The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas

Tissue clearing and 3D imaging in developmental biology

Tissue clearing increases the transparency of late developmental stages and enables deep imaging in fixed organisms. Successful implementation of these methodologies requires a good grasp of sample processing, imaging and the possibilities offered by image analysis. In this Primer, we highlight how tissue clearing can revolutionize the histological analysis of developmental processes and we advise on how to implement effective clearing protocols, imaging strategies and analysis methods for developmental biology.

Single-cell and single-nucleus RNA-seq uncovers shared and distinct axes of variation in dorsal LGN neurons in mice, non-human primates, and humans

Abundant evidence supports the presence of at least three distinct types of thalamocortical (TC) neurons in the primate dorsal lateral geniculate nucleus (dLGN) of the thalamus, the brain region that conveys visual information from the retina to the primary visual cortex (V1). Different types of TC neurons in mice, humans, and macaques have distinct morphologies, distinct connectivity patterns, and convey different aspects of visual information to the cortex. To investigate the molecular underpinnings of these cell types, and how these relate to differences in dLGN between human, macaque, and mice, we profiled gene expression in single nuclei and cells using RNA-sequencing. These efforts identified four distinct types of TC neurons in the primate dLGN: magnocellular (M) neurons, parvocellular (P) neurons, and two types of koniocellular (K) neurons. Despite extensively documented morphological and physiological differences between M and P neurons, we identified few genes with significant differential expression between transcriptomic cell types corresponding to these two neuronal populations. Likewise, the dominant feature of TC neurons of the adult mouse dLGN is high transcriptomic similarity, with an axis of heterogeneity that aligns with core vs. shell portions of mouse dLGN. Together, these data show that transcriptomic differences between principal cell types in the mature mammalian dLGN are subtle relative to the observed differences in morphology and cortical projection targets. Finally, alignment of transcriptome profiles across species highlights expanded diversity of GABAergic neurons in primate versus mouse dLGN and homologous types of TC neurons in primates that are distinct from TC neurons in mouse.

Neuronal Cell-type Engineering by Transcriptional Activation

Gene activation with the CRISPR-Cas system has great implications in studying gene function, controlling cellular behavior, and modulating disease progression. In this review, we survey recent studies on targeted gene activation and multiplexed screening for inducing neuronal differentiation using CRISPR-Cas transcriptional activation (CRISPRa) and open reading frame (ORF) expression. Critical technical parameters of CRISPRa and ORF-based strategies for neuronal programming are presented and discussed. In addition, recent progress on in vivo applications of CRISPRa to the nervous system are highlighted. Overall, CRISPRa represents a valuable addition to the experimental toolbox for neuronal cell-type programming.

An optical flow based left-invariant metric for natural gradient descent in affine image registration

Accurate spatial alignment is essential for any population neuroimaging study, and affine (12 parameter linear/translation) or rigid (6 parameter rotation/translation) alignments play a major role. Here we consider intensity based alignment of neuroimages using gradient based optimization, which is a problem that continues to be important in many other areas of medical imaging and computer vision in general. A key challenge is robustness. Optimization often fails when transformations have components with different characteristic scales, such as linear versus translation parameters. Hand tuning or other scaling approaches have been used, but efficient automatic methods are essential for generalizing to new imaging modalities, to specimens of different sizes, and to big datasets where manual approaches are not feasible. To address this we develop a left invariant metric on these two matrix groups, based on the norm squared of optical flow induced on a template image. This metric is used in a natural gradient descent algorithm, where gradients (covectors) are converted to perturbations (vectors) by applying the inverse of the metric to define a search direction in which to update parameters. Using a publicly available magnetic resonance neuroimage database, we show that this approach outperforms several other gradient descent optimization strategies. Due to left invariance, our metric needs to only be computed once during optimization, and can therefore be implemented with negligible computation time.

