期待张师兄贴出一些关于ica的知识

Hi, I learn that we can input FunImgARWS images in ICA analysis using MICA, but I also read that some studies applied detrend and filter to the FunImgARWS images before inputting the preprocessed images into ICA. Does it matter much between the choice of preprocessed images (FunImgARWS or FunImgARWSDF) for ICA? Thanks!

 Hi!
I have a question regarding ICA.
I'm using the fastICA algorithm and I have this problem. My two dependent variables, say X1 and X2 are mixtures of one common non gaussian variable T and two gaussian error terms. My algorithm is able to recover the signal T (I did a lot of simulations), but I want to prove it theoretically. Do you have any suggestion?

My model can be written as:
X1=T+E1
X2=T+E2

where T is non gaussian, E1 and E2 are gaussian and the three variables (T, E1 and E2) are independent.

Thank you in advance for your help

 Hi, Dr. Zhang,

I have a question about ICA. Is it reasonable to perform ICA in follow-up study, since a subject's data at baseline and follow-up time are interelated each other。

Best Wish！

我在使用mica的时候，在成分挑选的时候，gui view界面中点击sort components，并且选择空间相关并加载了需要的DMN网络模板，点击ok之后，软件没有任何反应，
问题1：恳请张寒老师指导一下，mica中sort components的使用。
问题2：identify components在使用默认的设置，全部勾选，点击ok，matlaB就会报错，请问identify components的作用以及他的使用方法。
Idendentify components
??? Undefined function or variable 'dim'.

Error in ==> view_gui>ButtIdenComp_Callback at 898
[ICNOs]=nic_removeNoiseComponent(compNum,dim,outPrefix,threshold,zipFilePath,a);

Error in ==> gui_mainfcn at 96
        feval(varargin{:});

Error in ==> view_gui at 30
    gui_mainfcn(gui_State, varargin{:});
 
??? Error while evaluating uicontrol Callback

老师好:
    关于独立成分分析还是有些地方不明白,在成分提取之后,如何对已提取的成分进行筛选,看文章里面说筛选步骤主要分两步,(1)首先由于背侧注意网络的频带属于低频段(0.01－0.1Hz)，分析各个独立成分对应的时间序列的功率谱，如果高频信号(>0.1Hz)占该独立成分的功率谱 50％以上，则去除该成分.功率图谱是怎么看的呢？？？（2）然后在剩余的成分中用一个模板匹配程序选择与背侧注意网络模板最匹配的成分，该模板匹配程序主要是计算每个成分中落在模板内体素的 z 值的平均值与模板外体素的 z 值的均值之差，定义为拟合度值(goodness-of-fit scores)，选择拟合度值最大的成分作为最匹配(best-fit)的成分，即可认为该成分是背侧注意网络。请问老师，这两步具体是怎么实现的呢？？希望能得到老师指点…………

Hi,

I'm trying to use ICA to denoise an EEG recording, but first I checked how ICA works.
I tried decomposing a sin + sawtooth + white noise, which works wonderful. But when I added the same signals with delays it stopped working (according with my readings that's Time Embedded Data, which should improve the performance). The same result when I repeated the inputs varying only amplitudes (without any delay). Am I doing something wrong?

I attached a piece of code down here to illustrate my problem.

N = 5000;
Fs = 500;
t = (0:(N-1))/Fs;

% 3 independent signals
a = sin(t*2*pi);
b = sawtooth(t*2*pi*5);
c = rand(1,N);

% 3 signal built mixing linearly the independent signals
x1 = zeros(N,3);
x1(:,1) = rand*a+rand*b+rand*c;
x1(:,2) = rand*a+rand*b+rand*c;
x1(:,3) = rand*a+rand*b+rand*c;
% a bigger set of signal usign x1 with delays
delay = 5;
x2 = x1(delay*1:end,:);
x3 = x1(delay*2:end,:);
x4 = x1(delay*3:end,:);
x5 = x1(delay*4:end,:);
Lm = length(x5);
x = [x1(1:Lm,:) x2(1:Lm,:) x3(1:Lm,:) x4(1:Lm,:) x5];
x = x';

[Y,W,P] = ica(x);

Thanks!

