Literature DB >> 16203984

Task-specific disruption of perceptual learning.

Aaron R Seitz1, Noriko Yamagishi, Birgit Werner, Naokazu Goda, Mitsuo Kawato, Takeo Watanabe.   

Abstract

For more than a century, the process of stabilization has been a central issue in the research of learning and memory. Namely, after a skill or memory is acquired, it must be consolidated before it becomes resistant to disruption by subsequent learning. Although it is clear that there are many cases in which learning can be disrupted, it is unclear when learning something new disrupts what has already been learned. Herein, we provide two answers to this question with the demonstration that perceptual learning of a visual stimulus disrupts or interferes with the consolidation of a previously learned visual stimulus. In this study, we trained subjects on two different hyperacuity tasks and determined whether learning of the second task disrupted that of the first. We first show that disruption of learning occurs between visual stimuli presented at the same orientation in the same retinotopic location but not for the same stimuli presented at retinotopically disparate locations or different orientations at the same location. Second, we show that disruption from stimuli in the same retinotopic location is ameliorated if the subjects wait for 1 h before training on the second task. These results indicate that disruption, at least in visual learning, is specific to features of the tasks and that a temporal delay of 1 h can stabilize visual learning. This research shows that visual learning is susceptible to disruption and elucidates the processes by which the brain can consolidate learning and thus protect what is learned from being overwritten.

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Year:  2005        PMID: 16203984      PMCID: PMC1253567          DOI: 10.1073/pnas.0505765102

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  45 in total

1.  Psychophysics: Is subliminal learning really passive?

Authors:  Aaron R Seitz; Takeo Watanabe
Journal:  Nature       Date:  2003-03-06       Impact factor: 49.962

2.  Nonlinear ideal observation and recurrent preprocessing in perceptual learning.

Authors:  L Zhaoping; Michael H Herzog; Peter Dayan
Journal:  Network       Date:  2003-05       Impact factor: 1.273

3.  Random presentation enables subjects to adapt to two opposing forces on the hand.

Authors:  Rieko Osu; Satomi Hirai; Toshinori Yoshioka; Mitsuo Kawato
Journal:  Nat Neurosci       Date:  2004-01-25       Impact factor: 24.884

4.  Functional magnetic resonance imaging examination of two modular architectures for switching multiple internal models.

Authors:  Hiroshi Imamizu; Tomoe Kuroda; Toshinori Yoshioka; Mitsuo Kawato
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

5.  Pharmacological modulation of perceptual learning and associated cortical reorganization.

Authors:  Hubert R Dinse; Patrick Ragert; Burkhard Pleger; Peter Schwenkreis; Martin Tegenthoff
Journal:  Science       Date:  2003-07-04       Impact factor: 47.728

6.  The spatial window of the perceptual template and endogenous attention.

Authors:  Barbara Anne Dosher; Shiau-Hua Liu; Nathaniel Blair; Zhong-Lin Lu
Journal:  Vision Res       Date:  2004-06       Impact factor: 1.886

7.  The effect of perceptual learning on neuronal responses in monkey visual area V4.

Authors:  Tianming Yang; John H R Maunsell
Journal:  J Neurosci       Date:  2004-02-18       Impact factor: 6.167

8.  Modular organization of internal models of tools in the human cerebellum.

Authors:  Hiroshi Imamizu; Tomoe Kuroda; Satoru Miyauchi; Toshinori Yoshioka; Mitsuo Kawato
Journal:  Proc Natl Acad Sci U S A       Date:  2003-04-18       Impact factor: 11.205

9.  Sleep-dependent learning: a nap is as good as a night.

Authors:  Sara Mednick; Ken Nakayama; Robert Stickgold
Journal:  Nat Neurosci       Date:  2003-07       Impact factor: 24.884

10.  Dissociable stages of human memory consolidation and reconsolidation.

Authors:  Matthew P Walker; Tiffany Brakefield; J Allan Hobson; Robert Stickgold
Journal:  Nature       Date:  2003-10-09       Impact factor: 49.962

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  47 in total

1.  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

2.  Perceptual learning: how much daily training is enough?

Authors:  Beverly A Wright; Andrew T Sabin
Journal:  Exp Brain Res       Date:  2007-02-27       Impact factor: 1.972

3.  Simultaneity learning in vision, audition, tactile sense and their cross-modal combinations.

Authors:  Veijo Virsu; Henna Oksanen-Hennah; Anita Vedenpää; Pentti Jaatinen; Pekka Lahti-Nuuttila
Journal:  Exp Brain Res       Date:  2008-01-09       Impact factor: 1.972

4.  Learning, worsening, and generalization in response to auditory perceptual training during adolescence.

Authors:  Julia Jones Huyck; Beverly A Wright
Journal:  J Acoust Soc Am       Date:  2013-08       Impact factor: 1.840

5.  When more equals less: overtraining inhibits perceptual learning owing to lack of wakeful consolidation.

Authors:  Soren Ashley; Joel Pearson
Journal:  Proc Biol Sci       Date:  2012-08-15       Impact factor: 5.349

6.  Deep Neural Networks for Modeling Visual Perceptual Learning.

Authors:  Li K Wenliang; Aaron R Seitz
Journal:  J Neurosci       Date:  2018-05-23       Impact factor: 6.167

7.  REM sleep rescues learning from interference.

Authors:  Elizabeth A McDevitt; Katherine A Duggan; Sara C Mednick
Journal:  Neurobiol Learn Mem       Date:  2014-12-11       Impact factor: 2.877

Review 8.  Advances in visual perceptual learning and plasticity.

Authors:  Yuka Sasaki; Jose E Nanez; Takeo Watanabe
Journal:  Nat Rev Neurosci       Date:  2009-12-02       Impact factor: 34.870

Review 9.  Common mechanisms of human perceptual and motor learning.

Authors:  Nitzan Censor; Dov Sagi; Leonardo G Cohen
Journal:  Nat Rev Neurosci       Date:  2012-09       Impact factor: 34.870

10.  Sleep and native language interference affect non-native speech sound learning.

Authors:  F Sayako Earle; Emily B Myers
Journal:  J Exp Psychol Hum Percept Perform       Date:  2015-08-17       Impact factor: 3.332

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