Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning

Bulf, Hermann; Brenna, Viola; Valenza, Eloisa; Johnson, Scott P.; Turati, Chiara

doi:10.3389/fpsyg.2015.01595

Cited by 27 publications

(28 citation statements)

References 33 publications

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“…Indeed, faces are the most salient and frequent visual stimulus category available in infants’ environment and familiar stimuli. As such, they enhance infants’ ability to detect and generalize abstract rules18263536. It is also noteworthy to consider that the posterior cortical activity in infants spread over adjacent but possibly functionally distinct cortical areas, suggesting that the CNV may embody functionally distinct anticipatory processes.…”

Section: Discussionmentioning

confidence: 99%

“…To such purpose, we collected the high-spatial resolution EEG signal in both 9-month-old infants and adults with an experimental paradigm purposely designed to automatically induce temporal expectancy of socially-relevant stimuli. The age of 9 months was purposely chosen because the ability to predict the occurrence of audiovisual events is stable at this age1718.…”

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confidence: 99%

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Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants

Mento

Valenza

2016

Sci Rep

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Anticipating events occurrence (Temporal Expectancy) is a crucial capacity for survival. Yet, there is little evidence about the presence of cortical anticipatory activity from infancy. In this study we recorded the High-density electrophysiological activity in 9 month-old infants and adults undergoing an audio-visual S1–S2 paradigm simulating a lifelike “Peekaboo” game inducing automatic temporal expectancy of smiling faces. The results indicate in the S2-preceding Contingent Negative Variation (CNV) an early electrophysiological signature of expectancy-based anticipatory cortical activity. Moreover, the progressive CNV amplitude increasing across the task suggested that implicit temporal rule learning is at the basis of expectancy building-up over time. Cortical source reconstruction suggested a common CNV generator between adults and infants in the right prefrontal cortex. The decrease in the activity of this area across the task (time-on-task effect) further implied an early, core role of this region in implicit temporal rule learning. By contrast, a time-on-task activity boost was found in the supplementary motor area (SMA) in adults and in the temporoparietal regions in infants. Altogether, our findings suggest that the capacity of the human brain to translate temporal predictions into anticipatory neural activity emerges ontogenetically early, although the underlying spatiotemporal cortical dynamics change across development.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants

Mento

Valenza

2016

Sci Rep

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“…Many studies have demonstrated that infants' RL is fully operative in the visual domain as well, even in the absence of social cues. For example, 7-month-olds can extract and generalize abstract rules from visual sequences of familiar objects, such as images of animals (Saffran et al, 2007) and upright faces (Bulf et al, 2015), but also from visual sequences of unfamiliar geometrical shapes, at least when sequences are presented from left to right (Bulf et al, 2017). Overall, these pieces of evidence show that RL is a domain-general mechanism that operates across sensory modalities since early infancy.…”

Section: Introductionmentioning

confidence: 89%

Infants’ Learning of Rule-Based Visual Sequences Predicts Language Outcome at 2 Years

et al. 2020

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The ability to learn and generalize abstract rules from sensory input-i.e., Rule Learning (RL)-is seen as pivotal to language development, and specifically to the acquisition of the grammatical structure of language. Although many studies have shown that RL in infancy is operating across different perceptual domains, including vision, no studies have directly investigated the link between infants' visual RL and later language acquisition. Here, we conducted a longitudinal study to investigate whether 7-montholds' ability to detect visual structural regularities predicts linguistic outcome at 2 years of age. At 7 months, infants were tested for their ability to extract and generalize ABB and ABA structures from sequences of visual shapes, and at 24 months their lexical and grammatical skills were assessed using the MacArthur-Bates CDI. Regression analyses showed that infants' visual RL abilities selectively predicted early grammatical abilities, but not lexical abilities. These results may provide the first evidence that RL mechanisms are involved in language acquisition, and suggest that RL abilities may act as an early neurocognitive marker for language impairments.

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“…Experience seems to mediate these effects. Learning is facilitated by the use of familiar rather than unfamiliar stimuli, such as animals rather than abstract shapes or upright faces rather than inverted faces (e.g., Bulf et al 2015, Saffran et al 2007). Experience can also inhibit learning.…”

Section: Statistics Of What? the Primitives Over Which Statistics mentioning

confidence: 99%

Infant Statistical Learning

Saffran

Kirkham

2018

Annu. Rev. Psychol.

324

211

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Perception involves making sense of a dynamic, multimodal environment. In the absence of mechanisms capable of exploiting the statistical patterns in the natural world, infants would face an insurmountable computational problem. Infant statistical learning mechanisms facilitate the detection of structure. These abilities allow the infant to compute across elements in their environmental input, extracting patterns for further processing and subsequent learning. In this selective review, we summarize findings that show that statistical learning is both a broad and flexible mechanism (supporting learning from different modalities across many different content areas) and input specific (shifting computations depending on the type of input and goal of learning). We suggest that statistical learning not only provides a framework for studying language development and object knowledge in constrained laboratory settings, but also allows researchers to tackle real-world problems, such as multilingualism, the role of ever-changing learning environments, and differential developmental trajectories.

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Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning

Cited by 27 publications

References 33 publications

Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants

Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants

Infants’ Learning of Rule-Based Visual Sequences Predicts Language Outcome at 2 Years

Infant Statistical Learning

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