No abstract

The coordination of activity between brain cells is a key determinant of neural circuit function; nevertheless, approaches that selectively regulate communication between two distinct cellular components of a circuit, while leaving the activity of the presynaptic brain cell undisturbed remain sparce. To address this gap, we developed a novel class of electrical synapses by selectively engineering two connexin proteins found in Morone americana (white perch fish): connexin34.7 (Cx34.7) and connexin35 (Cx35). By iteratively exploiting protein mutagenesis, a novel in vitro assay of connexin docking, and computational modeling of connexin hemichannel interactions, we uncovered the pattern of structural motifs that broadly determine connexin hemichannel docking. We then utilized this knowledge to design Cx34.7 and Cx35 hemichannels that dock with each other, but not with themselves nor other major connexins expressed in the human central nervous system. We validated these hemichannels in vivo, demonstrating that they facilitate communication between two neurons in Caenorhabditis elegans and recode a learned behavioral preference. This system can be applied to edit circuits composed by pairs of genetically defined brain cell types across multiple species. Thus, we establish a potentially translational approach, Long-term integration of Circuits using connexins (LinCx), for context-precise circuit-editing with unprecedented spatiotemporal specificity.

No abstract

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.