An Optimized Mouse Brain Atlas for Automated Mapping and Quantification of Neuronal Activity Using iDISCO+ and Light Sheet Fluorescence Microscopy

In recent years, the combination of whole-brain immunolabelling, light sheet fluorescence microscopy (LSFM) and subsequent registration of data with a common reference atlas, has enabled 3D visualization and quantification of fluorescent markers or tracers in the adult mouse brain. Today, the common coordinate framework version 3 developed by the Allen’s Institute of Brain Science (AIBS CCFv3), is widely used as the standard brain atlas for registration of LSFM data. However, the AIBS CCFv3 is based on histological processing and imaging modalities different from those used for LSFM imaging and consequently, the data differ in both tissue contrast and morphology. To improve the accuracy and speed by which LSFM-imaged whole-brain data can be registered and quantified, we have created an optimized digital mouse brain atlas based on immunolabelled and solvent-cleared brains. Compared to the AIBS CCFv3 atlas, our atlas resulted in faster and more accurate mapping of neuronal activity as measured by c-Fos expression, especially in the hindbrain. We further demonstrated utility of the LSFM atlas by comparing whole-brain quantitative changes in c-Fos expression following acute administration of semaglutide in lean and diet-induced obese mice. In combination with an improved algorithm for c-Fos detection, the LSFM atlas enables unbiased and computationally efficient characterization of drug effects on whole-brain neuronal activity patterns. In conclusion, we established an optimized reference atlas for more precise mapping of fluorescent markers, including c-Fos, in mouse brains processed for LSFM.

Localizing Microemboli within the Rodent Brain through Block-Face Imaging and Atlas Registration

Brain microinfarcts are prevalent in humans, however because of the inherent difficulty of identifying and localizing individual microinfarcts, brain-wide quantification is impractical. In mice, microinfarcts have been created by surgically introducing microemboli into the brain, but a major limitation of this model is the absence of automated methods to identify and localize individual occlusions. We present a novel and semi-automated workflow to identify the anatomic location of fluorescent emboli (microspheres) within the mouse brain through histologic processing and atlas registration. By incorporating vibratome block-face imaging with the QuickNII brain registration tool, we show that the anatomic location of microspheres can be accurately registered to brain structures within the Allen mouse brain (AMB) atlas (e.g., somatomotor areas, hippocampal region, visual areas, etc.). Compared with registering images of slide mounted sections to the AMB atlas, microsphere location was more accurately determined when block-face images were used. As a proof of principle, using this workflow we compared the distribution of microspheres within the brains of mice that were either perfused or immersion fixed. No significant effect of perfusion on total microsphere number or location was detected. In general, microspheres were distributed brain-wide, with the largest density found in the thalamus. In sum, our block-face imaging workflow enables efficient characterization of the widespread distribution of fluorescent microemboli, facilitating future investigation into the impact of microinfarct load and location on brain health.

A distributed circuit for associating environmental context with motor choice in retrosplenial cortex

During navigation, animals often use recognition of familiar environmental contexts to guide motor action selection. The retrosplenial cortex (RSC) receives inputs from both visual cortex and subcortical regions required for spatial memory and projects to motor planning regions. However, it is not known whether RSC is important for associating familiar environmental contexts with specific motor actions. We test this possibility by developing a task in which motor trajectories are chosen based on the context. We find that mice exhibit differential predecision activity in RSC and that optogenetic suppression of RSC activity impairs task performance. Individual RSC neurons encode a range of task variables, often multiplexed with distinct temporal profiles. However, the responses are spatiotemporally organized, with task variables represented along a posterior-to-anterior gradient along RSC during the behavioral performance, consistent with histological characterization. These results reveal an anatomically organized retrosplenial cortical circuit for associating environmental contexts with appropriate motor outputs.

