Linking human brain local activity fluctuations to structural and functional network architectures.

Abstract:

:Activity of cortical local neuronal populations fluctuates continuously, and a large proportion of these fluctuations are shared across populations of neurons. Here we seek organizational rules that link these two phenomena. Using neuronal activity, as identified by functional MRI (fMRI) and for a given voxel or brain region, we derive a single measure of full bandwidth brain-oxygenation-level-dependent (BOLD) fluctuations by calculating the slope, α, for the log-linear power spectrum. For the same voxel or region, we also measure the temporal coherence of its fluctuations to other voxels or regions, based on exceeding a given threshold, Θ, for zero lag correlation, establishing functional connectivity between pairs of neuronal populations. From resting state fMRI, we calculated whole-brain group-averaged maps for α and for functional connectivity. Both maps showed similar spatial organization, with a correlation coefficient of 0.75 between the two parameters across all brain voxels, as well as variability with hodology. A computational model replicated the main results, suggesting that synaptic low-pass filtering can account for these interrelationships. We also investigated the relationship between α and structural connectivity, as determined by diffusion tensor imaging-based tractography. We observe that the correlation between α and connectivity depends on attentional state; specifically, α correlated more highly to structural connectivity during rest than while attending to a task. Overall, these results provide global rules for the dynamics between frequency characteristics of local brain activity and the architecture of underlying brain networks.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Baria AT,Mansour A,Huang L,Baliki MN,Cecchi GA,Mesulam MM,Apkarian AV

doi

10.1016/j.neuroimage.2013.01.072

subject

Has Abstract

pub_date

2013-06-01 00:00:00

pages

144-55

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(13)00119-5

journal_volume

73

pub_type

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