Carolina Tecuatl

The paper presents an automated machine learning pipeline for standardizing and correcting neural morphology reconstructions, achieving high accuracy in dendritic relabeling and structural normalization.

Hippocampome.org provides a resource for classifying neuron types in the rodent hippocampal formation, focusing on subicular neurons and their circuitry.

The paper describes improvements to NeuroMorpho.Org, a digital neuromorphology database, to accelerate data sharing and processing, reducing time from data identification to public release by 63.7%.

Hippocampome.org v2.0 provides data-driven computational simulations of rodent hippocampal circuits using expanded neuron type classifications and empirical data.

The paper presents a tool that uses natural language processing and deep learning to automatically identify scientific publications describing digital reconstructions of neural morphology, achieving high accuracy and efficiency.