Dear Colleagues,
With best regards,
Claudius Gros and Dimitrije Marković
Abstract
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Brains empower living organisms with extraordinary information
processing capabilities. Complex spatio-temporal dependencies
present in their environments may be learned, long- and short-term
memories of experiences and plans regarding the future.
Importantly, information processing in the brain happens over
multiple spatio-temporal scales, from single synapses and synaptic
terminals to dendritic trees and neuronal bodies, all the way up
to neuronal networks and large brain areas.
Hence, it is not surprising that information theory has led to
many exciting developments in computational neuroscience, providing
tools essential for our modern understanding of the computational
principles that govern the development, structure, physiology,
and dynamics of the nervous system.
In this Special Issue, we aim to bring together neuronal models
and neuronal plasticity mechanisms that are grounded in information
theory principles, modern inference, and learning algorithms. We
welcome submissions that use information theory as the basis for
defining generative principles of neuronal dynamics over multiple
spatio-temporal scales, which informs our understanding of
information processing in the brain.