Vinken et al. (2020)

Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception

Science Advances, 6(42)

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DOI

Abstract

Adding a cellular adaptation mechanism to artificial neural networks explains temporal context modulation of biological vision.

Reference

Vinken, K., Boix, X., & Kreiman, G. (2020). Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception. Science Advances, 6(42). https://doi.org/10.1126/sciadv.abd4205

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Non-Associative Learning Memory Systems

Measured in AI

Response suppression to repeated input has been shown in AI mainly when researchers build it in: an image-recognition network given built-in suppression reproduced adaptation aftereffects seen in people, but this is sensory adaptation, which the psychology definition separates from habituation, and the component is not part of today's AI assistants