Literature DB >> 11008139

Perceptual learning for a pattern discrimination task.

I Fine1, R A Jacobs.   

Abstract

Our goal was to differentiate low and mid level perceptual learning. We used a complex grating discrimination task that required observers to combine information across wide ranges of spatial frequency and orientation. Stimuli were 'wicker'-like textures containing two orthogonal signal components of 3 and 9 c/deg. Observers discriminated a 15% spatial frequency shift in these components. Stimuli also contained four noise components, separated from the signal components by at least 45 degrees of orientation or approximately 2 octaves in spatial frequency. In Experiment 1 naive observers were trained for eight sessions with a four-alternative same-different forced choice judgment with feedback. Observers showed significant learning, thresholds dropped to approximately 1/3 of their original value. In Experiment 2 we found that observers showed far less learning when the noise components were not present. Experiment 3 found, unlike many other studies, almost complete transfer of learning across orientation. The results of Experiments 2 and 3 suggest that, unlike many other perceptual learning studies, most learning in Experiment 1 occurs at mid to high levels of processing rather than within low level analyzers tuned for spatial frequency and orientation. Experiment 4 found that performance was more severely impaired by spatial frequency shifts in noise components of the same spatial frequency or orientation as the signal components (though there was significant variability between observers). This suggests that after training observers based their responses on mechanisms tuned for selective regions of Fourier space. Experiment 5 examined transfer of learning from a same-sign task (the two signal components both increased/decreased in spatial frequency) to an opposite-sign task (signal components shifted in opposite directions in frequency space). Transfer of learning from same-sign to opposite-sign tasks and vice versa was complete suggesting that observers combined information from the two signal components independently.

Mesh:

Year:  2000        PMID: 11008139     DOI: 10.1016/s0042-6989(00)00163-2

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  14 in total

1.  MECHANISMS OF PERCEPTUAL LEARNING.

Authors:  Zhong-Lin Lu; Barbara Anne Dosher
Journal:  Learn Percept       Date:  2009-06-01

Review 2.  Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies.

Authors:  Michael Beyeler; Ariel Rokem; Geoffrey M Boynton; Ione Fine
Journal:  J Neural Eng       Date:  2017-06-14       Impact factor: 5.379

3.  Hebbian Reweighting on Stable Representations in Perceptual Learning.

Authors:  Barbara Anne Dosher; Zhong-Lin Lu
Journal:  Learn Percept       Date:  2009-06-01

Review 4.  Exercising your brain: a review of human brain plasticity and training-induced learning.

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5.  Task precision at transfer determines specificity of perceptual learning.

Authors:  Pamela E Jeter; Barbara Anne Dosher; Alexander Petrov; Zhong-Lin Lu
Journal:  J Vis       Date:  2009-03-05       Impact factor: 2.240

6.  Optimization of perceptual learning: effects of task difficulty and external noise in older adults.

Authors:  Denton J DeLoss; Takeo Watanabe; George J Andersen
Journal:  Vision Res       Date:  2013-11-21       Impact factor: 1.886

7.  Learning to detect and combine the features of an object.

Authors:  Jordan W Suchow; Denis G Pelli
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-24       Impact factor: 11.205

8.  Brain activity underlying auditory perceptual learning during short period training: simultaneous fMRI and EEG recording.

Authors:  Ana Cláudia Silva de Souza; Hani Camille Yehia; Masa-aki Sato; Daniel Callan
Journal:  BMC Neurosci       Date:  2013-01-14       Impact factor: 3.288

Review 9.  Treatment of amblyopia in the adult: insights from a new rodent model of visual perceptual learning.

Authors:  Joyce Bonaccorsi; Nicoletta Berardi; Alessandro Sale
Journal:  Front Neural Circuits       Date:  2014-07-16       Impact factor: 3.492

10.  Neuronal basis of perceptual learning in striate cortex.

Authors:  Zhen Ren; Jiawei Zhou; Zhimo Yao; Zhengchun Wang; Nini Yuan; Guangwei Xu; Xuan Wang; Bing Zhang; Robert F Hess; Yifeng Zhou
Journal:  Sci Rep       Date:  2016-04-20       Impact factor: 4.379

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