utism spectrum disorder (ASD) is characterized by sociocommunicative impairments, repetitive behaviors, and restricted interests. 1 While viewed as a neurological disorder, its precise neural bases are not well understood. Growing evidence suggests that sociocommunicative, cognitive, and sensorimotor impairments are related to abnormalities of distributed networks, rather than of single brain loci. [2][3][4] Reports of atypical hemispheric asymmetries in ASD come from anatomical [5][6][7] and functional imaging studies. [8][9][10][11][12] Eyler and colleagues 13 observed atypical rightward asymmetry of receptive language activations during natural sleep in infants down to age 12.5 months, indicating that abnormal lateralization may predate language acquisition. However, all of the studies cited above focused on brain regions or stimuli specifically related to language. A recent study on gene expression in post mortem frontal cortex showed abnormalities in patterning pathways affecting lateralization in ASD, 14 possibly suggesting a broader impact on asymmetries even outside the language domain. While far from conclusive, these intriguing findings prompt the question whether atypical asymmetry could be a fundamental feature of brain organization in ASD. Indeed, theoretical considerations about possible left-hemisphere dysfunction 15,16 or, alternatively, predominant righthemisphere impairment 17,18 have a long history in autism research. However, these conjectures were largely based on limited behavioral findings, and conclusive imaging evidence beyond the language domain is lacking. Functional asymmetries related to nonverbal processing in ASD have received little attention, with only 2 studies reporting atypical left-hemisphere processing for motor tasks. 19,20 Moreover, functional studies have typically applied a priori models of task-driven activation effects. Since ASD is a pervasive developmental disorder whose neurofunctional bases are not well understood, hypothesis-driven approaches targeting single domains may, however, fail to provide comprehensive evidence because unexpected abnormalities may be missed.IMPORTANCE Autism spectrum disorder (ASD) is a brain-based pervasive developmental disorder, which-by growing consensus-is associated with abnormal organization of functional networks. Several previous studies of ASD have indicated atypical hemispheric asymmetries for language.OBJECTIVE To examine the asymmetry of functional networks using a data-driven approach for a comprehensive investigation of hemispheric asymmetry in ASD. DESIGN, SETTING, AND PARTICIPANTSThis cross-sectional study involved 24 children with ASD and 26 matched typically developing children at

Sleep disturbances are commonly reported in patients with bipolar I disorder (BPI) and are risk factors for mood episodes. In other populations, central nervous system (CNS) hyperarousal is associated with sleep initiation and maintenance problems, and CNS hypoarousal is associated with increased sleep drive. However, it is unclear whether CNS arousal levels are a useful index of sleep disruption in BPI. This study aimed to investigate daytime CNS arousal levels in relation to perceived sleep quality in BPI. Resting EEG, mood state, and self-reported sleep quality data were collected from 34 individuals with BPI. CNS hyperarousal was associated with pervasive poor subjective sleep quality including increased sleep disturbances, increased sleep latency, and reduced global sleep quality. CNS hypoarousal was associated with greater daytime sleepiness, indicating reduced arousal. These preliminary findings suggest that CNS arousal may be a useful index for identifying individuals at high risk for relapse into a mood episode. A limitation of this study is the use of self-report instruments for sleep quality assessment. Future research should investigate the temporal relationship of CNS arousal to sleep disturbances using objective measurements of sleep quality such as polysomnography. If these findings are replicated, measures of CNS arousals may allow for identification of high-risk patients with BPI.

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