[1] Matteo Carandini, Jonathan B Demb, Valerio Mante, David J Tolhurst, Yang Dan, Bruno A Olshausen, Jack L Gallant, and Nicole C Rust. Do we know what the early visual system does? Journal of Neuroscience, 25(46):10577-10597, 2005.
[2] Marcel AJ van Gerven. A primer on encoding models in sensory neuroscience. Journal of Mathematical Psychology, 76:172-183, 2017.
[3] Thomas Naselaris, Kendrick N Kay, Shinji Nishimoto, and Jack L Gallant. Encoding and decoding in fmri. Neuroimage, 56(2):400-410, 2011.
[4] Christina Enroth-Cugell and John G Robson. The contrast sensitivity of retinal ganglion cells of the cat. The Journal of physiology, 187(3):517-552, 1966.
[5] Edward H Adelson and James R Bergen. Spatiotemporal energy models for the perception of motion. Josa a, 2(2):284-299, 1985.
[6] Daniel LK Yamins, Ha Hong, Charles F Cadieu, Ethan A Solomon, Darren Seibert, and James J DiCarlo. Performance-optimized hierarchical models predict neural responses in higher visual cortex. Proceedings of the national academy of sciences, 111(23):8619–8624, 2014.
[7] Seyed-Mahdi Khaligh-Razavi and Nikolaus Kriegeskorte. Deep supervised, but not unsupervised, models may explain it cortical representation. PLoS computational biology, 10(11):e1003915, 2014.
[8] Alexander JE Kell, Daniel LK Yamins, Erica N Shook, Sam V Norman-Haignere, and Josh H McDermott. A task-optimized neural network replicates human auditory behavior, predicts brain responses, and reveals a cortical processing hierarchy. Neuron, 98(3):630–644, 2018.
[9] Blake A Richards, Timothy P Lillicrap, Philippe Beaudoin, Yoshua Bengio, Rafal Bogacz, Amelia Christensen, Claudia Clopath, Rui Ponte Costa, Archy de Berker, Surya Ganguli, et al. A deep learning framework for neuroscience. Nature neuroscience, 22(11):1761-1770, 2019.
[10] Grace W Lindsay. Convolutional neural networks as a model of the visual system: Past, present, and future. Journal of cognitive neuroscience, 33(10):2017-2031, 2021.
[11] Martin Schrimpf, Jonas Kubilius, Ha Hong, Najib J Majaj, Rishi Rajalingham, Elias B Issa, Kohitij Kar, Pouya Bashivan, Jonathan Prescott-Roy, Franziska Geiger, et al. Brain-score: Which artificial neural network for object recognition is most brain-like? BioRxiv, page 407007, 2018.
[12] Greta Tuckute, Jenelle Feather, Dana Boebinger, and Josh H McDermott. Many but not all deep neural network audio models capture brain responses and exhibit hierarchical region correspondence. bioRxiv, pages 2022-09, 2022.
[13] Colin Conwell, Jacob S Prince, Kendrick N Kay, George A Alvarez, and Talia Konkle. What can 1.8 billion regressions tell us about the pressures shaping high-level visual representation in brains and machines? BioRxiv, pages 2022-03, 2022.
[14] Andrew Saxe, Stephanie Nelli, and Christopher Summerfield. If deep learning is the answer, what is the question? Nature Reviews Neuroscience, 22(1):55-67, January 2021.
[15] Jenelle Feather, Guillaume Leclerc, Aleksander Madry, and Josh H McDermott. Model metamers reveal divergent invariances between biological and artificial neural networks. Nature Neuroscience, pages 1-18, 2023.
[16] Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A Wichmann, and Wieland Brendel. Partial success in closing the gap between