bioRxiv Science⌕ Search

Biology subjects

Dunn, A. W. E.

Publications and source records attributed to Dunn, A. W. E..

2 recordsLinked to original sources

Mecp2 deficiency impairs microscale cortical network topology and dynamics in a Rett syndrome mouse model

Rett syndrome is a debilitating neurodevelopmental disorder with cerebral processing impairments caused by MECP2 loss-of-function mutations. Mecp2-deficient mouse models reveal disruptions of microscale cortical circuits. Yet how cellular-scale information processing is altered in Mecp2-deficient microscale functional networks is unknown. We investigated the development of functional connectivity, network topology, and dynamics in microelectrode array (MEA) recordings of primary cortical cultures from Mecp2-deficient and wild-type mice. Mecp2-deficient cortical networks developed more slowly and showed decreased functional connectivity compared to wild-type, leading to smaller network size, density, and strength of connectivity. Altered network topological features in Mecp2-deficient microscale circuits predicted decreased efficiency and information-sharing capacity. This reveals developmental deficits in microscale functional networks, which may in turn underlie the cortical decline and severe cognitive disability in Rett syndrome. These findings also offer circuit-level targets and an in-vitro approach for evaluating new therapeutic products for restoring microscale network function.

neuroscience↗

Homophilic wiring principles underpin neuronal network topology in vitro

Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, the precise nature of the economic negotiations governing this putative organizational principle remains unclear. Here, we address this question further by combining large-scale electrophysiological recordings, to characterize the functional connectivity of developing neuronal networks in vitro, with a generative modeling approach capable of simulating network formation. We find that the best fitting model uses a homophilic generative wiring principle in which neurons form connections to other neurons which are spatially proximal and have similar connectivity patterns to themselves. Homophilic generative models outperform more canonical models in which neurons wire depending upon their spatial proximity either alone or in combination with the extent of their local connectivity. This homophily-based mechanism for neuronal network emergence accounts for a wide range of observations that are described, but not sufficiently explained, by traditional analyses of network topology. Using rodent and human monolayer and organoid cultures, we show that homophilic generative mechanisms can accurately recapitulate the topology of emerging cellular functional connectivity, representing an important wiring principle and determining factor of neuronal network formation in vitro.

neuroscience↗