September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Extensive training of orientation filtered textures increases generalization of learning
Author Affiliations
  • Ali Hashemi
    Department of Psychology, Neuroscience, & Behaviour, McMaster University
  • Allison Sekuler
    Department of Psychology, Neuroscience, & Behaviour, McMaster University
  • Patrick Bennett
    Department of Psychology, Neuroscience, & Behaviour, McMaster University
Journal of Vision August 2017, Vol.17, 509. doi:10.1167/17.10.509
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      Ali Hashemi, Allison Sekuler, Patrick Bennett; Extensive training of orientation filtered textures increases generalization of learning. Journal of Vision 2017;17(10):509. doi: 10.1167/17.10.509.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Previously, we (Hashemi et al., VSS 2015 & VSS 2016) investigated perceptual learning in a texture identification task using textures that contain diagnostic information (Target) in one orientation band and non-diagnostic information (Context) in a perpendicular orientation band. We found that, compared to Target-alone (i.e., no Context) textures, training in a 1-of-6 identification task with Target+Context textures resulted in lower accuracy, less learning, but greater generalization of learning. Specifically, training with Target+Context patterns generalized to familiar Target-alone textures, but training with Target-alone stimuli did not generalize to familiar Target+Context textures. Nevertheless, even with Target+Context training, we found no evidence of generalization to novel targets, regardless of context. Here we investigated whether greater generalization of learning could be obtained by significantly increasing the amount of training with Target+Context stimuli from 960 to 4200 trials. Before and after training, we assessed identification accuracy on trained and novel Targets with and without Context. We also tested accuracy on textures where the Target and Context orientations were swapped, using both novel and trained Targets. Results varied across observers: During training, accuracy increased by at least 50% in half of the participants, but only by ~20% in the others. Our post-training assessment found 1) all participants improved on the trained Target+Context textures; and some participants generalized learning to 2) familiar and novel Target-alone textures; 3) novel Target+Context textures; and/or 4) orientation-swapped Target+Context textures. Finally, the different patterns of generalization were not related in any simple way to the change in accuracy that occurred during training. Our results indicate that perceptual learning of orientation filtered textures varies significantly across individuals, but that it can be generalized to novel and familiar targets in novel contexts. These findings may have implications for perceptual learning in applied settings in which generalization of learning is a critical component of training.

Meeting abstract presented at VSS 2017

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