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Bejjanki, V. R.

Publications and source records attributed to Bejjanki, V. R..

2 recordsLinked to original sources

How to read a baby's mind: Re-imagining fMRI for awake, behaving infants

Thousands of functional magnetic resonance imaging (fMRI) studies have provided important insight into the human brain. However, only a handful of these studies tested infants while they were awake, because of the significant and unique methodological challenges involved. We report our efforts over the past five years to address these challenges, with the goal of creating methods for infant fMRI that can reveal the inner workings of the developing, preverbal mind. We use these methods to collect and analyze two fMRI datasets obtained from infants during cognitive tasks, released publicly with this paper. In these datasets, we explore data quantity and quality, task-evoked activity, and preprocessing decisions to derive and evaluate recommendations for infant fMRI. We disseminate these methods by sharing two software packages that integrate infant-friendly cognitive tasks and behavioral monitoring with fMRI acquisition and analysis. These resources make fMRI a feasible and accessible technique for cognitive neuroscience in human infants.

neuroscience

Young children combine sensory cues with learned information in a statistically efficient manner: But task complexity matters

Human adults are adept at mitigating the influence of sensory uncertainty on task performance by integrating sensory cues with learned prior information, in a Bayes-optimal fashion. Previous research has shown that young children and infants are sensitive to environmental regularities, and that the ability to learn and use such regularities is involved in the development of several cognitive abilities. However, it has also been reported that children younger than 8 do not combine simultaneously available sensory cues in a Bayes-optimal fashion. Thus, it remains unclear whether, and by what age, children can combine sensory cues with learned regularities in an adult manner. Here, we examine the performance of 6-7-year old children when tasked with localizing a hidden target by combining uncertain sensory information with prior information learned over repeated exposure to the task. We demonstrate that 6-7-year olds learn task-relevant statistics at a rate on-par with adults, and like adults, are capable of integrating learned regularities with sensory information in a statistically efficient manner. We also show that variables such as task complexity can influence young childrens behavior to a greater extent than that of adults, leading their behavior to look sub-optimal. Our findings have important implications for how we should interpret failures in young childrens ability to carry out sophisticated computations. These failures need not be attributed to deficits in the fundamental computational capacity available to children early in development, but rather to ancillary immaturities in general cognitive abilities that mask the operation of these computations in specific situations.\n\nResearch HighlightsO_LIYoung children are sensitive to, and can learn, environmental regularities. Can they also utilize such learned regularities in a statistically efficient manner?\nC_LIO_LIWe demonstrate that 6-7-year olds are capable of learning and utilizing regularities in a statistically efficient fashion, and in a manner indistinguishable from adult behavior.\nC_LIO_LIHowever, variables such as task complexity can influence young childrens behavior to a greater extent than that of adults, leading their behavior to look sub-optimal.\nC_LIO_LIThese findings have important implications for how we should interpret failures in young childrens ability to carry out sophisticated computations.\nC_LI

neuroscience