The brain is organized into intrinsic networks that support cognition and emotion. Functional magnetic resonance imaging (fMRI) has proven to be a useful tool in probing large-scale neural systems in living subjects. Using fMRI scans taken while subjects are at rest in a scanner, we can examine how these intrinsic systems are altered in developmentally abnormal individuals, who might struggle with a task. Researchers have suggested that autism spectrum disorders (ASD) are characterized by hyperconnectivity in intrinsic networks, but little is known about how network connectivity changes with development. In this study, we examined connectivity measures in ASD and typically developing (TD) groups (n = 496, ages 7-35) using fMRI scans retrieved from the Autism Brain Imaging Data Exchange repository. After screening for data quality, ASD and TD subjects were matched for age, motion, and intelligence. We calculated connectivity within five major intrinsic networks related to internally-directed thought, attention, and emotional processing (related to self and other). After preprocessing, we analyzed correlations between regions of interest within these networks to calculate individual within-network connectivity measures. We used linear regression to determine whether connectivity was predicted by age, diagnostic group, and their interaction. We found that age was related to decline in all connectivity measures in all five examined networks, possibly reflecting de-differentiation of network function. There was a selective difference by diagnostic group only in the “other” network. Subjects with ASD showed a steeper decline in connectivity with age (p = 0.045). Our results indicate that the “other” network may be a possible physiological marker of social symptom severity in autism, which we are now exploring. If so, it may be useful assessing effectiveness of intervention or therapy in autism.