Greater plasticity in lower-level than higher-level visual motion processing in a passive perceptual learning task

Watanabe, T.; Náñez, José E.; Koyama, Shinichi; Mukai, Ikuko; Liederman, Jacqueline; Sasaki, Yuka

doi:10.1038/nn915

Cited by 193 publications

(210 citation statements)

References 44 publications

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“…However, training in clear displays requires the system to work to reduce internal limitations (or equivalently amplify the stimulus) but also provides good information about the nature of the target stimulus or the perceptual template. Although an optimized template is far more critical in noisy displays, template tuning may nonetheless occur in low-noise training by optimization of information about the stimulus, ¶ or possibly by repetitive task-relevant exposure to the signal stimuli (25,26). Training the template in (lowcontrast) low-noise displays may be sufficient to optimize the filtering of external noise substantially, especially when the external noise is white.…”

Section: Discussionmentioning

confidence: 99%

Perceptual learning in clear displays optimizes perceptual expertise: Learning the limiting process

Dosher

Lü

2005

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

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Human operators develop expertise in perceptual tasks by practice or perceptual learning. For noisy displays, practice improves performance by learned external-noise filtering. For clear displays, practice improves performance by improved amplification or enhancement of the stimulus. Can these two mechanisms of perceptual improvement be trained separately? In an orientation task, we found that training with clear displays generalized to performance in noisy displays, but we did not find the reverse to be true. In noisy displays, the noise in the stimulus limits performance. In clear displays, performance is limited by noisiness of internal representations and processes. Our results suggest that training in one display condition optimizes the limiting factor(s) in performance in that condition and that noise filtering is also improved by exposure to the stimulus in clear displays. The asymmetric pattern of transfer implies the existence of two independent mechanisms of perceptual learning, which may reflect channel reweighting in adult visual system. These results also suggest that training operators with clear stimuli may suffice to improve performance in a range of clear and noisy environments by simultaneous learning by two mechanisms.training procedures ͉ noisy displays ͉ observer models P erceptual learning (1-4) can improve the performance of observers significantly, creating perceptual expertise (5, 6). Practice on a stimulus and task often results in very substantial improvements reflected in improved accuracy or in an ability to perform at a given threshold accuracy level with a more difficult (e.g., lower contrast) stimulus. Also, perceptual learning accrued by practice often exhibits specificities to stimulus characteristics such as retinal position (2, 7), orientation (8, 9), or scale (10, 11), demonstrating perceptual rather than strategic knowledge. Refs. 1 and 12 proposed the possible existence of three independent mechanisms of perceptual learning and empirically documented the existence of two of the mechanisms: external-noise filtering and stimulus amplification. The mechanisms are characterized and tested by a perceptual template model (PTM) of the human observer with titrated external-noise manipulations (12-14). The two mechanisms are important in different environments: external-noise filtering or exclusion in noisy environments and stimulus amplification in clear environments. Perceptual learning in these two mechanisms reflects the improvements in different kinds of limitations: improvements in the quality of the information in the stimulus by external-noise filtering and improvements in the intrinsic limitations in the processing of the human observer by stimulus enhancement.In these investigations of perceptual learning in visual tasks (1, 12, 15), training in high and low noise have always been intermixed, so that the two documented mechanisms have often occurred together as mixtures (for exception, see ref. 16). Single-mechanism models have provided one explanation for simultaneous lea...

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Section: Discussionmentioning

confidence: 99%

Perceptual learning in clear displays optimizes perceptual expertise: Learning the limiting process

Dosher

Lü

2005

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

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“…Similarly, Ahissar and Hochstein (2002) found that subjects' learning to detect a target within a horizontally or vertically elongated array does not transfer to a feature of the array they do not attend, namely, the orientation of the array. Although Watanabe and his colleagues (Watanabe et al, 2001(Watanabe et al, , 2002Seitz and Watanabe, 2003) have shown that it is not necessary for attention to be directed to a visual feature for that feature to be learned, they admit that attention plays an important role in perceptual learning (Seitz and Watanabe, 2005).…”

Section: Changes In Attention-related Areas During Perceptual Learningmentioning

confidence: 99%

Activations in Visual and Attention-Related Areas Predict and Correlate with the Degree of Perceptual Learning

