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time, which provide a compact representation that is directly related to biophysical brain dynamics.īrain activity spans many decades of spatial and temporal scale and constantly changes due to stimuli and internally generated signals ( Raichle, 2011). It is argued that for many purposes the intrinsic limitations of covariance-based FC instead favor the alternative of tracking eigenmode coefficients vs. Despite this, modes are independent and do not interact in the linear limit.

Unlike most published artificially discretized “resting state networks” and other statistically-derived patterns, eigenmodes overlap, with every mode extending across the whole brain and every region participating in every mode-just like the vibrations that give rise to notes of a musical instrument.

Common artifacts introduced by statistical analyses that do not incorporate the physical nature of the brain are discussed and it is shown that these are avoided by spectral analysis using eigenmodes. It is shown that FC is dynamic even when the brain structure and effective connectivity are fixed, and that the observed patterns of FC are dominated by relatively few eigenmodes. The dependences of FC on dynamics at various timescales, and on windowing, are clarified and the results are demonstrated on simple test cases, demonstrating how modes provide directly interpretable insights that can be related to brain structure and function.

These approaches integrate over space instead of averaging over time and thereby greatly reduce or remove the temporal averaging effects, windowing artifacts, and noise at fine spatial scales that have bedeviled the analysis of dynamical functional connectivity (FC). Spectral analysis based on neural field theory is used to analyze dynamic connectivity via methods based on the physical eigenmodes that are the building blocks of brain dynamics.

3Department of Biomedical Engineering, University of Melbourne, Parkville, VIC, Australia.

2Center of Excellence for Integrative Brain Function, University of Sydney, Sydney, NSW, Australia.

1School of Physics, University of Sydney, Sydney, NSW, Australia.

Aquino 1,2, Tara Babaie-Janvier 1,2 and Xiao Gao 1,2,3

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