Ivanova A, Schrimpf M, Anzellottie S, Zaslavsky N, Fedorenko E, and Isik L (2022) Is it that simple? Beyond Linear Regression: mapping models in cognitive neuroscience should align with research goals. Neurons, Brain, Data, and Theory [pdf]
Vogelstein J, Verstynen T, Kording K, Isik L et al. (2022) Prospective Learning: Back to the Future. [pdf]
Soulos P and Isik L (2020) Disentangled face representations in deep generative models and the human brain. NeurIPS SVRHM Workshop. [pdf]
Isik L, Mynick A, Pantazis D, and Kanwisher N (2020) The speed of human social interaction perception.
Dobs K, Isik L, Pantazis D, and Kanwisher N (2019) How face perception unfolds over time. Nature communications. [pdf]
Ward E, Isik L and Chun M (2018) General transformations of object representations in human visual cortex. Journal of Neuroscience.
Tacchetti A, Isik L, and Poggio T (2018) Invariant recognition shapes neural representations of visual input. Annual Reviews in Vision Science. [pdf]
Isik L, Tacchetti A, and Poggio T (2018) A fast, invariant representation for action in the human visual system. Journal of Neurophysiology. [pdf]
Isik L, Koldewyn K, Beeler D, and Kanwisher N (2017) Perceiving social interactions in the posterior superior temporal sulcus. PNAS. [pdf]
Isik L, Singer J, Madsen J, Kanwisher N, and Kreiman G (2017) What is changing when: Decoding visual information in movies from human intracranial recordings. Neuroimage. [pdf]
Tacchetti A*, Isik L*, and Poggio T (2017) Invariant recognition drives neural representations of actions. PLoS Computational Biology. [pdf]
Chen F, Roig G, Isik L, Boix X, and Poggio T (2017) Eccentricity-dependent deep neural networks: modeling invariance in human vision. Association for the Advancement of Artificial Intelligence. [pdf]
Isik L, Meyers E, Leibo J, and Poggio T (2014) The dynamics of invariant object recognition in the human visual system. Journal of Neurophysiology. [pdf]
Isik L, Mutch J, and Poggio T (2014) Computational role of eccentricity dependent cortical magnification. arXiv:1406.1770. [pdf]
Isik L, Leibo J, and Poggio T (2012) Learning and disrupting invariance in visual recognition with a temporal association learning rule. Frontiers in Computational Neuroscience. [pdf]