Spatial constraints and cell surface molecule depletion structure a randomly connected learning circuit
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1154304 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30478600.fastq.gz | Fastqsanger.gz | |||
| SRR30478601.fastq.gz | Fastqsanger.gz | |||
| SRR30478593.fastq.gz | Fastqsanger.gz | |||
| SRR30478594.fastq.gz | Fastqsanger.gz | |||
| SRR30478595.fastq.gz | Fastqsanger.gz |
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Project description:Spatial constraints and cell surface molecule depletion structure a randomly connected learning circuit
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Project description:The brain can represent almost limitless objects to "categorize an unlabeled world" (Edelman, 1989). This feat is supported by expansion layer circuit architectures, in which neurons carrying information about discrete sensory channels make combinatorial connections onto much larger postsynaptic populations. Combinatorial connections in expansion layers are modeled as randomized sets. The extent to which randomized wiring exists in vivo is debated, and how combinatorial connectivity patterns are generated during development is not understood. Non-deterministic wiring algorithms could program such connectivity using minimal genomic information. Here, we investigate anatomic and transcriptional patterns and perturb partner availability to ask how Kenyon cells, the expansion layer neurons of the insect mushroom body, obtain combinatorial input from olfactory projection neurons. Olfactory projection neurons form their presynaptic outputs in an orderly, predictable, and biased fashion. We find that Kenyon cells accept spatially co-located but molecularly heterogeneous inputs from this orderly map, and ask how Kenyon cell surface molecule expression impacts partner choice. Cell surface immunoglobulins are broadly depleted in Kenyon cells, and we propose that this allows them to form connections with molecularly heterogeneous partners. This model can explain how developmentally identical neurons acquire diverse wiring identities.
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