Abstract
Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.
Highlights
Excitation-inhibition (E:I) balance in the brain has been hypothesized to be atypical in many neuropsychiatric conditions (Rubenstein and Merzenich, 2003; Sohal and Rubenstein, 2019), including autism
In a bottom-up fashion, we first worked to identify potential biomarkers of E:I imbalance from neural time-series data such as local field potentials (LFPs)
Motivating our in-silico modeling of E:I effects on LFP and BOLD data, we note prior work by Gao and colleagues (Gao et al, 2017). This prior work simulated LFP time-series from non-interacting excitatory and inhibitory neuronal populations (Figure 1—figure supplement 1A) and showed that spectral properties such as the 1/f slope flatten with increasing E:I ratio (Figure 1—figure supplement 1B)
Summary
Excitation-inhibition (E:I) balance in the brain has been hypothesized to be atypical in many neuropsychiatric conditions (Rubenstein and Merzenich, 2003; Sohal and Rubenstein, 2019), including autism. Rubenstein and Merzenich originally suggested that some types of autism may be explained by an E:I imbalance that may lead to hyper-excitability in cortical circuitry and potentially enhanced levels of neuronal noise (Rubenstein and Merzenich, 2003). A majority of the literature about E:I balance in autism extends from investigations of prominent single gene mutations associated with autism and the animal model research around these genes (Sohal and Rubenstein, 2019; Nelson and Valakh, 2015). This leaves a significant gap in evaluating the E:I theory on a larger majority of the autistic population. While no one theory can fully explain all individuals with an autism diagnosis (Happeet al., 2006; Lombardo et al, 2019a), the E:I imbalance theory may have utility for understanding subtypes of autistic individuals (Lombardo et al, 2015; Lombardo et al, 2018a; Lombardo et al, 2019b)
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