Jennifer D. Whitesell

Neurodegenerative tauopathies are hypothesized to propagate via brain networks. This is uncertain because we have lacked precise network resolution of pathology. We therefore developed whole-brain staining methods with anti-p-tau nanobodies and imaged in 3D PS19 tauopathy mice, which have pan-neuronal expression of full-length human tau containing the P301S mutation. We analyzed patterns of p-tau deposition across established brain networks at multiple ages, testing the relationship between structural connectivity and patterns of progressive pathology. We identified core regions with early tau deposition, and used network propagation modeling to determine the link between tau pathology and connectivity strength. We discovered a bias towards retrograde network-based propagation of tau. This novel approach establishes a fundamental role for brain networks in tau propagation, with implications for human disease. One-Sentence Summary: Novel whole brain imaging of p-tau deposition reveals retrograde-dominant network propagation in a tauopathy mouse model.

The relationship between brainwide functional decline and accumulation of pathological protein aggregates in Alzheimer’s disease (AD) is complex and not well understood. A set of highly interconnected cortical regions known as the default mode network (DMN) exhibits selective vulnerability to both functional decline and amyloid beta (A β ) plaques in early AD. One possibility is that early A β accumulation in the DMN drives vulnerability. However, it is unknown whether there is something intrinsic to neuronal projections within the DMN that biases these circuits towards dysfunction. Here we directly test this hypothesis using long-term recordings of the spiking activity of ensembles of single units in freely behaving mice characterized by global cortical and hippocampal A β burden (APP/PS1). Specifically, we track the interactions of a population of neurons within a DMN region and two additional populations that comprise monosynaptic targets, one within and the other outside the DMN. In addition, we record single neurons in hippocampus and examine interactions between the in-DMN and out-DMN cortical circuits triggered on hippocampal sharp-wave ripples, stereotyped hippocampal events that contribute to memory consolidation in the cortex. We examine the statistics of local activity as well as inter-regional communication in a region, genotype, and brain-state dependent manner. Our data reveal dysfunction restricted to the in-DMN projecting circuit. In contrast, communication along neuronal projections that originate in the DMN but target an out-DMN population is equivalent in APP/PS1 and WT mice. Circuit dysfunction is most evident throughout sleep, and particularly disrupted within sharp-wave ripples. Summarily, our results indicate that, even in the face of transgene overexpression and widespread A β , there is distinct intrinsic and selective vulnerability. This vulnerability to amyloidosis is circuit-specific and conditioned on target, and neither source nor amyloid burden. These data raise the possibility that neuronal function in the DMN is not universally vulnerable; DMN subnetworks whose interactions involve targets outside the DMN may be resilient to A β .

Understanding mechanisms of immune regulation is key to developing immunotherapies for autoimmunity and cancer. We examined the role of mononuclear phagocytes during peripheral T cell regulation in type 1 diabetes and melanoma. MERTK expression and activity in mononuclear phagocytes in the pancreatic islets promoted islet T cell regulation, resulting in reduced sensitivity of T cell scanning for cognate antigen in prediabetic islets. MERTK-dependent regulation led to reduced T cell activation and effector function at the disease site in islets and prevented rapid progression of type 1 diabetes. In human islets, MERTK-expressing cells were increased in remaining insulin-containing islets of type 1 diabetic patients, suggesting that MERTK protects islets from autoimmune destruction. MERTK also regulated T cell arrest in melanoma tumors. These data indicate that MERTK signaling in mononuclear phagocytes drives T cell regulation at inflammatory disease sites in peripheral tissues through a mechanism that reduces the sensitivity of scanning for antigen leading to reduced responsiveness to antigen.

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically¹. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset—part of the Allen Brain Observatory²—that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas³. We find that four classical hierarchical measures—response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale—are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.

High-resolution mapping of the mouse axonal connectome reveals new foundational wiring principles of the mammalian brain.

The evolutionarily conserved default mode network (DMN) is characterized by temporally correlated activity between brain regions during resting states. The DMN has emerged as a selectively vulnerable network in multiple disorders, so understanding its anatomical composition will provide fundamental insight into how its function is impacted by disease. Reproducible rodent analogs of the human DMN offer an opportunity to investigate the underlying brain regions and structural connectivity (SC) with high spatial and cell type resolution. Here, we performed systematic analyses using mouse resting state functional magnetic resonance imaging to identify the DMN and whole brain axonal tracing data, co-registered to the 3D Allen Mouse Common Coordinate Framework reference atlas. We identified the specific, predominantly cortical, brain regions comprising the mouse DMN and report preferential SC between these regions. Next, at the cell class level, we report that cortical layer (L) 2/3 neurons in DMN regions project almost exclusively to other DMN regions, whereas L5 neurons project to targets both in and out of the DMN. We then test the hypothesis that in- and out-DMN projection patterns originate from distinct L5 neuron sub-classes using an intersectional viral tracing strategy to label all the axons from neurons defined by a single target. In the ventral retrosplenial cortex, a core DMN region, we found two L5 projection types related to the DMN and mapped them to unique transcriptomically-defined cell types. Together, our results provide a multi-scale description of the anatomical correlates of the mouse DMN.

