Structural Basis of Large-Scale Functional Connectivity in the Mouse

Translational neuroimaging requires approaches and techniques that can bridge between multiple different species and disease states. One candidate method that offers insights into the brain's functional connectivity (FC) is resting-state fMRI (rs-fMRI). In both humans and nonhuman primates, patterns of FC (often referred to as the functional connectome) have been related to the underlying structural connectivity (SC; also called the structural connectome). Given the recent rise in preclinical neuroimaging of mouse models, it is an important question whether the mouse functional connectome conforms to the underlying SC. Here, we compared FC derived from rs-fMRI in female mice with the underlying monosynaptic structural connectome as provided by the Allen Brain Connectivity Atlas. We show that FC between interhemispheric homotopic cortical and hippocampal areas, as well as in cortico-striatal pathways, emerges primarily via monosynaptic structural connections. In particular, we demonstrate that the striatum (STR) can be segregated according to differential rs-fMRI connectivity patterns that mirror monosynaptic connectivity with isocortex. In contrast, for certain subcortical networks, FC emerges along polysynaptic pathways as shown for left and right STR, 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.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 (FC) derived from resting-state fMRI with gold standard structural connectivity measures based on tracer injections. In particular, we demonstrate high correspondence between FC measurements of cortico-cortical and cortico-striatal regions and their anatomical underpinnings. This work provides a critical foundation for studying the pathology of these circuits across mouse models and human patients

Deletion of autism risk gene Shank3 disrupts prefrontal connectivity

Mutations in the synaptic scaffolding protein Shank3 are a major cause of autism, and are associated with prominent intellectual and language deficits. However, the neural mechanisms whereby SHANK3 deficiency affects higher order socio-communicative functions remain unclear. Using high-resolution functional and structural MRI in adult male mice, here we show that loss of Shank3 (Shank3B-/-) results in disrupted local and long-range prefrontal and fronto-striatal functional connectivity. We document that prefrontal hypo-connectivity is associated with reduced short-range cortical projections density, and reduced gray matter volume. Finally, we show that prefrontal disconnectivity is predictive of social communication deficits, as assessed with ultrasound vocalization recordings. Collectively, our results reveal a critical role of SHANK3 in the development of prefrontal anatomy and function, and suggest that SHANK3 deficiency may predispose to intellectual disability and socio-communicative impairments via dysregulation of higher-order cortical connectivity

Homozygous loss of autism-risk gene CNTNAP2 results in reduced local and long-range prefrontal functional connectivity

Functional connectivity aberrancies, as measured with resting-state fMRI (rsfMRI), have been consistently observed in the brain of autism spectrum disorders (ASD) patients. However, the genetic and neurobiological underpinnings of these findings remain unclear. Homozygous mutations in Contactin Associated Protein-like 2 (CNTNAP2), a neurexin-related cell-adhesion protein, are strongly linked to autism and epilepsy. Here we used rsfMRI to show that homozygous mice lacking Cntnap2 exhibit reduced long-range and local functional connectivity in prefrontal and midline brain “connectivity hubs”. Long-range rsfMRI connectivity impairments affected heteromodal cortical regions and were prominent between frontoposterior components of the mouse default-mode network (DMN), an effect that was associated with reduced social investigation, a core “autism trait” in mice. Notably, viral tracing revealed reduced frequency of prefrontal-projecting neural clusters in the cingulate cortex of Cntnap2-/- mutants, suggesting a possible contribution of defective mesoscale axonal wiring to the observed functional impairments. Macroscale cortico-cortical white matter organization appeared to be otherwise preserved in these animals. These findings reveal a key contribution of ASD-associated gene CNTNAP2 in modulating macroscale functional connectivity, and suggest that homozygous loss-of-function mutations in this gene may predispose to neurodevelopmental disorders and autism through a selective dysregulation of connectivity in integrative prefrontal areas

The claustrum is a highway not a hub : organizing principles of claustrocortical synaptic transmission

