Perceptual learning and representational learning in humans and animals

Fiser, József

doi:10.3758/lb.37.2.141

Cited by 30 publications

(34 citation statements)

References 64 publications

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“…Fiser andAslin (2002a, 2002b) found that following a familiarization phase in which novel shapes were combined into visual triplets, both infants (2002b) and adults (2002a) learned the visual triplets. These similar findings across different modalities are compatible with a claim that statistical learning is an amodal learning mechanism (Fiser, 2009;Kirkham, Slemmer, & Johnson, 2002) giving rise to higher-order primitives in both audition and vision (e.g., words and visual objects; TurkBrowne, Scholl, Chun, & Johnson, 2009). Statistical learning is thought to scaffold more complex types of regularity learning, such as those prevalent in natural languages (Aslin & Newport, 2012;Frost, 2012).…”

Section: Introductionmentioning

confidence: 99%

The role of cross-modal associations in statistical learning

Glicksohn

Cohen

2013

Psychon Bull Rev

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Our environment is richly structured, with objects producing correlated information within and across sensory modalities. A prominent challenge faced by our perceptual system is to learn such regularities. Here, we examined statistical learning and addressed learners' ability to track transitional probabilities between elements in the auditory and visual modalities. Specifically, we investigated whether cross-modal information affects statistical learning within a single modality. Participants were familiarized with a statistically structured modality (e.g., either audition or vision) accompanied by different types of cues in a second modality (e.g., vision or audition). The results revealed that statistical learning within either modality is affected by cross-modal information, with learning being enhanced or reduced according to the type of cue provided in the second modality.

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Section: Introductionmentioning

confidence: 99%

The role of cross-modal associations in statistical learning

Glicksohn

Cohen

2013

Psychon Bull Rev

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“…Both Fiser (2009) and Tsushima and Watanabe (2009) suggest that perceptual learning may take place outside…”

Section: Perceptual Learning Outside Of Awarenessmentioning

confidence: 99%

“…Tsushima and Watanabe (2009) define perceptual learning as an "improvement on a perceptual or sensory task b by practice or experience" (p. 126). Fiser (2009) states that the problem of perceptual learning is to understand "how humans and animals extract novel visual descript tions, features, or chunks from their visual environment and represent them" (p. 142). These definitions of perceptual learning seem much broader than those of Hall f (2009) and Mackintosh (2009).…”

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confidence: 99%

“…These inconsistencies will be described, and two possible resolutions will be suggested. Then this overview will evaluate Fiser's (2009) suggestion that a Bayesian approach provides a better account of learning than does associative link formation. Before concluding, a very brief comment will be made on Fiser's and Tsushima and Watanabe's claims to have observed perceptual learning outside of awareness.…”

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confidence: 99%

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Human and animal perceptual learning: Some common and some unique features

Mitchell

2009

Learning & Behavior

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A selective summary of the four contributions to this special issue of Learning & Behavior on perceptual r d learning is presented. Mackintosh and Hall propose an associative analysis of perceptual learning. It is argued that Tsushima and Watanabe's psychophysical evidence and Fiser's Bayesian-modeling work represent (in dif-f f ferent ways) challenges to the associative approach. Some tentative suggestions are explored with regard to how animal learning theorists might meet these challenges. Finally, the role of awareness in perceptual learning is b briefly examined.

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“…Using a process called visual statistical learning, or VSL, the visual system can both learn and use these statistical regularities (Chun & Jiang, 1998;Fiser & Aslin, 2001;Orbán, Fiser, Aslin, & Lengyel, 2008). When statistical regularities are present in a scene or a sequence, observers can learn these regularities Chun & Jiang, 1998;Fiser, 2009;Fiser & Aslin, 2001, 2002a, 2002bFiser, Scholl, & Aslin, 2007;Kirkham, Slemmer, & Johnson, 2002;Otsuka, Nishiyama, Nakahara, & Kawaguchi, 2013;Turk-Browne, Scholl, Chun & Johnson, 2009). …”

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confidence: 99%

Visual statistical learning of temporal structures at different hierarchical levels

Jun

Chong

2016

Atten Percept Psychophys

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Visual environments are complex. In order to process the complex information provided by visual environments, the visual system adopts strategies to reduce its complexity. One strategy, called visual statistical learning, or VSL, is to extract the statistical regularities from the environment. Another strategy is to use the hierarchical structure of a scene (e.g., the co-occurrence between local and global information). Through a series of experiments, this study investigated whether the utilization of the statistical regularities and the hierarchical structure could work together to reduce the complexity of a scene. In the familiarization phase, the participants were asked to passively view a stream of hierarchical scenes where the shapes were concurrently presented at the local and global levels. At each of the two levels there were temporal regularities among the three shapes, which always appeared in the same order. In the test phase, the participants judged the familiarity between 2 triplets, whose temporal regularities were either preserved or not. We found that the participants extracted the temporal regularities at each of the local and global levels (Experiment 1). The hierarchical structure influenced the ability to extract the temporal regularities (Experiment 2). Specifically, VSL was either enhanced or impaired depending on whether the hierarchical structure was informative or not. In summary, in order to process a complex scene, the visual system flexibly uses statistical regularities and the hierarchical structure of the scene.

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Perceptual learning and representational learning in humans and animals

Cited by 30 publications

References 64 publications

The role of cross-modal associations in statistical learning

The role of cross-modal associations in statistical learning

Human and animal perceptual learning: Some common and some unique features

Visual statistical learning of temporal structures at different hierarchical levels

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