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New technological devices, particularly those with touch screens, have become virtually omnipresent over the last decade. Practically from birth, children are now surrounded by smart phones and tablets. Despite being our constant companions, little is known about whether these tools can be used not only for entertainment, but also to collect reliable scientific data. Tablets may prove particularly useful for collecting behavioral data from those children (1–10 years), who are, for the most part, too old for studies based on looking times and too young for classical psychophysical testing. Here, we analyzed data from six studies that utilized touch screen tablets to deliver experimental paradigms in developmental psychology. In studies 1 and 2, we employed a simple sorting and recall task with children from the ages of 2–8. Study 3 (ages 9 and 10) extended these tasks by increasing the difficulty of the stimuli and adding a staircase-based perception task. A visual search paradigm was used in study 4 (ages 2–5), while 1- to 3-year-olds were presented with an extinction learning task in study 5. In study 6, we used a simple visuo-spatial paradigm to obtain more details about the distribution of reaction times on touch screens over all ages. We collected data from adult participants in each study as well, for comparison purposes. We analyzed these data sets in regard to four metrics: self-reported tablet usage, completeness of data, accuracy of responses and response times. In sum, we found that children from the age of two onwards are very capable of interacting with tablets, are able to understand the respective tasks and are able to use tablets to register their answers accordingly. Results from all studies reiterated the advantages of data collection through tablets: ease of use, high portability, low-cost, and high levels of engagement for children. We illustrate the great potential of conducting psychological studies in young children using tablets, and also discuss both methodological challenges and their potential solutions.

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Visual functions requiring interhemispheric transfer exhibit a long developmental trajectory up to age 12, which might be constrained by corpus callosum maturation. Here, we use electrophysiological and behavioral crossed-uncrossed differences (CUDs) in a visual Poffenberger paradigm to estimate the interhemispheric transfer time (IHTT)-a measure of corpus callosum maturation-in 7-year-old children and adults. Adults' electrophysiological CUDs were faster than 7-year-olds'. Behavioral CUDs did not differ and proved to be unreliable in a 6-month follow-up test. These findings suggest that the corpus callosum still undergoes development at the age of 7 that can only reliably be traced with neuroscientific methods.

27Axonal myelination is a key white matter maturation process as it increases conduction velocity, 28 synchrony, and reliability. While diffusion tensor imaging (DTI) is sensitive to myelination, it is also 29 sensitive to unrelated microstructural properties, thus hindering straightforward interpretations. Myelin 30 water imaging (MWI) provides a more reliable and direct in vivo measure of myelination. Although 31 early histological studies show protracted myelination from childhood to adulthood, reliable tract-32 specific in vivo evidence from MWI is still lacking. Here, we combine MWI and DTI tractography to 33 investigate myelination in middle childhood, late childhood, and adulthood in 18 major white matter 34 tracts. In the vast majority of major white matter tracts, myelin water fraction continued to increase 35 beyond late childhood. Our study provides first in vivo evidence for protracted myelination beyond late 36 childhood. 37 Keywords 38 development, maturation, child, gradient spin echo (GRASE), diffusion tensor imaging (DTI) 39 40

No abstract

Head motion remains a challenging confound in functional magnetic resonance imaging (fMRI) studies of both children and adults. Most pediatric neuroimaging labs have developed experience-based, child-friendly standards concerning e.g. the maximum length of a session or the time between mock scanner training and actual scanning. However, it is unclear which factors of child-friendly neuroimaging approaches are effective in reducing head motion. Here, we investigate three main factors including (i) time lag of mock scanner training to the actual scan, (ii) prior scan time, and (iii) task engagement in a dataset of 77 children (aged 6-13) and 64 adults (aged 18-35) using a multilevel modeling approach. In children, distributing fMRI data acquisition across multiple same-day sessions reduces head motion. In adults, motion is reduced after inside-scanner breaks. Despite these positive effects of splitting up data acquisition, motion increases over the course of a study as well as over the course of a run in both children and adults. Our results suggest that splitting up fMRI data acquisition is an effective tool to reduce head motion in general. At the same time, different ways of splitting up data acquisition benefit children and adults.HighlightsIn children, fMRI data acquisition split into multiple sessions reduces head motionIn adults, fMRI data acquisition split by inside-scanner breaks reduces head motionIn both children and adults, motion increases over the duration of a studyIn both children and adults, motion increases over the duration of a run

We investigated the ability to detect a face among other visual objects in a complex visual array in 3-, 4-, and 5-year-old children, as well as in adults. To this end, we used a visual search paradigm implemented on a touch-tablet device. Subjects ( N = 100) saw up to eighty 3 × 3 visual search arrays and had to find and tap upon a target—a face or a car—among eight objects that served as distractors. Our data revealed a relative face detection advantage, which did not differ in its extent between children and adults. This suggests that, beginning in young childhood and ending in adulthood, face detection performance advances as a consequence of other cognitive functions such as a general advance in visual search performance. Our study closes a gap in the knowledge about the development of face detection—as a prototype for social stimuli and their capacity to attract attention—from early to middle childhood.