| Full text | |
| Author(s): |
Costa, Ariadne A.
;
Amon, Mary Jean
;
Sporns, Olaf
;
Favela, Luis H.
;
Cornelius, S
;
Coronges, K
;
Goncalves, B
;
Sinatra, R
;
Vespignani, A
Total Authors: 9
|
| Document type: | Journal article |
| Source: | COMPLEX NETWORKS IX; v. N/A, p. 11-pg., 2018-01-01. |
| Abstract | |
Although there is increasing evidence of criticality in the brain, the processes that guide neuronal networks to reach or maintain criticality remain unclear. The present research examines the role of neuronal gain plasticity in time-series of simulated neuronal networks composed of integrate-and-fire stochastic spiking neurons and the utility of fractal methods in assessing network criticality. Simulated time-series were derived from a network model of fully connected discrete-time stochastic excitable neurons. Monofractal and multifractal analyses were applied to neuronal gain time-series. Fractal scaling was greatest in networks with a mid-range of neuronal plasticity, versus extremely high or low levels of plasticity. Peak fractal scaling corresponded closely to additional indices of criticality, including average branching ratio. Networks exhibited multifractal structure, or multiple scaling relationships. Multifractal spectra around peak criticality exhibited elongated right tails, suggesting that the fractal structure is relatively insensitive to high-amplitude local fluctuations. Networks near critical states exhibited mid-range multifractal spectra width and tail length, which is consistent with the literature suggesting that networks poised at quasi-critical states must be stable enough to maintain organization but unstable enough to be adaptable. Lastly, fractal analyses may offer additional information about critical state dynamics of networks by indicating scales of influence as networks approach critical states. (AU) | |
| FAPESP's process: | 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat |
| Grantee: | Oswaldo Baffa Filho |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/00430-3 - Computational simulations of stochastic integrate-and-fire neurons balanced networks |
| Grantee: | Ariadne de Andrade Costa |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 16/20945-8 - Impact of Connection Topology on the Dynamics of Stochastic Integrate-and-Fire Neuronal Network |
| Grantee: | Ariadne de Andrade Costa |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |