An explainable deep learning model for the identification of layers and areas in the primate cerebral cortex
Piotr Majka, Adam Datta, Agata Kulesza, Sylwia Bednarek, Marcello Rosa · FENS Forum 2024
Understanding the principles behind how the cerebral cortex processes information requires identifying and characterizing its areal and laminar cytoarchitecture. In this context, deep learning offers a promising avenue to address these challenges by streamlining manual segmentation and offering observer-independent insights into cortical structure.We propose a deep-learning model for segmenting the cerebral cortex into areas and layers. We tested this solution on a dataset of one-dimensional cortical profiles derived from a non-human primate - common marmoset monkey (Callithrix jacchus) brain.
ePoster · Neuroscience