Perceptual Learning: Toward a Comprehensive Theory

Watanabe, Takeo; Sasaki, Yuka

doi:10.1146/annurev-psych-010814-015214

Cited by 276 publications

(299 citation statements)

References 153 publications

(281 reference statements)

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“…The perceptual learning literature, which is the main paradigm for studying adult sensory plasticity, suggests that long term plasticity effects are more prominent in associative areas (13,18), questioning the original idea that V1 circuitry can be optimized by perceptual experience (15). Our paradigm is very different from perceptual learning, having short-term consequences and being independent of perceptual decisions; our data clearly show that V1 circuitry can change with abnormal visual experience.…”

Section: Discussionmentioning

confidence: 99%

“…Perceptual learning requires long training sessions repeated over several days in combination with positive reward (13)(14)(15)(16)(17)(18). In spite of extensive research, it is still debated whether perceptual learning fine-tunes the neuronal responses at level of primary visual cortex or whether the effect primarily lies in associative cortices (18)(19)(20)(21)(22)(23)(24), which usually retain a higher level of plasticity in adulthood. More recently, psychophysical studies have revealed a form of adult plasticity after short-term deprivation, probably associated with an alteration of primary visual cortex processing, where deprivation paradoxically leads to enhanced sensitivity.…”

Section: Introductionmentioning

confidence: 99%

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Short-term plasticity of the human adult visual cortex measured with 7T BOLD

Binda

Kurzawski

Lunghi

et al. 2018

Preprint

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Primary visual cortex is considered to be resilient to plastic changes in adults -particularly ocular dominance, which appears to be hard-wired after the end of the critical period. We show that shortterm (2h) monocular deprivation unexpectedly shifts ocular dominance in favor of the deprived eye: contrary to common belief. The plastic response of V1 (measured with 7T fMRI) consists of a homeostatic increase of the deprived-eye BOLD response, a shift of V1 ocular dominance and a decrease of spatial frequency selectivity for the deprived eye. These effects reliably predict the robust perceptual changes induced by deprivation at the individual participant level. Our results indicate that primary visual cortex retains a high potential for homeostatic plasticity in the human adult. Significance statementPlasticity, the brain reorganization in response to deprivation, is maximum during development but decreases in adulthood, particularly in primary sensory areas. Here we show, for the first time, that short-term sensory deprivation in human adults transiently changes key functional properties of primary visual cortex. Our participants applied a translucent patch on one eye for 2h, after which two key properties of V1 (measured with ultra-high field fMRI) were systematically changed:All rights reserved. No reuse allowed without permission.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Short-term plasticity of the human adult visual cortex measured with 7T BOLD

Binda

Kurzawski

Lunghi

et al. 2018

Preprint

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“…perceptual learning | motion | psychophysics | transcranial magnetic stimulation | functional magnetic resonance imaging P erceptual learning, an enduring improvement in the performance of a sensory task resulting from practice, has been widely used as a model to study experience-dependent cortical plasticity in adults (1). However, at present, there is no consensus on the nature of the neural mechanisms underlying this type of learning.…”

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confidence: 99%

Perceptual learning modifies the functional specializations of visual cortical areas