The claustrum (CLA) is a brain nucleus wedged between the cortex and striatum. The behaviors it has been implicated in include consciousness, attention, memory and salience detection; dysfunction of CLA circuits is associated with schizophrenia, epilepsy, parkinsonism and disrupted consciousness. While previous research has focused on the gross anatomy of the CLA, it is the functional communication of the CLA with other brain regions that generates behavioral output. Understanding CLA functional connectivity will bring us closer to understanding how the CLA is involved in different behaviors and how these dysfunctions can be remedied. The anterior cingulate cortex-projecting (CLA-ACC) neuron population was used as a model to investigate claustrocortical synaptic transmission. This thesis proposes that the CLA is organized as a highway for connections between brain regions. Paper I revealed that the CLA is organized as functional modules. Specifically, it showed that CLA-ACC neurons receive multicortical input biased towards frontal & limbic cortices rather than sensory cortices, and that CLA-ACC neurons could be segmented into at least two cortical targeting systems. An insular-claustrum- anterior cingulate cortex circuit, which may be the substrate underpinning the Salience Network, was also identified. These findings support feedforward inhibition as a mechanism of action within the CLA. Paper II extended the concept of topological selectivity in the CLA to the single- cell level. Topological selectivity was previously known to exist at a population level. Characterization of the intrinsic electrophysiological properties of individual CLA-ACC neurons revealed four types of CLA-ACC populations. These CLA- ACC neurons were distributed heterogeneously with one type predominant in the anterior and posterior CLA and a second type prominent in the middle of the CLA. Paper III identified the cell-type and layer-specific cortical targets of the CLA. It showed that CLA-ACC neurons provide excitatory monosynaptic input to all layers of the ACC and that different neuron populations receive CLA input in a layer-dependent fashion. From these data, Paper III derived a scheme of CLA targets within a cortex. The findings from this thesis can be summarized using a transportation analogy. Although commonly described as a hub for cortical inputs and outputs, the CLA is likely organized as a collection of highways. A significantly large input should arrive within a small time-window to generate action potentials and enable downstream signal propagation. This is akin to a toll booth with a high toll fee that must be paid-in-full, without delays, before a vehicle can pass through. Projection neurons directed to the same cortical region may have different cell/layer targets. This is comparable to different vehicles on the same highway ending up in different destinations. The findings in this thesis add to our understanding of CLA functional organization by suggesting that any input received by the CLA must be sufficiently strong in order to overcome FFI and for the signal to be propagated. This implies that only input of ethological relevance is processed. Such a mechanism could underlie CLA action across behaviors. This thesis is divided into 6 chapters. Chapter 1 is a preamble. Chapter 2 encompasses the state-of-the-art in CLA and describes the gaps in knowledge that this thesis aims to fill. Chapter 3 clarifies the aims of this thesis. Chapter 4 provides an overview of the methods used. Chapter 5 presents and discusses the main results. Chapter 6 explores the main conclusions from this work. Manuscripts and publications are appended after

Vascular cognitive impairment in the mouse reshapes visual, spatial network functional connectivity

Connectome analysis of neuroimaging data is a rapidly expanding field to identify disease specific biomarkers. Structural diffusion MRI connectivity has been useful in individuals with radiological features of small vessel disease, such as white matter hyperintensities. Global efficiency, a network metric calculated from the structural connectome, is an excellent predictor of cognitive decline. To dissect the biological underpinning of these changes, animal models are required. We tested whether the structural connectome is altered in a mouse model of vascular cognitive impairment. White matter damage was more pronounced by 6 compared to 3 months. Global efficiency remained intact, but the visual association cortex exhibited increased structural connectivity with other brain regions. Exploratory resting state functional MRI connectivity analysis revealed diminished default mode network activity in the model compared to shams. Further perturbations were observed in a primarily cortical hub and the retrosplenial and visual cortices, and the hippocampus were the most affected nodes. Behavioural deficits were observed in the cued water maze, supporting the suggestion that the visual and spatial memory networks are affected. We demonstrate specific circuitry is rendered vulnerable to vascular stress in the mouse, and the model will be useful to examine pathophysiological mechanisms of small vessel disease

Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

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

Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

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

Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

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

Identifying reproducible resting state networks and functional connectivity alterations following chronic restraint stress in anaesthetized rats

BackgroundResting-state functional MRI (rs-fMRI) in rodent models have the potential to bridge invasive experiments and observational human studies, increasing our understanding of functional alterations in the brains of patients with depression. A major limitation in current rodent rs-fMRI studies is that there has been no consensus on healthy baseline resting-state networks (RSNs) that are reproducible in rodents. Therefore, the present study aimed to construct reproducible RSNs in a large dataset of healthy rats and then evaluate functional connectivity changes within and between these RSNs following a chronic restraint stress (CRS) model within the same animals.MethodsA combined MRI dataset of 109 Sprague Dawley rats at baseline and after two weeks of CRS, collected during four separate experiments conducted by our lab in 2019 and 2020, was re-analysed. The mICA and gRAICAR toolbox were first applied to detect optimal and reproducible ICA components and then a hierarchical clustering algorithm (FSLNets) was applied to construct reproducible RSNs. Ridge-regularized partial correlation (FSLNets) was used to evaluate the changes in the direct connection between and within identified networks in the same animals following CRS.ResultsFour large-scale networks in anesthetised rats were identified: the DMN-like, spatial attention-limbic, corpus striatum, and autonomic network, which are homologous across species. CRS decreased the anticorrelation between DMN-like and autonomic network. CRS decreased the correlation between amygdala and a functional complex (nucleus accumbens and ventral pallidum) in the right hemisphere within the corpus striatum network. However, a high individual variability in the functional connectivity before and after CRS within RSNs was observed.ConclusionThe functional connectivity changes detected in rodents following CRS differ from reported functional connectivity alterations in patients with depression. A simple interpretation of this difference is that the rodent response to CRS does not reflect the complexity of depression as it is experienced by humans. Nonetheless, the high inter-subject variability of functional connectivity within networks suggests that rats demonstrate different neural phenotypes, like humans. Therefore, future efforts in classifying neural phenotypes in rodents might improve the sensitivity and translational impact of models used to address aetiology and treatment of psychiatric conditions including depression