Biology subjects

Hughes, D. N.

Publications and source records attributed to Hughes, D. N..

3 recordsLinked to original sources

bioRxiv2025

Long-term editing of brain circuits in mice using an engineered electrical synapse

Electrical signaling across distinct populations of brain cells underpins cognitive and emotional function; however, approaches that selectively regulate electrical signaling between two cellular components of a mammalian neural circuit remain sparse. Here, we engineered an electrical synapse composed of two connexin proteins found in Morone americana (white perch fish) - connexin34.7 and connexin35 - to accomplish mammalian circuit modulation. By exploiting protein mutagenesis, devising a new in vitro system for assaying connexin hemichannel docking, and performing computational modeling of hemichannel interactions, we uncovered a structural motif that contributes to electrical synapse formation. Targeting these motifs, we designed connexin34.7 and connexin35 hemichannels that dock with each other to form an electrical synapse, but not with other major connexins expressed in the mammalian central nervous system. We validated this electrical synapse in vivo using C. elegans and mice, demonstrating that it can strengthen communication across neural circuits composed of pairs of distinct cell types and modify behavior accordingly. Thus, we establish Long-term integration of Circuits using connexins (LinCx) for precision circuit-editing in mammals.

neuroscience↗

bioRxiv2024

A widespread electrical brain network encodes anxiety in health and depressive states

In rodents, anxiety is characterized by heightened vigilance during low-threat and uncertain situations. Though activity in the frontal cortex and limbic system is fundamental to supporting this internal state, the underlying network architecture that integrates activity across brain regions to encode anxiety across animals and paradigms remains unclear. Here, we utilize parallel electrical recordings in freely behaving mice, multiple translational paradigms known to induce anxiety, and machine learning to discover a multi-region network that encodes the anxious brain state. The network is composed of circuits widely implicated in anxiety behavior, it generalizes across many behavioral contexts that induce anxiety, and it fails to encode multiple behavioral contexts that do not. Strikingly, the activity of this network is also principally altered in two mouse models of depression. Thus, we establish a network-level process whereby the brain encodes anxiety in health and disease.

neuroscience↗

bioRxiv2019

Brain-wide electrical spatiotemporal dynamics encode reward anticipation

Anticipation of an upcoming stimulus induces neural activity across cortical and subcortical regions and influences subsequent behavior. Nevertheless, the network mechanism whereby the brain integrates this information to signal the anticipation of rewards remains relatively unexplored. Here we employ multi-circuit electrical recordings from six brain regions as mice perform a sample-to-match task in which reward anticipation is operationalized as their progress towards obtaining a potential reward. We then use machine learning to discover the naturally occurring network patterns that integrate this neural activity across timescales. Only one of the networks that we uncovered signals responses linked to reward anticipation, specifically relative proximity and reward magnitude. Activity in this Electome (electrical functional connectivity) network is dominated by theta oscillations leading from prelimbic cortex and striatum that converge on ventral tegmental area, and by beta oscillations leading from striatum that converge on prelimbic cortex. Network activity is also synchronized with brain-wide cellular firing. Critically, this network generalizes to new groups of healthy mice, as well as a mouse line that models aberrant neural circuitry observed in brain disorders that show altered reward anticipation. Thus, our findings reveal the network-level architecture whereby the brain integrates spatially distributed activity across timescales to signal reward anticipation.

neuroscience↗