White matter matures with age and is important for the efficient transmission of neuronal signals. Consequently, white matter growth may underlie the development of cognitive processes important for learning, including the speed of information processing. To dissect the relationship between white matter structure and information processing speed, we administered a reaction time task (finger abduction in response to visual cue) to 27 typically developing, right-handed children aged 4 to 13. Magnetoencephalography and Diffusion Tensor Imaging were used to delineate white matter connections implicated in visual-motor information processing. Fractional anisotropy (FA) and radial diffusivity (RD) of the optic radiation in the left hemisphere, and FA and mean diffusivity (MD) of the optic radiation in the right hemisphere changed significantly with age. MD and RD decreased with age in the right inferior fronto-occipital fasciculus, and bilaterally in the cortico-spinal tracts. No age-related changes were evident in the inferior longitudinal fasciculus. FA of the cortico-spinal tract in the left hemisphere and MD of the inferior fronto-occipital fasciculus of the right hemisphere contributed uniquely beyond the effect of age in accounting for reaction time performance of the right hand. Our findings support the role of white matter maturation in the development of information processing speed. (JINS, 2013, 19, 1–14)

Impairments in visual motion perception and use of visual motion information to guide behavior have been reported in autism, but the brain alterations underlying these abnormalities are not well characterized. We performed functional magnetic resonance imaging (fMRI) studies to investigate neural correlates of impairments related to visual motion processing. Sixteen high-functioning individuals with autism and 14 age and IQ-matched typically developing individuals completed two fMRI tasks using passive viewing to examine bottom–up responses to visual motion and visual pursuit tracking to assess top–down modulation of visual motion processing during sensorimotor control. The autism group showed greater activation and faster hemodynamic decay in V5 during the passive viewing task and reduced frontal and V5 activation during visual pursuit. The observations of increased V5 activation and its faster decay during passive viewing suggest alterations in local V5 circuitries that may be associated with reduced GABAergic tone and inhibitory modulation. Reduced frontal and V5 activation during active pursuit suggest reduced top–down modulation of sensory processing. These results suggest that both local intrinsic abnormalities in V5 and more widely distributed network level abnormalities are associated with visual motion processing in autism. (JINS, 2014, 20, 113–122)

The aim of this study was to assess cognitive functioning in children with type 1 diabetes (T1D) and examine whether glycemic history influences cognitive function. Neuropsychological evaluation of 216 children (healthy controls, n = 72; T1D, n = 144) ages 4–10 years across five DirecNet sites. Cognitive domains included IQ, Executive Functions, Learning and Memory, and Processing Speed. Behavioral, mood, parental IQ data, and T1D glycemic history since diagnosis were collected. The cohorts did not differ in age, gender or parent IQ. Median T1D duration was 2.5 years and average onset age was 4 years. After covarying age, gender, and parental IQ, the IQ and the Executive Functions domain scores trended lower (both p = .02, not statistically significant adjusting for multiple comparisons) with T1D relative to controls. Children with T1D were rated by parents as having more depressive and somatic symptoms (p < .001). Learning and memory (p = .46) and processing speed (p = .25) were similar. Trends in the data supported that the degree of hyperglycemia was associated with Executive Functions, and to a lesser extent, Child IQ and Learning and Memory. Differences in cognition are subtle in young children with T1D within 2 years of onset. Longitudinal evaluations will help determine whether these findings change or become more pronounced with time. (JINS, 2014, 20, 238–247)