Intrinsic control mechanisms of neuronal network dynamics
Control of self-organizing nonlinear systems, 2016•Springer
The brain is a complex dynamical system which employs specific mechanisms in a self-
organized way to stabilize functionally relevant patterns of activity and switch between them,
depending on computational demands. We first provide an overview of control mechanisms
that involve delayed feedback of activity, plasticity of synaptic coupling strengths and
changes of neuronal adaptation properties, and then focus on the latter, summarizing recent
results for different spatial levels, obtained through mathematical bottom-up modeling.
organized way to stabilize functionally relevant patterns of activity and switch between them,
depending on computational demands. We first provide an overview of control mechanisms
that involve delayed feedback of activity, plasticity of synaptic coupling strengths and
changes of neuronal adaptation properties, and then focus on the latter, summarizing recent
results for different spatial levels, obtained through mathematical bottom-up modeling.
Abstract
The brain is a complex dynamical system which employs specific mechanisms in a self-organized way to stabilize functionally relevant patterns of activity and switch between them, depending on computational demands. We first provide an overview of control mechanisms that involve delayed feedback of activity, plasticity of synaptic coupling strengths and changes of neuronal adaptation properties, and then focus on the latter, summarizing recent results for different spatial levels, obtained through mathematical bottom-up modeling.
Springer
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