Transfer of visual perceptual learning over a task-irrelevant feature through feature-invariant representations: Behavioral experiments and model simulations

被引:0
|
作者
Liu, Jiajuan [1 ]
Lu, Zhong-Lin [2 ,3 ,4 ]
Dosher, Barbara [1 ]
机构
[1] Univ Calif Irvine, Dept Cognit Sci, Irvine, CA 92617 USA
[2] NYU Shanghai, Div Arts & Sci, Shanghai, Peoples R China
[3] NYU, Psychol, New York, NY USA
[4] NYU ECNU Inst Brain & Cognit Sci, Shanghai, Peoples R China
来源
JOURNAL OF VISION | 2024年 / 24卷 / 06期
关键词
perceptuallearning; transfer; generalization; task-irrelevant feature; SPATIAL-FREQUENCY; ORIENTATION; SPECIFICITY; DISCRIMINATION; IMPROVEMENT; MECHANISMS; ADULTS;
D O I
10.1167/jov.24.6.17
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
A large body of literature has examined specificity and transfer of perceptual learning, suggesting a complex picture. Here, we distinguish between transfer over variations in a "task-relevant" feature (e.g., transfer of a learned orientation task to a different reference orientation) and transfer over a "task-irrelevant" feature (e.g., transfer of a learned orientation task to a different retinal location or different spatial frequency), and we focus on the mechanism for the latter. Experimentally, we assessed whether learning a judgment of one feature (such as orientation) using one value of an irrelevant feature (e.g., spatial frequency) transfers to another value of the irrelevant feature. Experiment 1 examined whether learning in eight-alternative orientation identification with one or multiple spatial frequencies transfers to stimuli at five different spatial frequencies. Experiment 2 paralleled Experiment 1, examining whether learning in eight-alternative spatial-frequency identification at one or multiple orientations transfers to stimuli with five different orientations. Training the orientation task with a single spatial frequency transferred widely to all other spatial frequencies, with a tendency to specificity when training with the highest spatial frequency. Training the spatial frequency task fully transferred across all orientations. Computationally, we extended the identification integrated reweighting theory (I-IRT) to account for the transfer data (Dosher, Liu, & Lu, 2023; Liu, Dosher, & Lu, 2023). Just as location-invariant representations in the original IRT explain transfer over retinal locations, incorporating feature-invariant representations effectively accounted for the observed transfer. Taken together, we suggest that feature-invariant representations can account for transfer of learning over a "task-irrelevant" feature.
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页数:24
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