Network connectivity modulates power spectrum scale invariance

NeuroImage
Anca R Radulescu, Lilianne R Mujica-Parodi

Abstract

Measures of complexity are sensitive in detecting disease, which has made them attractive candidates for diagnostic biomarkers; one complexity measure that has shown promise in fMRI is power spectrum scale invariance (PSSI). Even if scale-free features of neuroimaging turn out to be diagnostically useful, however, their underlying neurobiological basis is poorly understood. Using modeling and simulations of a schematic prefrontal-limbic meso-circuit, with excitatory and inhibitory networks of nodes, we present here a framework for how network density within a control system can affect the complexity of signal outputs. Our model demonstrates that scale-free behavior, similar to that observed in fMRI PSSI data, can be obtained for sufficiently large networks in a context as simple as a linear stochastic system of differential equations, although the scale-free range improves when introducing more realistic, nonlinear behavior in the system. PSSI values (reflective of complexity) vary as a function of both input type (excitatory, inhibitory) and input density (mean number of long-range connections, or strength), independent of their node-specific geometric distribution. Signals show pink noise (1/f) behavior when excitatory and in...Continue Reading

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Citations

Feb 3, 2016·Scientific Reports·Anusha MohanSven Vanneste
Dec 23, 2015·BMC Neurology·Sanja NedicJaime S Ide
Feb 2, 2015·Chaos·Anca Rǎdulescu, Sergio Verduzco-Flores
Mar 29, 2020·The International Journal of Neuropsychopharmacology·Lilianne R Mujica-Parodi, Helmut H Strey
Feb 5, 2021·Brain and Behavior·Frigyes Samuel RaczAndras Eke
Mar 7, 2021·Scientific Reports·Anar AmgalanHava T Siegelmann

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