MATLAB运行mica第一次报错如下：

 Exception occured. (MATLAB:innerdim)

 STARTING DATA REDUCTION (PRINCIPAL COMPONENTS ANALYSIS)

关于ICA算法的问题

    老师您好，看了calhoun的2001年（A Method for Making Group Inferences from

Component Analysis）和2009年的文章（A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic,
and ERP data），有如下几个问题：
1.我的理解是对于每个个体group ICA GIFT软件back reconstruct 出来的同一个成分的map是不一样的，但是同一个成分的time course 是一样的并且和整个group的是一样的。我的理解对吗？老师

2. 2009年的文章中说time concatenation时是这样说的：The temporal concatenation approach allows for

请教张老师，ICA分离出来的不同成分（默认网络、中央执行网络、额顶网络等等），有比较一致的模板吗？多谢！

大家好，
我是一名MICA的初级使用者，通过论坛我学会了一部分的操作。但是在run后出现了这样的错误。这是什么导致的呢？
有人能发我一份默认网络、运动网络、执行控制网络、记忆网络这四个网络的模板吗？（我想通过MICA提取出这四个网络的体空间和时间序列）
谢谢！
......................................
Group ICA Error Information:

Error using nic_spm_write_vol (line 20)

Inic_ompatible dimensions.

Error in ==> nic_spm_write_vol at 20

Error in ==> nic_write_vol at 37

Error in ==> nic_icatb_saveICAData at 117

Error in ==> nic_rsdd_groupStats at 178

Error in ==> nic_rsdd_runAnalysis at 201

Error in ==> RulAll_Callback at 473

Error in ==> gui_mainfcn at 96

Error in ==> moica_gui at 57

......................................

Exception occured. ()

Error using icatb_displayErrorMsg (line 23)

23#line, icatb_displayErrorMsg, in "E:\MICA\MICA_beta1.22_20120523\nic_functions\nic_icatb_helper_functions\icatb_displayErrorMsg.m"

44#line, nic_write_vol, in "E:\MICA\MICA_beta1.22_20120523\nic_functions\nic_spm5_files\nic_write_vol.m"

117#line, nic_icatb_saveICAData, in "E:\MICA\MICA_beta1.22_20120523\nic_functions\nic_icatb_saveICAData.m"

178#line, nic_rsdd_groupStats, in "E:\MICA\MICA_beta1.22_20120523\nic_rsdd_groupStats.m"

201#line, nic_rsdd_runAnalysis, in "E:\MICA\MICA_beta1.22_20120523\nic_rsdd_runAnalysis.m"

473#line, RulAll_Callback, in "E:\MICA\MICA_beta1.22_20120523\moica_gui.m"

96#line, gui_mainfcn, in "D:\matlab2012a_install\toolbox\matlab\guide\gui_mainfcn.m"

57#line, moica_gui, in "E:\MICA\MICA_beta1.22_20120523\moica_gui.m"

Error using fileparts

Too many output arguments.

Error in nic_rsdd_misc (line 15)

[pathstr, name, ext, versn] = fileparts(mfilename('fullpath'));

Error in view_gui>view_gui_OpeningFcn (line 76)

set(handles.templateFile,'String',fullfile(nic_rsdd_misc('WhereIs'),'template','nsingle_subj_T1_2_2_5.nii'));

Error in gui_mainfcn (line 221)

feval(gui_State.gui_OpeningFcn, gui_hFigure, [], guidata(gui_hFigure), varargin{:});

Error in view_gui (line 30)

gui_mainfcn(gui_State, varargin{:});

Error in moica_gui>guiView_Callback (line 656)

view_gui(handles.moicaCfg);

Error in gui_mainfcn (line 96)

feval(varargin{:});

Error in moica_gui (line 57)

gui_mainfcn(gui_State, varargin{:});

Error while evaluating uicontrol Callback

张老师你好，我最近想做ADHD_index评分跟ICA之后两组样本差异脑区的相关分析，我提取了八个静息态网络，然后做了双样本t检验（多重比较校正),我用这个作为提取roi的mask，然后把两组人放在同一个文件夹下提取roi时间信号，这样做对吗？非常希望您能帮我解答这个问题。