- Key People:
- Eleanor J. Gibson
- Related Topics:
- perception
- learning
- adaptation
perceptual learning
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What is perceptual learning?
Perceptual learning is the process through which sensory systems enhance their ability to respond to stimuli through experience, whether from interacting with the environment or practicing specific sensory tasks. This learning results in changes in behavior and physiology, enabling improved discrimination of odors, musical pitches, and color shades.
Neural changes underlie perceptual learning mechanisms, reflecting the brain's coding of percepts during tasks. These changes include increased neural representation size, where more neurons respond to a stimulus as task performance improves. Another change is the sharpening of neuronal tuning functions, which enhances a neuron's sensitivity to stimulus variations. Perceptual systems also use changes in the relative timing of neuronal responses to represent learned information.
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How does perceptual learning help people improve their senses?
Perceptual learning enhances the ability of sensory systems to respond to stimuli through interactions with the environment and task-specific practice. This learning results in the improved ability to differentiate between odors, musical pitches, and color shades.
The mechanisms of perceptual learning are complex, involving changes in neural processing that fine-tune acuity. This process can modify neural connections in visual areas or cortical top-down connections from high-level areas. Neural changes include increased neural representation size, sharpened neuronal tuning functions, and altered timing of neuronal responses.
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What are some examples of perceptual learning in daily life?
Perceptual learning is the process through which sensory systems improve their ability to respond to stimuli through experience, enhancing the ability to distinguish between different odors, musical pitches, or shades of color.
Examples of perceptual learning in daily life include:
* Learning to distinguish musical notes: With practice, one can learn to identify musical pitches.
* Wine tasting: Developing the ability to differentiate between subtle flavors and aromas in wines.
* Detecting threats: Animals learn chemical cues associated with predators, enabling them to behave appropriately.
* Foraging: Honeybees learn to associate particular floral odors with the presence of nectar rewards, increasing their foraging efficiency.3 Britannica SourcesCreated from Britannica articles using AI. AI can make mistakes, so verify using Britannica articles. -
How do practice and experience change the way we notice things?
Through perceptual learning, practice and experience improve the ability of sensory systems to respond to stimuli. This process occurs via interaction with the environment and specific sensory tasks, leading to changes in behavior and physiology.
Neural changes, such as an increase in the size of neural representation, occur with practice. The number of neurons responding to a stimulus in a brain region increases as performance improves. Additionally, neurons become more selective, and the timing of responses made by sets of neurons can change.
Initially, perceptual learning was thought to be restricted to early development or changes in high-level cognitive processes; however, research has revealed that adult perceptual systems are highly mutable.
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Why is perceptual learning important in sports and music?
Perceptual learning is important in sports and music because it enhances the ability of sensory systems to respond to stimuli through experience. This learning process improves the discrimination of sensory information, such as distinguishing musical pitches. Neural changes, like increased neural representation size and sharpened neuronal tuning functions, reflect the brain's adaptation to represent percepts more efficiently. These changes enhance performance in sensory tasks.
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How do scientists study changes in the brain during perceptual learning?
Scientists study changes in the brain during perceptual learning using various approaches, primarily based on techniques in psychophysics and computational modeling.
Psychophysics, which studies the relationships between physical and sensory stimuli and mental processes, provides insights into perceptual learning. By observing the responses to carefully constructed stimuli, inferences can be made about the inner workings of a perceptual system.
Computational models like representation modification and reweighting also help understand the mechanisms behind perceptual learning. Representation modification suggests that learning is associated with changes in the properties of neurons in the early stages of visual processing. Reweighting, suggests that learning changes the strength of connections between cortical sensory representations and mid- or high-level brain areas.
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perceptual learning, process by which the ability of sensory systems to respond to stimuli is improved through experience. Perceptual learning occurs through sensory interaction with the environment as well as through practice in performing specific sensory tasks. The changes that take place in sensory and perceptual systems as a result of perceptual learning occur at the levels of behaviour and physiology. Examples of perceptual learning include developing an ability to distinguish between different odours or musical pitches and an ability to discriminate between different shades of colours.
Views of perceptual learning in humans
Perceptual learning in humans was once assumed to be a phenomenon restricted to the early stages of human development or attributable to changes in high-level cognitive processes. In the case of development, a great deal of neural tuning and reorganization takes place during early childhood, and many experiments have shown that perceptual experience (or lack thereof) during that time can play a large role in permanently shaping the properties of neural mechanisms. It was traditionally assumed that after that critical period of perceptual development had passed, neural mechanisms at the earliest stages of information processing were no longer plastic and thus could not be modified through experience with the world. In the case of perceptual learning in adults, it was generally assumed that changes in high-level cognitive processes, such as decision making, were responsible for improvements in perceptual performance with practice.
