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Journal Article 1: Immordino-Yang, M. H. (2016). Emotion, Sociality, and the Brain’s Default Mode Network. Policy Insights from the Behavioral and Brain Sciences, 3(2), 211-219. doi:10.1177/2372732216656869

Abstract: Education research—for example, on character, stereotype threat, and identity-based motivation—demonstrates that social and emotional factors influence students’ cognitive abilities and academic achievement. In parallel, recent advances in social-affective and cultural neuroscience reveal the social nature of human brain development and neural processing. Neuroscience can inform educational practice and policy by uncovering the mechanisms that may produce the observed social and emotional effects on learning. One major advance shows how the brain’s Default Mode Network supports social-emotional feelings and broader thought patterns associated with self-processing, identity, meaning-making, and future-oriented thought. This article introduces policy makers to this research and its implications for educational decision making.

Journal Article 2: Takeuchi, H.,& Kawashima, R. (2016). Neural mechanisms and children’s intellectual development: Multiple impacts of environmental factors. Neuroscientist, 22(6), 618-631.
doi: 10.1177/1073858415610294.

Abstract: Human psychometric intelligence can predict a number of important social and academic outcomes. Substantial parts of the variances of human intelligence and the brain volume supporting those abilities are explained by environmental factors, and during childhood, human brains have higher plasticity and also 60% of variance of intelligence that is explained by environmental factors. Here, we review the representative environmental factors known to affect human intellectual development during each developmental stage. We describe what is (and what is not) being investigated to determine how these factors affect human brain development through analyses of volumetrical and cortical structures. In conclusion, environmental factors that affect children’s intellectual development lead to three patterns of brain structural change. The first is global change in the brain structure, observed more often in the earlier phase of development. The second is structural changes concentrated in the medial prefrontal and adjacent areas and medial temporal areas, which are likely to be induced by stress in many cases. The third is sporadic region-specific change, likely to be primarily caused by use-dependent plasticity of the areas that is often observed in the later phase of development. These changes may underlie the alterations in children’s intellectual development that is induced by environmental factors.

Journal Article 3: Park, S., Lee, J.-M., Baik, Y., Kim, K., Yun, H. J., Kwon, H., .. . Kim, B.-N. (2015). A preliminary study of the effects of an arts education program on executive function, behavior, and brain structure in a sample of nonclinical school-aged children. Journal of Child Neurology, 30(13), 1757-1766.
doi: 10.1177/0883073815579710.

Abstract: The authors examined the effects of arts education on cognition, behavior, and brain of children. Twenty-nine nonclinical children participated in a 15-week arts education program that was composed of either creative movement or musical arts. Children completed the Wisconsin Card Sorting Test, clinical scales, and brain magnetic resonance imaging before and after the intervention. Following program completion, performances on the Wisconsin Card Sorting Test, the Children’s Depression Inventory scores, and conduct disorder scores were significantly improved. Furthermore, cortical thickness in the left postcentral gyrus and superior parietal lobule were increased, and the mean diffusivity values in the right posterior corona radiate and superior longitudinal fasciculus were decreased. Positive correlations between changes in cognitive measurements and changes in cortical thickness were observed. This preliminary study suggests a positive effect of arts education on executive functions in association with brain changes. However, these findings must be interpreted with caution due to the noncomparative study design.

Journal Article 4: Jäncke, L.,& Alahmadi, N. (2016). Resting state EEG in children with learning disabilities: An independent component analysis approach. Clinical EEG and Neuroscience, 47(1), 24-36.
doi: 10.1177/1550059415612622.

Abstract: In this study, the neurophysiological underpinnings of learning disabilities (LD) in children are examined using resting state EEG. We were particularly interested in the neurophysiological differences between children with learning disabilities not otherwise specified (LD-NOS), learning disabilities with verbal disabilities (LD-Verbal), and healthy control (HC) children. We applied 2 different approaches to examine the differences between the different groups. First, we calculated theta/beta and theta/alpha ratios in order to quantify the relationship between slow and fast EEG oscillations. Second, we used a recently developed method for analyzing spectral EEG, namely the group independent component analysis (gICA) model. Using these measures, we identified substantial differences between LD and HC children and between LD-NOS and LD-Verbal children in terms of their spectral EEG profiles. We obtained the following findings: (a) theta/beta and theta/alpha ratios were substantially larger in LD than in HC children, with no difference between LD-NOS and LD-Verbal children; (b) there was substantial slowing of EEG oscillations, especially for gICs located in frontal scalp positions, with LD-NOS children demonstrating the strongest slowing; (c) the estimated intracortical sources of these gICs were mostly located in brain areas involved in the control of executive functions, attention, planning, and language; and (d) the LD-Verbal children demonstrated substantial differences in EEG oscillations compared with LD-NOS children, and these differences were localized in language-related brain areas. The general pattern of atypical neurophysiological activation found in LD children suggests that they suffer from neurophysiological dysfunction in brain areas involved with the control of attention, executive functions, planning, and language functions. LD-Verbal children also demonstrate atypical activation, especially in language-related brain areas. These atypical neurophysiological activation patterns might provide a helpful guide for rehabilitation strategies to treat the deficiencies in these children with LD.

Journal Article 5: Chowdhury, R., Sharda, M., Foster, N. E. V., Germain, E., Tryfon, A., Doyle-Thomas, K., . . . Hyde, K. L. (in press). Auditory pitch perception in autism spectrum disorder is associated with nonverbal abilities. Perception.
doi:10.1177/0301006617718715.

Abstract: Atypical sensory perception and heterogeneous cognitive profiles are common features of autism spectrum disorder (ASD). However, previous findings on auditory sensory processing in ASD are mixed. Accordingly, auditory perception and its relation to cognitive abilities in ASD remain poorly understood. Here, children with ASD, and age- and intelligence quotient (IQ)-matched typically developing children, were tested on a low- and a higher level pitch processing task. Verbal and nonverbal cognitive abilities were measured using the Wechsler’s Abbreviated Scale of Intelligence. There were no group differences in performance on either auditory task or IQ measure. However, there was significant variability in performance on the auditory tasks in both groups that was predicted by nonverbal, not verbal skills. These results suggest that auditory perception is related to nonverbal reasoning rather than verbal abilities in ASD and typically developing children. In addition, these findings provide evidence for preserved pitch processing in school-age children with ASD with average IQ, supporting the idea that there may be a subgroup of individuals with ASD that do not present perceptual or cognitive difficulties. Future directions involve examining whether similar perceptual-cognitive relationships might be observed in a broader sample of individuals with ASD, such as those with language impairment or lower IQ.