To investigate children's inclusion of language-outgroup members, English-speaking children (8-9 years and 10-11 years of age, N = 57) made inclusion decisions while playing a simulated ball-tossing game, Cyberball, and while evaluating hypothetical scenarios involving language-outgroup members who wanted to play with their group. In the Cyberball game, the group norm was to exclude non-English-speaking peers, and participant tosses to a language-outgroup member (i.e., Spanish, Chinese, or Arabic speaking) were coded as a measure of behavioral inclusion. In the hypothetical scenarios, participants made prescriptive and descriptive judgments about their expectations regarding the inclusion of a language-outgroup member. They also evaluated their own and their group's inclusion likelihood. Results revealed that participants' evaluations of how acceptable exclusion was predicted their behavioral inclusion in the Cyberball game. Further, participants were more likely to think that the language-outgroup member should be included and less likely to think that the outgroup member would be included. They also differentiated between their own and their group's likelihood of including a language-outgroup member and reasoned about this decision by focusing on group functioning and language. In addition, there were age-related differences, with participants demonstrating greater inclusivity with age. The findings suggest the complexity of children's social cognition and the importance of providing them with a rich array of opportunities to play with language-outgroup members. (PsycINFO Database Record

Accurate analysis of scalp-recorded electrical activity requires the identification of electrode locations in 3D space. For example, source analysis of EEG/ERP (electroencephalogram, EEG; event-related-potentials, ERP) with realistic head models requires the identification of electrode locations on the head model derived from structural MRI recordings. Electrode systems must cover the entire scalp in sufficient density to discriminate EEG activity on the scalp and to complete accurate source analysis. The current study compares techniques for averaging electrode locations from 86 participants with the 128 channel “Geodesic Sensor Net” (GSN; EGI, Inc.), 38 participants with the 128 channel “Hydrocel Geodesic Sensor Net” (HGSN; EGI, Inc.), and 174 participants with the 81 channels in the 10-10 configurations. A point-set registration between the participants and an average MRI template resulted in an average configuration showing small standard errors, which could be transformed back accurately into the participants’ original electrode space. Average electrode locations are available for the GSN (86 participants), Hydrocel-GSN (38 participants), and 10-10 and 10-5 systems (174 participants)

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