ReHo measures fMRI BOLD signals' similarity (or accordance) among one voxel and its neighbouring voxels (in three dimension, 26 voxels). For each voxel, ReHo value can be calculated, therefore, we can get a "ReHo" brain, this is a local functional connectivity measurement. For details please refer to Zang et al., 2004, NeuroImage, "Regional homogeneity approach ..."
fALFF is a variation of ALFF. ALFF measures fMRI BOLD signals' fluctuation. In each voxel, there will be a BOLD time series, the amplitude of its fluctuation (or the variation of the fluctuation) in a certain frequency band (we usually use 0.01-0.08 Hz as its the main band for resting-state functional connectivity) produces ALFF. Therefore, fALFF measures the fluctuation characteristic for each voxel. Please see Zang et al., 2007, Brain & Development, "Altered baseline brain activity in children ..."
So far as I know, SPM uses "VOI" function to extract EVs. To use it, firstly you should get the spm result using "Result" in SPM, then, in the result view control window, you can find "VOI". In SPM 8 manual, search "VOI" you also can get the detailed answer. EVs is the first eigen vector obtained from Principle Component Analysis (PCA), basically, it is similar as the "weighted average". The first EV is often regarded as the "summary of the data".
So far as I know, SPM uses "VOI" function to extract EVs. To use it, firstly you should get the spm result using "Result" in SPM, then, in the result view control window, you can find "VOI". In SPM 8 manual, search "VOI" you also can get the detailed answer. EVs is the first eigen vector obtained from Principle Component Analysis (PCA), basically, it is similar as the "weighted average". The first EV is often regarded as the "summary of the data".
Submitted by Allwyn on Tue, 11/25/2014 - 23:44 Permalink
Re: SPM8，VBM的处理分析
can anyone pls tell me how ReHO differs from FALFF
Submitted by ZHANG_RESTadmin on Fri, 11/28/2014 - 18:28 Permalink
Re: SPM8，VBM的处理分析
ReHo measures fMRI BOLD signals' similarity (or accordance) among one voxel and its neighbouring voxels (in three dimension, 26 voxels). For each voxel, ReHo value can be calculated, therefore, we can get a "ReHo" brain, this is a local functional connectivity measurement. For details please refer to Zang et al., 2004, NeuroImage, "Regional homogeneity approach ..."
fALFF is a variation of ALFF. ALFF measures fMRI BOLD signals' fluctuation. In each voxel, there will be a BOLD time series, the amplitude of its fluctuation (or the variation of the fluctuation) in a certain frequency band (we usually use 0.01-0.08 Hz as its the main band for resting-state functional connectivity) produces ALFF. Therefore, fALFF measures the fluctuation characteristic for each voxel. Please see Zang et al., 2007, Brain & Development, "Altered baseline brain activity in children ..."
Submitted by ZHANG_RESTadmin on Fri, 11/28/2014 - 18:20 Permalink
Re: SPM8，VBM的处理分析
So far as I know, SPM uses "VOI" function to extract EVs. To use it, firstly you should get the spm result using "Result" in SPM, then, in the result view control window, you can find "VOI". In SPM 8 manual, search "VOI" you also can get the detailed answer. EVs is the first eigen vector obtained from Principle Component Analysis (PCA), basically, it is similar as the "weighted average". The first EV is often regarded as the "summary of the data".
Submitted by ZHANG_RESTadmin on Fri, 11/28/2014 - 18:21 Permalink
Re: SPM8，VBM的处理分析
So far as I know, SPM uses "VOI" function to extract EVs. To use it, firstly you should get the spm result using "Result" in SPM, then, in the result view control window, you can find "VOI". In SPM 8 manual, search "VOI" you also can get the detailed answer. EVs is the first eigen vector obtained from Principle Component Analysis (PCA), basically, it is similar as the "weighted average". The first EV is often regarded as the "summary of the data".