Analyzing Controllability of Dynamical Systems Modelling Brain Neural Networks
Year: 2019
Type: article
Abstract: The brain structure can be modelled as a deep recurrent complex neuronal network. Networked systems are expressly interesting systems to control because of the role of the underlying architecture, which predisposes some components to particular control motions. The concept of brain cognitive control is analogous to the mathematical concept of control used in engineering, where the state of a complex system can be adjusted by a particular input. The in-depth study on the controllability character of dynamical systems, despite being very difficult, could help to regulate the brain cognitive function. small advances in the study can favour the study and action against learning difficulties such as dyscalculia or other disturbances like the phenomena of forgetting.
Author: María Isabel García Planas
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3012308746