Significance: The brain is organized into processing streams, along which incoming sensory information is processed at increasingly abstract and integrative levels. This specialization of function is thought to be underpinned by corresponding changes in the brain’s local circuitry. Here we combine a wide range of measurements across the mouse brain, including the expression of genes, cell densities, and axonal connectivity, to show that the properties of local circuits of the mouse brain vary along putative processing streams in a similar way to the primate brain. This similarity across species points to common mechanisms through which mammalian brains may process information.

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.

Translational neuroimaging requires approaches and techniques that can bridge between multiple different species and disease states. One candidate method, which offers insights into the brain9s functional connectivity (FC), is resting state fMRI (rs-fMRI). In both humans and non-human primates, patterns of functional connectivity (often referred to as the functional connectome) have been related to the underlying structural connectivity (structural connectome). Given the recent rise in pre-clinical neuroimaging of mouse models it is an important question whether the mouse functional connectome conforms to the underlying structural connectivity. Here, we compared FC derived from rs-fMRI in female mice to the underlying monosynaptic structural connectome as provided by the Allen Brain Connectivity Atlas. We show that FC between inter-hemispheric homotopic cortical and hippocampal areas, as well as in cortical-striatal pathways, emerge primarily via monosynaptic structural connections. In particular, we demonstrate that the striatum can be segregated according to differential rs-fMRI connectivity patterns that mirror monosynaptic connectivity with isocortex. By contrast, for certain subcortical networks, FC emerges along polysynaptic pathways as shown for left and right striatum, which do not share direct anatomical connections, but high FC is putatively driven by a top-down cortical control. Finally, we show that FC involving cortico-thalamic pathways is limited, possibly confounded by the effect of anesthesia, small regional size and tracer injection volume. These findings provide a critical foundation for using rs-fMRI connectivity as a translational tool to study complex brain circuitry interactions and their pathology due to neurological or psychiatric diseases across species. SIGNIFICANCE STATEMENT A comprehensive understanding of how the anatomical architecture of the brain, often referred to as the “connectome”, corresponds to its function is arguably one of the biggest challenges for understanding the brain and its pathologies. Here we use the mouse as a model for comparing functional connectivity derived from resting-state fMRI with gold standard structural connectivity measures based on tracer injections. In particular, we demonstrate high correspondence between functional connectivity measurements of cortico-cortico and cortico-striatal and their anatomical underpinnings. This work provides a critical foundation for studying the pathology of these circuits across mouse models and human patients.