Spiking and saturating dendrites differentially expand single neuron computation capacity. - Romain Daniel Cazé; Mark D. Humphries; Boris S. Gutkin (NIPS, 2012)

Adaptive properties of differential learning rates for positive and negative outcomes. - Romain D. Cazé; Matthijs A. A. van der Meer (Biol. Cybern., 2013)

Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions. - Romain Daniel Cazé; Mark D. Humphries; Boris S. Gutkin (PLoS Comput. Biol., 2013)

Computing threshold functions using dendrites. - Romain D. Cazé; Bartosz Telenczuk; Alain Destexhe (CoRR, 2016)

Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity. - Romain D. Cazé; Sarah Jarvis; Amanda J. Foust; Simon R. Schultz (Neural Comput., 2017)

Any neuron can perform linearly non-separable computations. - Romain D. Cazé (F1000Research, 2021)

On exploiting the synaptic interaction properties to obtain frequency-specific neurons. - Guillaume Marthe; Claire Goursaud; Romain D. Cazé; Laurent Clavier (CoRR, 2023)