In the latter part of the 20th century, researchers demonstrated that human adult perceptual systems are in fact highly mutable. (For more information on the ability of neural pathways to change with learning, see neuroplasticity.) The discovery suggested that the properties of low-level cognitive processes, which involve areas of the brain that are the first to receive sensory information, could be reshaped by perceptual learning. Although it did not rule out the involvement of high-level cognitive processes in perceptual learning, the discovery prompted researchers to focus on simple sensory tasks and stimuli, which provide basic information about the changes that are occurring within a perceptual system as learning is taking place.
Various approaches, based largely on techniques in psychophysics and computational modeling, have been used in the study of perceptual learning. Psychophysics, which focuses on relationships between physical and sensory stimuli and mental processes, has provided especially useful insights into perceptual learning. Psychophysical techniques are designed to allow one to make inferences about the inner workings of a perceptual system by observing the responses that the system as a whole makes to carefully constructed stimuli. Psychophysical techniques have been used extensively to try to identify the kinds of cognitive processing changes that take place with practice in a wide variety of perceptual tasks.
Perceptual learning: vernier acuity
Many of the tasks that are used in psychophysics investigations involve relatively basic perceptual mechanisms. An example is vernier acuity, in which the viewer attempts to discern the alignment of two segments of a broken line. The amount of displacement that can be perceived between two lines in a vernier acuity test is less than the diameter of a single photoreceptor in the human eye. The level of acuity actually exceeds the physical capabilities of human photoreceptors and thus is an example of hyperacuity. Hyperacuity is associated with altered activity in the visual cortex of the brain, which helps explain why performance in vernier acuity can improve with practice.
In general, visual acuity training exhibits several unique characteristics. For example, depending on the type of training, enhanced acuity may be orientation specific, such that people who have been extensively trained with horizontal lines may not be able to transfer their learning to tests with vertical lines and vice versa. Initial performance with vertical lines may be only marginally better than initial performance with horizontal lines but can be improved to the same level that was achieved with horizontal lines. Also, depending on the type of acuity training undertaken, there sometimes is a similar degree of specificity for the position of training (e.g., training in the left visual field does not transfer to the right visual field) and the eye of training (e.g., training in the left eye does not transfer to training in the right eye).
In addition, similar to training for certain other sensory modalities, explicit accuracy feedback is not necessarily required for visual learning to take place, although the learning process is more gradual without feedback. There also are multiple phases to the learning process—an initial fast learning phase and a subsequent slower learning phase. The learning effects tend to be relatively long-lasting, with performance maintained for weeks or even months after initial training.
Mechanisms of perceptual learning
Although in some instances there is clear evidence that perceptual learning is associated with changes in cognitive processing, the mechanisms behind perceptual learning have been difficult to identify. It was thought, for example, that visual learning could not transfer across orientations, positions, or eyes. Hence, rather than occurring as a result of a generalized high-level learning process, visual learning was attributed to changes in neural processing that tuned acuity to a narrow range of orientations and a particular region of the visual field on the basis of input from one eye. As a result, the physiological locus of learning in a vernier acuity task was thought to lie in the primary visual cortex, where the first stages of visual cortical processing are carried out.
However, research conducted in the late 1990s and early 2000s indicated that perceptual learning can in some instances transfer between different visual tasks. The transfer of learning from one task to another depends on some degree of overlap in neural processing pathways as well as on the complexity of the visual training tasks involved. Scientists have presented various ideas on the mechanisms behind perceptual learning for visual tasks. Some of those ideas can be understood from the perspective of computational models. Examples of such models include representation modification and reweighting (or read-out modification). In representation modification, learning is associated with changes in the properties of neurons in the early stages of visual processing. Reweighting, on the other hand, suggests that learning is associated with changes in the strength of connections between cortical sensory representations and mid- or high-level brain areas. Still other models are based on different mechanisms, such as the modification by perceptual learning of neural connections in a single visual area or of cortical top-down connections that feed into early-stage processing areas from high-level areas.
In addition to visual acuity processing, psychophysical experiments have been applied to a wide array of tasks and stimuli involving other sensory modalities. Each of those applications is designed to uncover the underlying neural changes that take place with practice within a particular kind of perceptual processing. Examples of perceptual processes that have been investigated include visual motion detection, tactile spatial discrimination, and auditory frequency discrimination. Similar to vernier acuity, for other sensory modalities there tends to be a high degree of specificity of learning with regard to task and stimulus, though there are important exceptions to that trend.

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