Fine-grained descriptions of brain connectivity are fundamental for understanding how neural information is processed and relayed across spatial scales. Prior investigations of the mouse brain connectome have employed discrete anatomical parcellations, limiting spatial resolution and potentially concealing network attributes critical to the organization of the mammalian connectome. Here we provide a voxel-level description of the network and hierarchical structure of the directed mouse connectome, unconstrained by regional partitioning. We show that integrative hub regions can be directionally segregated into neural sinks and sources, defining a hierarchical axis. We describe a set of structural communities that spatially reconstitute previously described fMRI networks of the mouse brain, and document that neuromodulatory nuclei are strategically wired as critical orchestrators of inter-modular and network communicability. Notably, like in primates, the directed mouse connectome is organized along two superimposed cortical gradients reflecting unimodal-transmodal functional processing and a modality-specific sensorimotor axis. These structural features can be related to patterns of intralaminar connectivity and to the spatial topography of dynamic fMRI brain states, respectively. Together, our results reveal a high-resolution structural scaffold linking mesoscale connectome topography to its macroscale functional organization, and create opportunities for identifying targets of interventions to modulate brain function in a physiologically-accessible species.

Knowledge of mesoscopic brain connectivity is important for understanding inter- and intraregion information processing. Models of structural connectivity are typically constructed and analyzed with the assumption that regions are homogeneous. We instead use the Allen Mouse Brain Connectivity Atlas to construct a model of whole-brain connectivity at the scale of 100 μm voxels. The data consist of 428 anterograde tracing experiments in wild type C57BL/6J mice, mapping fluorescently labeled neuronal projections brain-wide. Inferring spatial connectivity with this dataset is underdetermined, since the approximately 2 × 10⁵ source voxels outnumber the number of experiments. To address this issue, we assume that connection patterns and strengths vary smoothly across major brain divisions. We model the connectivity at each voxel as a radial basis kernel-weighted average of the projection patterns of nearby injections. The voxel model outperforms a previous regional model in predicting held-out experiments and compared with a human-curated dataset. This voxel-scale model of the mouse connectome permits researchers to extend their previous analyses of structural connectivity to much higher levels of resolution, and it allows for comparison with functional imaging and other datasets.

A variety of Alzheimer's disease (AD) mouse models overexpress mutant forms of human amyloid precursor protein (APP), producing high levels of amyloid β (Aβ) and forming plaques. However, the degree to which these models mimic spatiotemporal patterns of Aβ deposition in brains of AD patients is unknown. Here, we mapped the spatial distribution of Aβ plaques across age in three APP‐overexpression mouse lines (APP/PS1, Tg2576, and hAPP‐J20) using in vivo labeling with methoxy‐X04, high throughput whole brain imaging, and an automated informatics pipeline. Images were acquired with high resolution serial two‐photon tomography and labeled plaques were detected using custom‐built segmentation algorithms. Image series were registered to the Allen Mouse Brain Common Coordinate Framework, a 3D reference atlas, enabling automated brain‐wide quantification of plaque density, number, and location. In both APP/PS1 and Tg2576 mice, plaques were identified first in isocortex, followed by olfactory, hippocampal, and cortical subplate areas. In hAPP‐J20 mice, plaque density was highest in hippocampal areas, followed by isocortex, with little to no involvement of olfactory or cortical subplate areas. Within the major brain divisions, distinct regions were identified with high (or low) plaque accumulation; for example, the lateral visual area within the isocortex of APP/PS1 mice had relatively higher plaque density compared with other cortical areas, while in hAPP‐J20 mice, plaques were densest in the ventral retrosplenial cortex. In summary, we show how whole brain imaging of amyloid pathology in mice reveals the extent to which a given model recapitulates the regional Aβ deposition patterns described in AD.

A variety of Alzheimer’s disease (AD) mouse models overexpress mutant forms of human amyloid precursor protein (APP), producing high levels of amyloid β (Aβ) and forming plaques However, the degree to which these models mimic spatiotemporal patterns of Aβ deposition in brains of AD patients is unknown. Here, we mapped the spatial distribution of Aβ plaques across ages in three APP-overexpression mouse lines (APP/PS1, Tg2576, hAPP-J20) using in vivo labeling with methoxy-X04, high throughput whole brain imaging, and an automated informatics pipeline. Images were acquired with high resolution serial 2-photon tomography and labeled plaques were detected using custom-built segmentation algorithms. Image series were registered to the Allen Mouse Brain Common Coordinate Framework, a 3D reference atlas, enabling automated brain-wide quantification of plaque density, number, and location. In both APP/PS1 and Tg2576 mice, plaques were identified first in isocortex, followed by olfactory, hippocampal, and cortical subplate areas. In hAPP-J20 mice, plaque density was highest in hippocampal areas, followed by isocortex, with little to no involvement of olfactory or cortical subplate areas. Within the major brain divisions, distinct regions were identified with high (or low) plaque accumulation; e.g. , the lateral visual area within the isocortex of APP/PS1 mice had relatively higher plaque density compared with other cortical areas, while in hAPP-J20 mice, plaques were densest in the ventral retrosplenial cortex. In summary, we show how whole brain imaging of amyloid pathology in mice reveals the extent to which a given model recapitulates the regional Aβ deposition patterns described in AD.