Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning

Chen, Nihong; Bi, Taiyong; Zhou, Tiangang; Li, Sheng; Liu, Zili; Fang, Fang

doi:10.1016/j.neuroimage.2015.04.041

Cited by 56 publications

(80 citation statements)

References 67 publications

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“…We reasoned that if training could improve the neural representations of the motion stimuli (especially in the trained direction), as suggested by the TMS and psychophysical results, it was possible that decoding accuracies for the orthogonal directions could be improved by training. Similar approaches have been used previously (19)(20)(21). Before training, a repeated-measures ANOVA revealed a significant main effect of stimulus coherence level and a significant interaction between stimulus coherence level and area [V3A and MT+; both F(1,11) > 7.87l P < 0.05; Fig.…”

Section: Resultsmentioning

confidence: 52%

“…In contrast, Vaina and colleagues (25,26) provided neuropsychological evidence indicating that V3A and MT+ are dominant in local and global motion processing, respectively. Recently, we found that perceptual training with 100% coherent motion increased the neural selectivity in V3A (21). We also have data showing that training with 40% coherent motion increased the neural selectivity in MT+.…”

Section: Discussionmentioning

confidence: 53%

“…The neural mechanisms of perceptual learning have been explained as changes in the tuning properties of neurons that provide sensory information and/or changes in how these sensory responses are routed to and weighted by decision-making areas (10,21,32). Our results suggest that both of these processes work in concert to improve task performance.…”

Section: Discussionmentioning

confidence: 76%

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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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Section: Resultsmentioning

confidence: 52%

Section: Discussionmentioning

confidence: 53%

Section: Discussionmentioning

confidence: 76%

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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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“…Changes also occur among connections linking stimulus components (Crist, Li, & Gilbert, 2001). Perceptual learning thereby improves efficiency in encoding and processing, which enhances response to stimuli (Chen et al, 2015;Li, Piech, & Gilbert, 2008).…”

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confidence: 99%

“…Neural models of perceptual learning emphasize interactions across levels of processing, particularly involving feedback from later stages that facilitate stimulus processing at early levels (Chen et al, 2015). The site of plasticity has been proposed to vary with task difficulty (reversed hierarchy theory), where less difficult tasks produce changes to high-order processing, while increased difficulty shifts plasticity to lowlevel processing specific to stimulus properties (Ahissar & Hochstein, 2004).…”

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confidence: 99%

Visual training improves perceptual grouping based on basic stimulus features

Kurylo

Waxman

Kidron

et al. 2017

Atten Percept Psychophys

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Training on visual tasks improves performance on basic and higher order visual capacities. Such improvement has been linked to changes in connectivity among mediating neurons. We investigated whether training effects occur for perceptual grouping. It was hypothesized that repeated engagement of integration mechanisms would enhance grouping processes. Thirty-six participants underwent 15 sessions of training on a visual discrimination task that required perceptual grouping. Participants viewed 20 × 20 arrays of dots or Gabor patches and indicated whether the array appeared grouped as vertical or horizontal lines. Across trials stimuli became progressively disorganized, contingent upon successful discrimination. Four visual dimensions were examined, in which grouping was based on similarity in luminance, color, orientation, and motion. Psychophysical thresholds of grouping were assessed before and after training. Results indicate that performance in all four dimensions improved with training. Training on a control condition, which paralleled the discrimination task but without a grouping component, produced no improvement. In addition, training on only the luminance and orientation dimensions improved performance for those conditions as well as for grouping by color, on which training had not occurred. However, improvement from partial training did not generalize to motion. Results demonstrate that a training protocol emphasizing stimulus integration enhanced perceptual grouping. Results suggest that neural mechanisms mediating grouping by common luminance and/or orientation contribute to those mediating grouping by color but do not share resources for grouping by common motion. Results are consistent with theories of perceptual learning emphasizing plasticity in early visual processing regions.

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Motion Perception

Park

Tadin

2018

Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience

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Motion perception is a key visual modality implicated in a wide range of critical functional roles. In addition to our ability to perceive moving objects, motion processing is involved in guiding locomotion, extracting object shape, figure‐ground segregation, capturing attention, and interpreting actions of our conspecifics. Here, we review advancements in our understanding of visual motion perception. We begin by describing the basic properties of motion, along with the computational challenges underlying detection and integration of motion signals. Next, we review more complex motion processes, discussing global motion perception, higher‐order motion, motion adaptation, motion in three dimensions, and biological motion. An important focus of this chapter is on interactions between motion perception and other sensory and cognitive modalities, including position, learning, attention, awareness, working memory, and multisensory processing. We also review notable examples of atypical motion processing in aging, cortical blindness, akinetopsia, amblyopia, schizophrenia, and autism spectrum disorder. For these topics, we cover key evidence from psychophysics, neurophysiology, neuroimaging, and computational modeling with an aim to provide a better understanding of the mechanisms that underlie our remarkable ability to take advantage of motion signals in the world. Finally, we highlight potentially interesting future directions in motion research.

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Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning

Cited by 56 publications

References 67 publications

Perceptual learning modifies the functional specializations of visual cortical areas

Perceptual learning modifies the functional specializations of visual cortical areas

Visual training improves perceptual grouping based on basic stimulus features

Motion Perception

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