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Topic: Hierarchical Bayesian Mixture Model

ePoster
1 ePoster

In Neuroscience

A hierarchical Bayesian mixture approach for modelling neuronal connectivity patterns from MAPseq data

Edward Agboraw, Jinlu Liu, Sara Wade, Sara Gomez Arnaiz, Gulsen Surmeli · FENS Forum 2024

Structural motif analysis seeks to better understand brain connectivity by interrogating the long-range axonal projections that link distant brain regions at the single-cell resolution. This approach is enabled by MAPseq, a novel experimental methodology which labels cellular projections with viral barcodes. This recontextualizes single-neuron tracing as a problem of sequencing, overcoming the throughput limitations of prior optical techniques and capitalizing on the swift advancement of modern sequencing technology.Current MAPseq-based long range projection motif analysis methods rely on the

ePoster · Neuroscience