Computational connectomics analysis of synapse tuning during development.

• Applicant: Andre Ferreira Castro, Ph.D.
• Subject Area: Experimental and Theoretical Network Neuroscience ; Developmental Neurobiology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 551026198

Understanding how distinct plasticity mechanisms synergize during development to generate functional circuits is one of the most important outstanding problems in neuroscience. This challenge is exacerbated by the technical challenges of obtaining anatomical data of fine-scale connectivity. The proposed research aims to investigate the synaptic plasticity mechanisms that govern neural circuit synaptic tuning, with a focus on the tractable insect brain. The core objective of our project is to elucidate how neural circuits achieve correct synaptic weights through a combination of activity-dependent and -independent mechanisms. The workflow and models to be developed will allow me to address how different plasticity mechanisms interact and contribute to synaptic tuning during development. The project will be accomplished with the following two aims: 1. Aim 1: I will generate structural synaptic data leveraging electronic microscopy datasets from a complete motor circuit of both wild-type Drosophila larva and mutants, encompassing those with genetically silenced activity or shifted neuronal positions. This will be a major advance in the field, as no other such prior analysis exists of any organism. I will quantify synapse sizes at nanometer resolution—a marker for synaptic strength across an entire, well-characterized neuronal circuit. This approach will enable me to evaluate candidate plasticity rules based on measured experimentally from densely-reconstructed connectomic datasets. 2. Aim 2: I will analyze anatomical traces of plasticity-dependent mechanisms based on the measured data from Aim 1. This analysis will inform the development of computational models that elucidate the interplay between activity-dependent and -independent mechanisms in the fine-tuning of synaptic connections. I will use these computational models to test various plasticity mechanisms implicated in synapse tuning, in order to challenge current models of neuronal circuit assembly. Crucially, combining synaptic-level resolution data with computational modeling will yield a mechanistic understanding of neuronal circuit tuning. This approach will enable me to dissect the role of individual plasticity mechanisms within our models—a task that is challenging to accomplish through experimental methods alone.

• DFG Programme: WBP Position