Journal article

Authors list: Kanwisher, N.; Gupta, P.; Dobs, K.

Publication year: 2023

Journal: iScience

Volume number: 26

Issue number: 2

Open access status: Gold

DOI Link: https://doi.org/10.1016/j.isci.2023.105976

Publisher: Cell Press

Abstract: 

Face perception has long served as a classic example of domain specificity of mind and brain. But an alternative “expertise” hypothesis holds that putatively face-specific mechanisms are actually domain-general, and can be recruited for the perception of other objects of expertise (e.g., cars for car experts). Here, we demonstrate the computational implausibility of this hypothesis: Neural network models optimized for generic object categorization provide a better foundation for expert fine-grained discrimination than do models optimized for face recognition.

Harvard Citation style: Kanwisher, N., Gupta, P. and Dobs, K. (2023) CNNs reveal the computational implausibility of the expertise hypothesis, iScience, 26(2), Article 105976. https://doi.org/10.1016/j.isci.2023.105976

APA Citation style: Kanwisher, N., Gupta, P., & Dobs, K. (2023). CNNs reveal the computational implausibility of the expertise hypothesis. iScience. 26(2), Article 105976. https://doi.org/10.1016/j.isci.2023.105976