Chen

Cai

Zhou

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Training can improve performance of perceptual tasks. This phenomenon, known as perceptual learning, is strongest for the trained task and stimulus, leading to a widely accepted assumption that the associated neuronal plasticity is restricted to brain circuits that mediate performance of the trained task. Nevertheless, learning does transfer to other tasks and stimuli, implying the presence of more widespread plasticity. Here, we trained human subjects to discriminate the direction of coherent motion stimuli. The behavioral learning effect substantially transferred to noisy motion stimuli. We used transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms underlying the transfer of learning. The TMS experiment revealed dissociable, causal contributions of V3A (one of the visual areas in the extrastriate visual cortex) and MT+ (middle temporal/medial superior temporal cortex) to coherent and noisy motion processing. Surprisingly, the contribution of MT+ to noisy motion processing was replaced by V3A after perceptual training. The fMRI experiment complemented and corroborated the TMS finding. Multivariate pattern analysis showed that, before training, among visual cortical areas, coherent and noisy motion was decoded most accurately in V3A and MT+, respectively. After training, both kinds of motion were decoded most accurately in V3A. Our findings demonstrate that the effects of perceptual learning extend far beyond the retuning of specific neural populations for the trained stimuli. Learning could dramatically modify the inherent functional specializations of visual cortical areas and dynamically reweight their contributions to perceptual decisions based on their representational qualities. These neural changes might serve as the neural substrate for the transfer of perceptual learning.perceptual learning | motion | psychophysics | transcranial magnetic stimulation | functional magnetic resonance imaging P erceptual learning, an enduring improvement in the performance of a sensory task resulting from practice, has been widely used as a model to study experience-dependent cortical plasticity in adults (1). However, at present, there is no consensus on the nature of the neural mechanisms underlying this type of learning. Perceptual learning is often specific to the physical properties of the trained stimulus, leading to the hypothesis that the underlying neural changes occur in sensory coding areas (2). Electrophysiological and brain imaging studies have shown that visual perceptual learning alters neural response properties in primary visual cortex (3, 4) and extrastriate areas including V4 (5) and MT+ (middle temporal/medial superior temporal cortex) (6), as well as object selective areas in the inferior temporal cortex (7,8). An alternative hypothesis proposes that perceptual learning is mediated by downstream cortical areas that are responsible for attentional allocation and/or decision-making, such as the intraparietal sulcus (IPS) and anterior...

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“…Our participant group of children with IN consisted of children with idiopathic IN and children with albinism accompanied by IN. Previous studies have demonstrated that reading performance can be improved by perceptual learning, [18][19][20] which refers to a long-term performance increase resulting from perceptual experience. 21 The reading measure that is improved by perceptual learning depends on the paradigm used. Visual span training, which aims to increase the number of letters that can be read without moving the eyes (visual span) by training several locations in the visual field, can increase maximum reading speed by an impressive 41%.…”

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confidence: 99%

Perceptual Learning in Children With Infantile Nystagmus: Effects on Reading Performance

Huurneman

Boonstra

Goossens

2016

Invest. Ophthalmol. Vis. Sci.

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PURPOSE. Perceptual learning improves visual acuity and reduces crowding in children with infantile nystagmus (IN). Here, we compare reading performance of 6-to 11-year-old children with IN with normal controls, and evaluate whether perceptual learning improves their reading. METHODS.Children with IN were divided in two training groups: a crowded training group (n ¼ 18; albinism: n ¼ 8; idiopathic IN: n ¼ 10) and an uncrowded training group (n ¼ 17; albinism: n ¼ 9; idiopathic IN: n ¼ 8). Also 11 children with normal vision participated. Outcome measures were: reading acuity (the smallest readable font size), maximum reading speed, critical print size (font size below which reading is suboptimal), and acuity reserve (difference between reading acuity and critical print size). We used multiple regression analyses to test if these reading parameters were related to the children's uncrowded distance acuity and/or crowding scores.RESULTS. Reading acuity and critical print size were 0.65 6 0.04 and 0.69 6 0.08 log units larger for children with IN than for children with normal vision. Maximum reading speed and acuity reserve did not differ between these groups. After training, reading acuity improved by 0.12 6 0.02 logMAR and critical print size improved by 0.11 6 0.04 logMAR in both IN training groups. The changes in reading acuity, critical print size, and acuity reserve of children with IN were tightly related to changes in their uncrowded distance acuity and the changes in magnitude and extent of crowding.CONCLUSIONS. Our findings are the first to show that visual acuity is not the only factor that restricts reading in children with IN, but that crowding also limits their reading performance. By targeting both of these spatial bottlenecks in children with IN, our perceptual learning paradigms significantly improved their reading acuity and critical print size. This shows that perceptual learning can effectively transfer to reading.

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Perceptual Learning: Toward a Comprehensive Theory

Cited by 276 publications

References 153 publications

Short-term plasticity of the human adult visual cortex measured with 7T BOLD

Short-term plasticity of the human adult visual cortex measured with 7T BOLD

Perceptual learning modifies the functional specializations of visual cortical areas

Perceptual Learning in Children With Infantile Nystagmus: Effects on Reading Performance

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