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While the observation of power laws within neuronal activity may be attractive we must address the issue of whether (specifically) a neuronal system in the region of a critical state can produce this type of dynamics.
This behaviour has also been observed in a more detailed, higher dimensional model of interacting neural masses used as a model of absence epilepsy, so our results suggest that there is an underlying bifurcation mechanism leading to this type of dynamics.
While LRTCs in avalanche activity would not be possible in a seeded computational system (where the activity is initiated 'by hand' and there is no memory within the system's dynamics) it is conceivable that a driven system, which is more akin to physiological networks which can display LRTCs, might display this type of dynamics in the waiting times of neuronal avalanches.
This type of dynamics represents the canonical bistable activity which has been a major focus of theoretical and computation modeling.
A model of a noise-driven bi- or multistable system in which different phenotypes correspond to a metastable state of the underlying transcriptional network can account for this type of dynamics.
This type of dynamics exhibits remarkable flexibility such that external stimulation can trigger a transfer of neural activity into different phase synchrony patterns with minimal expenditure of energy (cf., Freeman 2007).
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This third article focuses on approaches to develop an efficient coupled model of dynamics (considering aerodynamics, hydrodynamics, structural and mooring line dynamics, and control dynamics) for floating VAWTs, as well as suitable 'semi-analytical' hydrodynamic models for this type of coupled dynamics models.
The results further highlight the need for future work examining the type of dynamics we might expect from such systems.
Discovering the type of dynamics that governs the movements of the ER network is essential for gaining insights into the structure and functions of cells.
By analytically tuning the system to be in the region of a critical regime we were able to examine the type of dynamics displayed by such a system and to investigate whether the dynamics displays signatures of criticality.
Bad news on the macroeconomic or the political front still carries the risk of triggering the type of dynamics we saw last fall.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com