An interpretable deep learning framework for classifying neuronal morphologies using topology and graph neural networks
Abstract Neuronal shape determines how neurons process and integrate information, yet a consistent and objective classification of neuronal morphologies remains elusive. Current approaches rely heavily on subjective expert views or on predefined features, limiting reproducibility and interpretability. Here, we present...
Lida Kanari, Stanislav Schmidt, Francesco Casalegno et al.
· Scientific Reports · 0 citations