Brain functional connectivity at rest as similarity of neuronal activities
The brain is a connected network, requiring complex-system measures to describe its organization principles. The normalized compression distance (NCD)  is a parameter -free, quasi universal similarity measure that estimates the information shared by two signals comparing the compression length of one signal given the other. Here, we aim at testing whether this new measure is a suitable quantifier of the functional connectivity between cortical regions.
In particular, we tested whether NCD between homologous hemispheric regions is smaller (higher connectivity) in the same person than across different people, if it is smaller in the dominant hemisphere and if it depends on age.
We used the Functional Source Separation (FSS)  algorithm on magnetoencephalographic (MEG) data in order to identify functionally homologous areas in the two hemispheres devoted to the somatosensory contra-lateral hand representation (FS_S1) in 28 healthy people. Therefore, we calculated NCD between the left and right FS_S1s activities at rest.
We found that NCD 1) between left and right FS_S1s of the same person was smaller than across different people (p<10-7consistently) 2) was smaller within the left dominant hemisphere than within the non dominant right one (p=3*10 7) and 3) became more variable in older than younger people (p=.01).
This preliminary work shows that NCD, which measures the similarity of neuronal source activities via their compression sizes, displays an excellent ability in quantifying the similarity among neuronal activities, catching the maximal similarity expected for functionally homologous cortical areas of the two hemispheres. Thus, NCD seems a good candidate for two-nodes functional connectivity measure in resting state, able to overcome the limitations intrinsic to the classical Fourier or autoregressive estimates in assessing dynamics properties of the brain connectivity.