Complex adaptive networks are a ubiquitous paradigm in nature, with a wide field of applications ranging from physics, chemistry, biology, neuroscience, physiology, medicine to socio-economic systems. In adaptive networks, the connectivity changes in time, for instance, the synaptic connections between neurons are adapted depending on the relative timing of neuronal spiking. Thus the network structure reorganizes adaptively in response to the dynamics.
Similarly, chemical, biochemical, biological or even social systems have been reported, where the reaction rates adapt dynamically depending on the variables of the system. One of the simplest forms of adaptation can be found in the synchronization of coupled nonlinear oscillators. Various synchronization patterns are known, like cluster synchronization where the network splits into groups of synchronous elements, or partial synchronization patterns like chimera states where the system splits into coexisting domains of coherent (synchronized) and incoherent (desynchronized) states. These patterns are also explored in adaptive networks, where several dynamical scenarios have been revealed including the self-organized formation of co-existing frequency clusters or chimera-like states.
In this Research Topic contributions are invited within a general dynamical systems perspective, and a view to applications in physiological systems, in order to shed light on the complex interplay between adaptivity induced phenomena with complex connectivity structures, coupling delay, and noise. The focus is on functional modelling of the interactions between different parts of the living organism, not on a detailed biochemical modelling of a single organ or system.
Topics covered by this Research Topic include, but are not limited to:
• adaptive networks in neuroscience
• networks with adaptive biophysical and biochemical interactions, communication and information exchange between cells and organs.
• interplay of local dynamics and network topology, delay, and noise
• partial synchronization patterns in single and multilayer networks with adaptivity
• control and regulatory mechanisms in adaptive networks
Complex adaptive networks are a ubiquitous paradigm in nature, with a wide field of applications ranging from physics, chemistry, biology, neuroscience, physiology, medicine to socio-economic systems. In adaptive networks, the connectivity changes in time, for instance, the synaptic connections between neurons are adapted depending on the relative timing of neuronal spiking. Thus the network structure reorganizes adaptively in response to the dynamics.
Similarly, chemical, biochemical, biological or even social systems have been reported, where the reaction rates adapt dynamically depending on the variables of the system. One of the simplest forms of adaptation can be found in the synchronization of coupled nonlinear oscillators. Various synchronization patterns are known, like cluster synchronization where the network splits into groups of synchronous elements, or partial synchronization patterns like chimera states where the system splits into coexisting domains of coherent (synchronized) and incoherent (desynchronized) states. These patterns are also explored in adaptive networks, where several dynamical scenarios have been revealed including the self-organized formation of co-existing frequency clusters or chimera-like states.
In this Research Topic contributions are invited within a general dynamical systems perspective, and a view to applications in physiological systems, in order to shed light on the complex interplay between adaptivity induced phenomena with complex connectivity structures, coupling delay, and noise. The focus is on functional modelling of the interactions between different parts of the living organism, not on a detailed biochemical modelling of a single organ or system.
Topics covered by this Research Topic include, but are not limited to:
• adaptive networks in neuroscience
• networks with adaptive biophysical and biochemical interactions, communication and information exchange between cells and organs.
• interplay of local dynamics and network topology, delay, and noise
• partial synchronization patterns in single and multilayer networks with adaptivity
• control and regulatory mechanisms in adaptive networks