Mukai¹,

Kim²,

Fukunaga³

et al. 2007

J. Neurosci.

151

131

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Repeated experience with a visual stimulus can result in improved perception of the stimulus, i.e., perceptual learning. To understand the underlying neural mechanisms of this process, we used functional magnetic resonance imaging to track brain activations during the course of training on a contrast discrimination task. Based on their ability to improve on the task within a single scan session, subjects were separated into two groups: "learners" and "nonlearners." As learning progressed, learners showed progressively reduced activation in both visual cortex, including Brodmann's areas 18 and 19 and the fusiform gyrus, and several cortical regions associated with the attentional network, namely, the intraparietal sulcus (IPS), frontal eye field (FEF), and supplementary eye field. Among learners, the decrease in brain activations in these regions was highly correlated with the magnitude of performance improvement. Unlike learners, nonlearners showed no changes in brain activations during training. Learners showed stronger activation than nonlearners during the initial period of training in all these brain regions, indicating that one could predict from the initial activation level who would learn and who would not. In addition, over the course of training, the functional connectivity between IPS and FEF in the right hemisphere with early visual areas was stronger for learners than nonlearners. We speculate that sharpened tuning of neuronal representations may cause reduced activation in visual cortex during perceptual learning and that attention may facilitate this process through an interaction of attention-related and visual cortical regions.

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“…Fourth, is task involvement during training necessary for the observed shift in neural sites? It has been shown that perceptual learning of a feature results from not only training on a task on the feature but also exposure to the feature that is irrelevant to the task (17)(18)(19). It would be highly interesting to test whether the transfer observed in this study and associated neural shifts occur as a result of mere exposure to 100% coherent motion task-irrelevant.…”

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confidence: 86%

V3A takes over a job of MT+ after training on a visual task

Sasaki¹,

Watanabe²

2016

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

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A person's performance on a perceptual task can be significantly improved by repetitive training on the task. This improvement is termed perceptual learning and is regarded as a manifestation of adult plasticity in perceptual and brain processing (1). To date, detailed neural mechanisms of perceptual learning have yet to be completely understood. The recent study by Chen et al. in PNAS (2) advances the understanding by showing that transfer of perceptual learning of 100% coherent motion to noisy motion is associated with dramatic changes in involved neural sites.Distinguished from other types of learning and memory, many types of perceptual learning occur only for the trained feature and its presented location (3, 4). Such specificity has been interpreted as a manifestation of involvements of local circuits in early sensory cortical areas, which generally have smaller receptive fields than higher level cortical areas in perceptual and brain information processing (5).However, it has also been suggested that, as perceptual learning proceeds, those neural sites involved sometimes shift from higher-level cortical areas to lower-level ones (6). More recently, it has been found that, if some methods are combined with traditional training methods of perceptual learning, perceptual learning of a stimulus at a location in the visual field is transferred to other locations (7,8). These findings have attracted a great deal of attention because they suggest that neural sites involved in perceptual learning include brain regions beyond early sensory areas. These results are also consistent with the model that reweighting between sensory processing and perceptual decision underlies perceptual learning (9-11).Chen et al. have developed an ingenious experimental design to examine how two different areas, V3A and MT+, are involved in perceptual learning of a coherent motion task and its transfer to a different type of motion. Before training, participants' performance was measured for two types motion stimuli, 100% coherent motion and 40% coherent motion, presented on different sides of the visual field. A 100% coherent motion display consisted of dots, all of which move at the same direction and speed. A display with 40% coherent motion consists of only 40% of dots moving coherently while the remaining 60% of dots move randomly and therefore is regarded as a noisy motion display.Next, to examine brain areas that play significant roles in processing 100% and 40% coherent motions, transcranial magnetic stimulation (TMS) was applied on a region of the scalp close to V3A in one group of participants and to MT+ in the other group. The V3A-disturbed group showed impaired performance on discrimination of 100% coherent motion directions, whereas the MT+-disturbed group showed impaired performance on discrimination of 40% coherent motion directions. These results suggest that V3A plays an important role in processing 100% coherent motion, whereas it is MT+ that plays a significant role in processing a noisy 40% coherent motion.Then, bo...

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Greater plasticity in lower-level than higher-level visual motion processing in a passive perceptual learning task

Cited by 193 publications

References 44 publications

Perceptual learning in clear displays optimizes perceptual expertise: Learning the limiting process

Perceptual learning in clear displays optimizes perceptual expertise: Learning the limiting process

Activations in Visual and Attention-Related Areas Predict and Correlate with the Degree of Perceptual Learning

V3A takes over a job of MT+ after training on a visual task

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