ReHo and Temporal Dynamic Analysis

Dear colleagues,

Thank you for your work giving me an opportunity to explore the mysterious human brain. I am a student major in medicine and not good at mathematics. I have some questions that maybe silly and look forward to your answers.

1. ReHo assumes that a given voxel is temporally similar to that of its neighbors and uses KCC to measure the similarity of the time series of a given voxel to those of its nearest neighbors in a voxel-wise way (Zang et al., 2004). And Zou (Qihong Zou et al.,2009) summarized that ReHo reflects local synchrony by calculating similarity of dynamic fluctuations of voxels within a given cluster. I want to make sure whether temporal variation was taken into consideration or it just calculate the similarity of the mean time series of a given voxel to its nearest neighbors. If temporal variation was considered, what is the improvement of dynamic ReHo in the new module for Temporal Dynamic Analysis in DPABI_V3.0_171210?

2. I tried the TDA and got results including two folders (TemporalDynamics4D and TemporalDynamicsMetrics). I used to ask for advice, and Dr.Yan said CV*.nii and Std*.nii can be sort out for subsequent statistical analyses. Dr.Yan also said CV*.nii and Std*.nii make different significance. It is difficult for me to understand their significance and could you please give some clues or suggest some literatures?

Thanks for your patience.

Best wishes.


Daihong Liu



Please read Yan, C.-G., Yang, Z., Colcombe, S.J., Zuo, X.-N., Milham, M.P., 2017. Concordance among indices of intrinsic brain function: insights from inter-individual variation and temporal dynamics. Sci Bull 62, 1572-1584.