Imbalance between neurophysiological excitation versus inhibition (E:I) has been theorized as a core pathophysiological mechanism of autism. However, a majority of the evidence behind the E:I theory comes from animal models of rare genetic mutations that account for only a small fraction of the autistic population. Scale-free metrics of neural time-series data could represent biomarkers for E:I imbalance and could enable a greater understanding of how E:I imbalance affects different types of autistic individuals and how such mechanisms relate to behavior. Here we show that a measure of scale-free dynamics, the Hurst exponent (H), measured in-vivo in resting state fMRI (rsfMRI) data, is a surrogate marker of E:I imbalance and differentially affects autistic males versus females. In-silico modeling of local field potentials (LFP) from recurrent networks of interacting excitatory and inhibitory neurons shows that increasing the E:I ratio by specifically enhancing excitation attenuates H and flattens the 1/f slope. These in-silico predictions are confirmed in-vivo with chemogenetic manipulations to enhance excitation of prefrontal cortex in mice. In humans, social brain areas such as ventromedial prefrontal cortex (vMPFC), show decreased H specifically in autistic males but not females. However, continuous variation in vMPFC H correlates with ability to behaviorally camouflage social-communicative difficulties in autistic females but not males. This work provides insight into how in-vivo neuroimaging readouts can be utilized to understand E:I imbalance in human clinical populations. E:I imbalance in social brain circuitry may differentially affect autistic males versus females and may help explain sexrelated differences in compensatory phenomena.