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Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons
Preprint   Open access

Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons

Anthony Moreno-Sanchez, Alexander N Vasserman, HyoJong Jang, Bryce W Hina, Catherine R von Reyn and Jessica Ausborn
bioRxiv : the preprint server for biology
28 Apr 2024
DOI: https://doi.org/10.1101/2024.04.24.591016
PMID: 38712267
url
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11071487View
Preprint (Author's original)Open Access (License Unspecified),  Open

Abstract

Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.

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