Comparing memory capacity across stimuli requires maximally dissimilar foils: Using deep convolutional neural networks to understand visual working memory capacity for real-world objects.

MLA

Brady, Timothy F., and Viola S. Störmer. “Comparing Memory Capacity across Stimuli Requires Maximally Dissimilar Foils: Using Deep Convolutional Neural Networks to Understand Visual Working Memory Capacity for Real-World Objects.” Memory & Cognition, vol. 52, no. 3, Apr. 2024, pp. 595–609. EBSCOhost, https://doi.org/10.3758/s13421-023-01485-5.

APA

Brady, T. F., & Störmer, V. S. (2024). Comparing memory capacity across stimuli requires maximally dissimilar foils: Using deep convolutional neural networks to understand visual working memory capacity for real-world objects. Memory & Cognition, 52(3), 595–609. https://doi.org/10.3758/s13421-023-01485-5

Chicago

Brady, Timothy F., and Viola S. Störmer. 2024. “Comparing Memory Capacity across Stimuli Requires Maximally Dissimilar Foils: Using Deep Convolutional Neural Networks to Understand Visual Working Memory Capacity for Real-World Objects.” Memory & Cognition 52 (3): 595–609. doi:10.3758/s13421-023-01485-5.