Activity-dependent neurite outgrowth and neuronal migration interact to shape modular mesoscale network architecture by homeostatic self-organization.

Effectively connected neurons self-organize forming networks with a small-world architecture composed of modules, with most likely few and nearby neurons, integrated by more topologically important and high firing rate neurons.

Following sensory deprivation in adult mice, homeostatic synaptic strengthening occurs in non-sensory network responsive synapses, but not in sensory responsive synapses, despite homeostatic increases to the global sensory-evoked responses.

The NetPyNE software tool provides a framework to efficiently develop, simulate, optimize and analyze experimentally grounded neural models spanning the molecular, cellular and circuit scales.

Hippocampal sharp-wave sequences, which are considered the key phenomenon underlying consolidation of episodic memory, are preserved even after an animal’s memory is impaired.

A new probabilistic model of connectivity reveals the structural and functional properties of the neural networks controlling locomotion in many individual tadpoles.

The synaptic structure in mouse V1 is explained by a synergy of homeostatic plasticity in incoming and outgoing synapses of inhibitory interneurons, establishing a stimulus-specific balance of excitation and inhibition.

Neuronal networks balance flexibility with stability by allowing the firing rate of individual neurons within a network to vary over time, while ensuring that the average firing rate across the network remains constant.

A practical toolbox for application of Granger causality inference to calcium imaging data identifies strong driver neurons in the locus of the mesencephalic locomoter region in larval zebrafish.

Autism-associated iPSC-derived neurons mutant in CNTN5 or EHMT2 are hyperactive.