Comparing performance between a deep neural network and monkeys with bilateral removals of visual area TE in categorizing feature-ambiguous stimuli

Afraz, S. R., Kiani, R., & Esteky, H. (2006). Microstimulation of inferotemporal cortex influences face categorization. Nature., 442(7103), 692–5.

Article  CAS  PubMed  Google Scholar 

Bell, A. H., Hadj-Bouziane, F., Frihauf, J. B., Tootell, R. B., & Ungerleider, L. G. (2009). Object representations in the temporal cortex of monkeys and humans as revealed by functional magnetic resonance imaging. J Neurophysiol., 101(2), 688–700.

Article  PubMed  Google Scholar 

Cowey, A., & Gross, C. G. (1970). Effects of foveal prestriate and inferotemporal lesions on visual discrimination by rhesus monkeys. Exp Brain Res., 11(2), 128–44.

Article  CAS  PubMed  Google Scholar 

Deng, J., Dong, W., Socher, R., Li, L. J, Li, K., Li, F. F. (2009). ImageNet: A Large-Scale Hierarchical Image Database. Cvpr: 2009 IEEE Conference on Computer Vision and Pattern Recognition 1-4. 248-55.

Desimone, R., Albright, T. D., Gross, C. G., & Bruce, C. (1984). Stimulus-selective properties of inferior temporal neurons in the macaque. J Neurosci., 4(8), 2051–62.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Eldridge MA, Matsumoto N, Wittig JHJ, Masseau EC, Saunders RC, Richmond BJ. (2018) Perceptual processing in the ventral visual stream requires area TE but not rhinal cortex. Elife. 7.

Fukushima, K. (1980). Neocognitron: a self organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern., 36(4), 193–202.

Article  CAS  PubMed  Google Scholar 

Golan, T., et al. (2020). Controversial stimuli: Pitting neural networks against each other as models of human cognition. Proc Natl Acad Sci U S A, 117(47), 29330–29337.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., et al. (2014). Generative adversarial nets. In Proceedings of the 27th International Conference on Neural Information Processing Systems NIPS’14, Montreal, QC, 2672–2680.

Gothard, K. M., Erickson, C. A., & Amaral, D. G. (2004). How do rhesus monkeys (Macaca mulatta) scan faces in a visual paired comparison task? Anim Cognit, 7, 25–36.

Article  Google Scholar 

Gross, C. G., Rocha-Miranda, C. E., & Bender, D. B. (1972). Visual properties of neurons in inferotemporal cortex of the Macaque. J Neurophysiol., 35(1), 96–111.

Article  CAS  PubMed  Google Scholar 

Huang, G. B., Ramesh, M., Berg, T., & Learned-Miller, E. (2007). Labeled faces in the wild: a database for studying face recognition in unconstrained environments (pp. 07–49). University of Massachusetts Technical Report.

Google Scholar 

Iwai EM, Mishkin M. (1968). Two Visual Foci in the Temporal Lobe of Monkeys. In: Yoshii NB, N. A., editor. Neurophysiological Basis of Learning and Behavior: Osaka Univ. Press.

Kar, K., Kubilius, J., Schmidt, K., Issa, E. B., & DiCarlo, J. J. (2019). Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior. Nat Neurosci., 22(6), 974–83.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Krizhevsky, A., Sutskever, I., Hinton, G. E. (2012). ImageNet Classification with Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems.

Matsumoto, N., Eldridge, M. A., Saunders, R. C., Reoli, R., & Richmond, B. J. (2016). Mild Perceptual Categorization Deficits Follow Bilateral Removal of Anterior Inferior Temporal Cortex in Rhesus Monkeys. J Neurosci., 36(1), 43–53.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Matsumoto, N., Mototake, Y. I., Kawano, K., Okada, M., & Sugase-Miyamoto, Y. (2021). Comparison of neuronal responses in primate inferior-temporal cortex and feed-forward deep neural network model with regard to information processing of faces. J Comput Neurosci, 49(3), 251–257.

Article  PubMed  Google Scholar 

Matsumoto, N., Taguchi, Y., Shimizu, M., Katakami, S., Okada, M., & Sugase-Miyamoto, Y. (2022). Recurrent Connections Might Be Important for Hierarchical Categorization. Front Syst Neurosci, 16, 805990.

Article  PubMed  PubMed Central  Google Scholar 

Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983). Object Vision and Spatial Vision: Two Cortical Pathways. Trends in Neurosciences., 6(10), 414–7.

Article  Google Scholar 

Nefian, A.V., Hayes, M. H. (2000) Maximum likelihood training of the embedded HMM for face detection and recognition. IEEE International Conference on Image Processing, Vancouver, BC, Canada, September.

Riesenhuber, M., & Poggio, T. (2000). Models of object recognition. Nat Neurosci., 3(Suppl), 1199–204. Epub 2000/12/29.

Article  CAS  PubMed  Google Scholar 

Schrimpf, M., et al. (2020). Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like? bioRxiv: 407007.

Sigala, N., & Logothetis, N. K. (2002). Visual categorization shapes feature selectivity in the primate temporal cortex. Nature., 415(6869), 318–20.

Article  CAS  PubMed  Google Scholar 

Sugase, Y., Yamane, S., Ueno, S., & Kawano, K. (1999). Global and fine information coded by single neurons in the temporal visual cortex. Nature., 400(6747), 869–73.

Article  CAS  PubMed  Google Scholar 

Sugase-Miyamoto, Y., Matsumoto, N., Ohyama, K., & Kawano, K. (2014). Face inversion decreased information about facial identity and expression in face-responsive neurons in macaque area TE. J Neurosci., 34(37), 12457–69.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Spoerer, C. J., McClure, P., & Kriegeskorte, N. (2017). Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition. Front Psychol., 8, 1551.

Article  PubMed  PubMed Central  Google Scholar 

Szegedy C, Zaremba, W, Sutskever I, Bruna J, Erhan D, Goodfellow I, Fergus R. (2013) Intriguing properties of neural networks, arXiv, https://doi.org/10.48550/ARXIV.1312.6199

Tanaka, K. (1996). Inferotemporal cortex and object vision. Annu Rev Neurosci., 19, 109–39.

Article  CAS  PubMed  Google Scholar 

Tang, H., Schrimpf, M., Lotter, W., Moerman, C., Paredes, A., Ortega Caro, J., Hardesty, W., Cox, D., & Kreiman, G. (2018). Recurrent computations for visual pattern completion. PNAS, 115, 8835–8840.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tang, H., Buia, C., Madhavan, R., Madsen, J., Anderson, W., Crone, N., Kreiman, G. (2014). Spatiotemporal dynamics underlying object completion in human ventral visual cortex. Neuron, 83, 736–748.

Tsao, D. Y., Freiwald, W. A., Knutsen, T. A., Mandeville, J. B., & Tootell, R. B. (2003). Faces and objects in macaque cerebral cortex. Nat Neurosci., 6(9), 989–95.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Weiskrantz, L., & Saunders, R. C. (1984). Impairments of visual object transforms in monkeys. Brain., 107(Pt 4), 1033–72.

Article  PubMed  Google Scholar 

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