An unsupervised map of excitatory neuron dendritic morphology in the mouse visual cortex.

ABSTRACT: Neurons in the neocortex exhibit astonishing morphological diversity, which is critical for properly wiring neural circuits and giving neurons their functional properties. However, the organizational principles underlying this morphological diversity remain an open question. Here, we took a data-driven approach using graph-based machine learning methods to obtain a low-dimensional morphological "bar code" describing more than 30,000 excitatory neurons in mouse visual areas V1, AL, and RL that were reconstructed from the millimeter scale MICrONS serial-section electron microscopy volume. Contrary to previous classifications into discrete morphological types (m-types), our data-driven approach suggests that the morphological landscape of cortical excitatory neurons is better described as a c

SUBMITTER: Weis MA 

PROVIDER: S-EPMC11982532 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature