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Adaptivity and Inhomogeneity in Neuronal Networks

A prevailing property of neuronal networks in the brain is that they are inhomogeneous in structure and in composition. Nonetheless, networks of neurons are often implicitly treated as being homogeneous in structure, even though the properties of their individual nodes and connectivity vary considerably in biological neuronal networks. Recent reports show that networks react to these inhomogeneities and that this can have a profound impact on different aspects of a network’s activity dynamics.

However, what appears homogeneous on one scale of observation may appear inhomogeneous on another: parameters like neuron density, patchy connectivity patterns, inhomogeneous neuron types and synaptic connections between them, etc., can be viewed either on local or on global scales. No doubt do such inhomogeneities have an impact on network activity and, consequently, on the interpretation of experimental data. In addition to unavoidable statistical variability, pathological conditions, be it after peripheral amputations, stroke, dysplasia, epilepsy, etc., induce further changes to network structure. These changes, in turn, provoke adaptive responses on different levels, from synaptic plasticity to neurogenesis. Localized pathological changes may lead to another type of inhomogeneity in the form of gradients of properties.

Such inhomogeneities would have significant consequences from several perspectives. The statistical distribution of neuron types, synapses, connectivity motifs and recurrent connectivity would become highly variable across space. On the other hand, adaptive processes may counteract inhomogeneity. If this is the case at all, whether it is an advantageous goal, or under which boundary conditions it might be successful, is currently not known.

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