Hi,

Is there a way to visualize the functional connectivity maps on a individual basis in SPM?  I know I can do second-level group analyses, but I am interested in looking at functional connectivity on an individual basis.  Any advice would be helpful.  Thanks.

Duke

Dear all:
I'm a beginner using SPM and resting fMRI. I tried to preprocessed my data using DPARSF, with normalization by using T1 image unified segmentation. My data preparation and directory were arranged  according to the online-course. However, DPARSF crashed immediately after finishing realignment  with the following error message.

Done    'Realign: Estimate & Reslice'
Done

??? Error using ==> copyfile
No matching files were found.

Error in ==> DPARSF_run at 310

Dear REST authors:

I am new to the fMRI and REST toolbox. There was an warning message when I tried to use rest_sliceviewer--'Warning: image_toolbox not valid'. Could you please clarify which image-toolbox referred here? And where can I get it? Thank you very much in advance!

Sincerely yours,

Yong Li, PhD

 
做Reho时发现报错，请老师看看是什么原因。

ReHo :"D:\IA\Analysis\FunImgNormalized\Sub_006_detrend_filtered"
??? Undefined command/function 'rest_misc'.

Error in ==> reho_gui>btnComputeReho_Callback at 337
   rest_misc( 'DisplayLastException');

Error in ==> gui_mainfcn at 75
        feval(varargin{:});

Error in ==> reho_gui at 34
    gui_mainfcn(gui_State, varargin{:});

??? Error while evaluating uicontrol Callback.
 

按照COURSE中讲述的方法提取协变量，发现报错，

>> RPCov=load('rp_aSub_001.txt');
>> BCWCov=load('ROI_FCMap_Sub_001.txt')'
>>Cov=[RPCov,BCWCov];
??? Error using ==> horzcat
All matrices on a row in the bracketed expression must have the
 same number of rows.

附件是头动文件和ROI文件，请老师看看是哪里出问题了

 Dear DPARSF developers, 

I am trying to run a test set of participants on using DPARSF and receive the following error: 

Dear Chao
I have a question regarding you program y_corr2p, that was very useful to me. I would like to know how the P value is calculated. All other algorithms I have been using use the mean(r) and std(r) across all subjects, but your code is independent of the number of subjects, only taking into account the number of time points in the series. I am curious about how it is calculated
best regards
Pablo

Dear Pablo,