Feedforward object-vision models only tolerate small image variations compared to human. - Masoud Ghodrati; Amirhossein Farzmahdi; Karim Rajaei; Reza Ebrahimpour; Seyed-Mahdi Khaligh-Razavi (Frontiers Comput. Neurosci., 2014)

The importance of visual features in generic vs. specialized object recognition: a computational study. - Masoud Ghodrati; Karim Rajaei; Reza Ebrahimpour (Frontiers Comput. Neurosci., 2014)

A specialized face-processing network consistent with the representational geometry of monkey face patches. - Amirhossein Farzmahdi; Karim Rajaei; Masoud Ghodrati; Reza Ebrahimpour; Seyed-Mahdi Khaligh-Razavi (CoRR, 2015)

Deep Networks Resemble Human Feed-forward Vision in Invariant Object Recognition. - Saeed Reza Kheradpisheh; Masoud Ghodrati; Mohammad Ganjtabesh; Timothée Masquelier (CoRR, 2015)

Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder. - Saeed Reza Kheradpisheh; Masoud Ghodrati; Mohammad Ganjtabesh; Timothée Masquelier (Frontiers Comput. Neurosci., 2016)

Deep learning in spiking neural networks. - Amirhossein Tavanaei; Masoud Ghodrati; Saeed Reza Kheradpisheh; Timothée Masquelier; Anthony Maida (Neural Networks, 2019)

Perceptual difficulty modulates the direction of information flow in familiar face recognition. - Hamid Karimi-Rouzbahani; Farzad Ramezani; Alexandra Woolgar; Anina N. Rich; Masoud Ghodrati (NeuroImage, 2021)