Probabilistic Classification Task

Finn, Amy S.; Kalra, Priya B.; Goetz, Calvin; Leonard, Julia A.; Sheridan, Margaret A.; Gabrieli, John D. E.

doi:10.1037/t51677-000

Cited by 5 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The magnitude of their learned spatial bias was comparable to adults' learning, suggesting the presence of a highly functioning implicit spatial attention mechanism early in development. This is consistent with findings showing early mature implicit learning (Amso & Davidow, 2012;Aslin, 2017;Finn et al, 2016;Thomas et al, 2004).…”

Section: Discussionsupporting

confidence: 92%

“…Generally, implicit learning has been hypothesized to have five distinguishing features from explicit learning (Reber, 1989): (1) developmental invariance (Drag & Bieliauskas, 2010;Finn et al, 2016), (2) robustness to disease or injury (Reber, 2013;Reber, Martinex, & Weintraub, 2003), (3) specificity of transfer (Manza & Reber, 1997), (4) IQ independence (Atwell, Conners, & Merrill, 2003;Bussy, Charrin, Brun, Curie, & des Portes, 2011), and (5) secondary task independence (Curran & Keele, 1993;Hayes & Broadbent, 1988). That is, implicitly acquired knowledge tends to be inflexible, perceptually bound to the training context, and remains intact with regard to aging, developmental maturation, neurological/psychological disorder, and lack of attentional resources.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Statistical Learning of Target Location Probability in Children and Adults

S¹,

Sk²,

Hong³

2020

Preprint

View full text Add to dashboard Cite

Learning environmental regularities allows us to make predictions and guide behavior. Growing evidence of location probability learning (LPL) has shown that the statistical regularity of target locations affects spatial attention allocation. However, past studies on LPL have mostly focused on adults’ learning. To achieve a comprehensive understanding of the mechanism of this learning, we investigated the effect of target location probability on 5- to 9-year-old children’s visual search in comparison with that of adults. Both children and adults responded faster when the target appeared in the high probability “rich” quadrant than in the low probability “sparse” quadrants of the search space. This attentional bias toward the rich quadrant persisted even when the target was equally likely to appear in all four quadrants. Importantly, the magnitude of the bias was constant across various ages of participants and did not depend on individual differences in executive functions. Taken together, these results provide novel and converging evidence that implicit statistical learning of target locations occurs early in development and remains stable until early adulthood, which is a distinct developmental pattern from explicit goal-driven spatial attention learning.

show abstract

Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Statistical Learning of Target Location Probability in Children and Adults

S¹,

Sk²,

Hong³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The caudate nucleus matures early in development and is thought to be fully adult-like by 7 years-old (Casey et al, 2004). More generally, procedural memory and learning systems are thought to be fully adult-like by about 10 years old, in contrast to the protracted developmental course of declarative memory systems involved in the explicit system, such as the PFC and medial temporal lobe (Diamond, 2002;Finn et al, 2016).…”

Section: Information-integration Learning In Children and Adultsmentioning

confidence: 99%

Auditory information-integration category learning in young children and adults

Roark

Holt

2019

Journal of Experimental Child Psychology

View full text Add to dashboard Cite

Adults outperform children on category learning that requires selective attention to individual dimensions (rule-based categories) due to their more highly developed working memory abilities, but much less is known about developmental differences in learning categories that require integration across multiple dimensions (information-integration categories). The current study investigates auditory information-integration category learning in 5-7-year-old children (n = 34) and 18-25-year-old adults (n = 35). Adults generally outperformed children during learning. However, some children learned the categories well and used strategies similar to those of adults, assessed through decision bound computational models. The results demonstrate that information-integration learning ability continues to develop throughout at least middle childhood. These results have implications for the development of mechanisms that contribute to speech category learning.

show abstract

“…In the declarative-procedural memory framework, irregular forms are thought to be stored in declarative memory while the regular form is thought to be composed in real-time by the procedural memory system (Ullman et al 1997;Ullman 2001). Interestingly, a large body of evidence suggests that the procedural memory system is functioning at its peak during childhood, then progressively declines from adolescence through early adulthood (Fredriksson et al 2000;Schlaug 2001;Walton et al 1992;Wolansky et al 1999;Janacsek et al 2012), while the declarative memory system shows the opposite developmental pattern (Campbell and Spear 1972;DiGiulio et al 1994;Kail and Hagen 1977;Meudell 1983;Ornstein 1978;Siegler 1978;Finn et al 2016). That is, children's memory systems are in a maturational state that favors the formation of productive rules over storing individual forms.…”

Section: Why Does the Tolerance Principle Work For Children And Not Adults?mentioning

confidence: 99%

Testing the Tolerance Principle: Children form productive rules when it is more computationally efficient

Schuler¹,

Yang²,

Newport³

2021

Preprint

View full text Add to dashboard Cite

During language acquisition, children must learn when to generalize a pattern – applying it broadly and to new words (‘add –ed’ in English) – and when to restrict generalization, storing the pattern only with specific lexical items. But what governs when children will form productive rules during language acquisition? How do they determine when a pattern is widespread enough to generalize to novel words, and when a pattern should not extend beyond the cases they have observed in their input? One effort to quantify the conditions for generalization, the Tolerance Principle (Yang, 2016), has been shown to accurately predict children’s generalization behavior in dozens of corpus-based studies. The Tolerance Principle hypothesizes that a general rule will be formed when it is computationally more efficient than storing lexical forms individually. Here we test the Tolerance Principle in two artificial language experiments with children. In both experiments, we exposed children to a language with 9 novel nouns, some of which followed a regular pattern to form the plural (-ka) and some of which were exceptions to this rule. As predicted by the Tolerance Principle, in Experiment 1 we found that children exposed to 5 regular forms and 4 exceptions generalized, applying the regular form to 100% of novel test words. Children exposed to 3 regular forms and 6 exceptions did not extend the rule, even though the regular form was still the majority token in this condition. In Experiment 2, we found that children continued to behave categorically: either forming a productive rule (applying the regular form on all test trials) or using the regular form no more than predicted by chance. We found that the Tolerance Principle can be used to predict whether children will form a productive generalization or not based on each child’s individual vocabulary size. The Tolerance Principle appears to capture something fundamental about the way in which children form productive generalizations during language acquisition.

show abstract

Probabilistic Classification Task

Cited by 5 publications

References 0 publications

Statistical Learning of Target Location Probability in Children and Adults

Statistical Learning of Target Location Probability in Children and Adults

Auditory information-integration category learning in young children and adults

Testing the Tolerance Principle: Children form productive rules when it is more computationally efficient

Contact Info

Product

Resources

About