Literature DB >> 15955722

A unified model for perceptual learning.

Aaron Seitz1, Takeo Watanabe.   

Abstract

Perceptual learning in adult humans and animals refers to improvements in sensory abilities after training. These improvements had been thought to occur only when attention is focused on the stimuli to be learned (task-relevant learning) but recent studies demonstrate performance improvements outside the focus of attention (task-irrelevant learning). Here, we propose a unified model that explains both task-relevant and task-irrelevant learning. The model suggests that long-term sensitivity enhancements to task-relevant or irrelevant stimuli occur as a result of timely interactions between diffused signals triggered by task performance and signals produced by stimulus presentation. The proposed mechanism uses multiple attentional and reinforcement systems that rely on different underlying neuromodulators. Our model provides insights into how neural modulators, attentional and reinforcement learning systems are related.

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Year:  2005        PMID: 15955722     DOI: 10.1016/j.tics.2005.05.010

Source DB:  PubMed          Journal:  Trends Cogn Sci        ISSN: 1364-6613            Impact factor:   20.229


  127 in total

1.  SELECTIVENESS OF THE EXPOSURE-BASED PERCEPTUAL LEARNING: WHAT TO LEARN AND WHAT NOT TO LEARN.

Authors:  Hoon Choi; Takeo Watanabe
Journal:  Learn Percept       Date:  2009-05-07

2.  Pupillometry as a glimpse into the neurochemical basis of human memory encoding.

Authors:  Russell Cohen Hoffing; Aaron R Seitz
Journal:  J Cogn Neurosci       Date:  2014-11-12       Impact factor: 3.225

3.  Effect of feature-selective attention on neuronal responses in macaque area MT.

Authors:  X Chen; K-P Hoffmann; T D Albright; A Thiele
Journal:  J Neurophysiol       Date:  2011-12-14       Impact factor: 2.714

4.  Perceptual learning with perceptions.

Authors:  Anja Stemme; Gustavo Deco; Elmar W Lang
Journal:  Cogn Neurodyn       Date:  2010-10-01       Impact factor: 5.082

5.  Resetting capacity limitations revealed by long-lasting elimination of attentional blink through training.

Authors:  Hoon Choi; Li-Hung Chang; Kazuhisa Shibata; Yuka Sasaki; Takeo Watanabe
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-09       Impact factor: 11.205

6.  Rule-based learning explains visual perceptual learning and its specificity and transfer.

Authors:  Jun-Yun Zhang; Gong-Liang Zhang; Lu-Qi Xiao; Stanley A Klein; Dennis M Levi; Cong Yu
Journal:  J Neurosci       Date:  2010-09-15       Impact factor: 6.167

7.  Alpha-band EEG activity in perceptual learning.

Authors:  Brett C Bays; Kristina M Visscher; Christophe C Le Dantec; Aaron R Seitz
Journal:  J Vis       Date:  2015       Impact factor: 2.240

8.  Exogenous attention facilitates location transfer of perceptual learning.

Authors:  Ian Donovan; Sarit Szpiro; Marisa Carrasco
Journal:  J Vis       Date:  2015       Impact factor: 2.240

9.  Confidence-based integrated reweighting model of task-difficulty explains location-based specificity in perceptual learning.

Authors:  Bharath Chandra Talluri; Shao-Chin Hung; Aaron R Seitz; Peggy Seriès
Journal:  J Vis       Date:  2015       Impact factor: 2.240

10.  Varying irrelevant phonetic features hinders learning of the feature being trained.

Authors:  Mark Antoniou; Patrick C M Wong
Journal:  J Acoust Soc Am       Date:  2016-01       Impact factor: 1.840

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