Multiscale symbolic morpho-barcoding reveals region-specific and scale-dependent neuronal organization

Area of Science:

• Neuroscience
• Computational Biology
• Systems Neuroscience

Background:

• Neuronal morphology is crucial for brain circuit organization but its complexity challenges whole-brain analysis.
• Existing methods struggle to systematically analyze the multiscale features of neuronal structure.

Purpose of the Study:

• To introduce a novel framework, multiscale morpho-barcoding (MMB), for encoding and analyzing whole-brain neuronal morphology.
• To uncover organizational principles of neuronal morphology and circuit architecture across different scales.

Main Methods:

• Developed multiscale morpho-barcoding (MMB) to generate symbolic barcodes from neuronal geometry, axonal routing, arbor organization, and predicted synaptic distributions.
• Applied MMB to a dataset of 1,876 fully reconstructed mouse neurons and 2.63 million predicted presynaptic sites.

Main Results:

• Identified distinct multiscale morpho-patterns revealing that neuronal morphology is region-specific and scale-dependent.
• MMB successfully discriminated major anatomical divisions and resolved canonical thalamic circuit classes in mouse brain data.
• Demonstrated that MMB offers higher resolution than projection strength-based representations for classifying neuronal circuits.

Conclusions:

• MMB provides a scalable and interpretable framework for integrating neuronal morphology with connectivity and function.
• The framework has potential applications in analyzing disease-related structural phenotypes and advancing brain-wide morphological studies.