SS 4
Shah, A 4
Katura, T 4
Molavi, B 4
Wolf, M 4
Author: Xu Cui Categories: brain, nirs, programming Tags:

NIRS manufactures locations

May 4th, 2016

Where are the major NIRS device manufactures? You can see from the map below.

There are NIRS manufactures in US, Japan, Europe and Korea.

If you are a NIRS manufacture and would like to add to this list, please let me know (leave a comment in this post).
If you are interested in creating a map like this, please let me know (leave a comment in this post).

Related: NIRS manufactures products

Author: Xu Cui Categories: brain, nirs Tags: