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Предыдущая публикация
Jan M. Ache

One neat little feat: within each ensemble, individual DNs make unique connections to motor neurons via specific interneurons, which enable variations of the core motor pattern - leading to landing movements with unique leg kinematics, such as reaching overhead, suitable for landing on the ceiling.

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Jan M. Ache

3rd we went upstream to ask how DNs get recruited by sensory systems. We identified all visual inputs to landing and takeoff DN ensembles - and find they are recruited by separate, parallel sets of visual feature detectors. And core input neurons to the landing pathway drive landing phenotypes.

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1 прямых ответов · 9 сообщений

Jan M. Ache

Our connectome analysis predicts functional connectivity, which we verify by patching/optogenetic activation experiments in behaving flies. Importantly, though, actual connectivity is heavily state-dependent, so that sensory activity gets routed into landing pathways only during flight.

Ответ для Jan M. Ache
Jan M. Ache

This makes sense, functionally, because landing is only relevant in the context of flight, and the landing motor pattern would disrupt other actions, such as walking or courtship, when evoked in the wrong context.

Ответ для Jan M. Ache
Jan M. Ache

4th, we asked whether the variants of the landing movements driven by different DNs are matched to their sensory tuning - it turns out they are! Different Landing DNs receive visual input from different spatial directions, and the sensory tuning matches the movements they drive.

Ответ для Jan M. Ache
Jan M. Ache

Despite relying on a different set of sensory feature detectors, landing DNs are responsive to frontal looming stimuli. But their response differs from that of takeoff DNs, showing that the networks upstream of each DN ensemble encode different parameters of the same stimulus.

Ответ для Jan M. Ache
Jan M. Ache

At this point, we’ve shown that landing and takeoff are controlled by separate, parallel populations of neurons on each sensorimotor level - from feature detection to pre-motor assemblies. Despite being triggered by the same visual stimulus. How widespread is this parallel processing architecture?

Ответ для Jan M. Ache
Jan M. Ache

5th, it turns out - very! Based on their output similarity in the VNC, we were able to cluster all 1300 DNs into functional ensembles covering the entire behavioral space of the fly. DNs previously associated with specific behaviors clustered together. So these clusters align with specific behaviors

Ответ для Jan M. Ache
Jan M. Ache

Overall, DNs form parallel, loosely-overlapping ensembles that span a continuum from command-like neurons to synergistic population codes. Upstream, distinct combinations of sensory feature detectors differentially recruit DN ensembles to enable flexible, context-dependent behavioral control.

Ответ для Jan M. Ache
Jan M. Ache

We, in this case, are stellar postdocs and shared first-authors @sanderliessem.bsky.social and @skasin.bsky.social with a team from @uni-wuerzburg.de, @hhmijanelia.bsky.social and @columbiauniversity.bsky.social in a collaboration between the Ache and Card labs & friends.

Ответ для Jan M. Ache
Jan M. Ache

We are extremely grateful to the #maleCNS team, incl. @janelia-flyem.bsky.social, @jefferis.bsky.social and lab, and many, many others. Backstory >> bsky.app/profile/jeff... Website >> male-cns.janelia.org

Greg Jefferis

Excited to share our new #biorxivpreprint: “Sexual dimorphism in the complete connectome of the Drosophila male central nervous system” www.biorxiv.org/content/10.1... We describe the #connectomics reconstruction and analysis of an entire adult #maleCNS #drosophila central nervous system. 1/10