A cortical gradient of distance to criticality governs large-scale resting-state fMRI dynamics
Yellin, D.; Simony, E.; Malach, R.; Shriki, O.
Show abstract
A longstanding puzzle in cortical research is how the cerebral cortex, having largely uniform interconnected architecture, gives rise to such diverse yet highly structured spatiotemporal activity. Here, we propose that local cortical networks distance from criticality (DTC) provides a unifying principle related to this conundrum. Analyzing resting-state fMRI BOLD signals and leveraging simple network models of randomly connected recurrent units, we show that DTC robustly explains key dynamical features, in particular, local power spectra and functional connectivity, across the full set of 360 cortical areas. Our analysis shows that a rank-order distribution of DTC values is highly conserved across subjects. Moreover, the empirical analysis of cortical slow dynamics and its fitted network simulations demonstrate similar power-laws across hierarchies of the cortical sheet. These results suggest that recurrent neuronal networks, operating close to criticality, can generate a remarkably rich dynamical repertoire which fit the entire range of experimentally observed cortical dynamics. Our findings underscore the importance of DTC as a powerful, fundamental generator underlying the spectrum of diverse cortical dynamics. HighlightsO_LISpontaneous (resting-state) activity in the human cortex is shown to be organized along a conserved spatial gradient of distance from criticality (DTC), with regions exhibiting a stable cross-individual rank order along this axis. C_LIO_LIMulti-subject fMRI data of regional power spectra and functional connectivity can be fitted with a single parameter simulation model based on DTC. C_LIO_LIQuantitative estimation of the DTC across cortical regions can be achieved using a simple sparse recurrent neural network model. C_LIO_LIThe model fits the power spectra of low frequency fluctuations and the distribution of functional connectivity. C_LIO_LIShape collapse analysis of the power spectrum demonstrates a universal profile across the resting cortex depending only on the DTC. C_LI
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