Increasing stimulus similarity drives nonmonotonic representational change in hippocampus

eLife

Kenneth A Norman¹  Nicholas Turk-Browne²  Jeffrey Wammes³ 

[1] Department of Psychology, Princeton University, Princeton, United States;Princeton Neuroscience Institute, Princeton University, Princeton, United States;Department of Psychology, Yale University, New Haven, United States;Department of Psychology, Yale University, New Haven, United States;Department of Psychology, Queen’s University, Kingston, Canada;

关键词: plasticity;    statistical learning;    image synthesis;    deep neural networks;    model-based analysis;    Human;   

DOI  :  10.7554/eLife.68344

来源: eLife Sciences Publications, Ltd

【 摘 要 】

Studies of hippocampal learning have obtained seemingly contradictory results, with manipulations that increase coactivation of memories sometimes leading to differentiation of these memories, but sometimes not. These results could potentially be reconciled using the nonmonotonic plasticity hypothesis, which posits that representational change (memories moving apart or together) is a U-shaped function of the coactivation of these memories during learning. Testing this hypothesis requires manipulating coactivation over a wide enough range to reveal the full U-shape. To accomplish this, we used a novel neural network image synthesis procedure to create pairs of stimuli that varied parametrically in their similarity in high-level visual regions that provide input to the hippocampus. Sequences of these pairs were shown to human participants during high-resolution fMRI. As predicted, learning changed the representations of paired images in the dentate gyrus as a U-shaped function of image similarity, with neural differentiation occurring only for moderately similar images.

【 授权许可】

CC BY