Go with the FLOW: visualizing spatiotemporal dynamics in optical widefield calcium imaging

Widefield calcium imaging has recently emerged as a powerful experimental technique to record coordinated large-scale brain activity. These measurements present a unique opportunity to characterize spatiotemporally coherent structures that underlie neural activity across many regions of the brain. In this work, we leverage analytic techniques from fluid dynamics to develop a visualization framework that highlights features of flow across the cortex, mapping wavefronts that may be correlated with behavioural events. First, we transform the time series of widefield calcium images into time-varying vector fields using optic flow. Next, we extract concise diagrams summarizing the dynamics, which we refer to as FLOW (flow lines in optical widefield imaging) portraits. These FLOW portraits provide an intuitive map of dynamic calcium activity, including regions of initiation and termination, as well as the direction and extent of activity spread. To extract these structures, we use the finite-time Lyapunov exponent technique developed to analyse time-varying manifolds in unsteady fluids. Importantly, our approach captures coherent structures that are poorly represented by traditional modal decomposition techniques. We demonstrate the application of FLOW portraits on three simple synthetic datasets and two widefield calcium imaging datasets, including cortical waves in the developing mouse and spontaneous cortical activity in an adult mouse.

Sensory coding and the causal impact of mouse cortex in a visual decision

Correlates of sensory stimuli and motor actions are found in multiple cortical areas, but such correlates do not indicate whether these areas are causally relevant to task performance. We trained mice to discriminate visual contrast and report their decision by steering a wheel. Widefield calcium imaging and Neuropixels recordings in cortex revealed stimulus-related activity in visual (VIS) and frontal (MOs) areas, and widespread movement-related activity across the whole dorsal cortex. Optogenetic inactivation biased choices only when targeted at VIS and MOs,proportionally to each site's encoding of the visual stimulus, and at times corresponding to peak stimulus decoding. A neurometric model based on summing and subtracting activity in VIS and MOs successfully described behavioral performance and predicted the effect of optogenetic inactivation. Thus, sensory signals localized in visual and frontal cortex play a causal role in task performance, while widespread dorsal cortical signals correlating with movement reflect processes that do not play a causal role.

Transcriptomic encoding of sensorimotor transformation in the midbrain

Sensorimotor transformation, a process that converts sensory stimuli into motor actions, is critical for the brain to initiate behaviors. Although the circuitry involved in sensorimotor transformation has been well delineated, the molecular logic behind this process remains poorly understood. Here, we performed high-throughput and circuit-specific single-cell transcriptomic analyses of neurons in the superior colliculus (SC), a midbrain structure implicated in early sensorimotor transformation. We found that SC neurons in distinct laminae expressed discrete marker genes. Of particular interest, Cbln2 and Pitx2 were key markers that define glutamatergic projection neurons in the optic nerve (Op) and intermediate gray (InG) layers, respectively. The Cbln2+ neurons responded to visual stimuli mimicking cruising predators, while the Pitx2+ neurons encoded prey-derived vibrissal tactile cues. By forming distinct input and output connections with other brain areas, these neuronal subtypes independently mediated behaviors of predator avoidance and prey capture. Our results reveal that, in the midbrain, sensorimotor transformation for different behaviors may be performed by separate circuit modules that are molecularly defined by distinct transcriptomic codes.

A functional ultrasound brain GPS for automatic vascular-based neuronavigation

Recent advances in ultrasound imaging triggered by transmission of ultrafast plane waves have rendered functional ultrasound (fUS) imaging a valuable neuroimaging modality capable of mapping cerebral vascular networks, but also for the indirect capture of neuronal activity with high sensitivity thanks to the neurovascular coupling. However, the expansion of fUS imaging is still limited by the difficulty to identify cerebral structures during experiments based solely on the Doppler images and the shape of the vessels. In order to tackle this challenge, this study introduces the vascular brain positioning system (BPS), a GPS of the brain. The BPS is a whole-brain neuronavigation system based on the on-the-fly automatic alignment of ultrafast ultrasensitive transcranial Power Doppler volumic images to common templates such as the Allen Mouse Brain Common Coordinates Framework. This method relies on the online registration of the complex cerebral vascular fingerprint of the studied animal to a pre-aligned reference vascular atlas, thus allowing rapid matching and identification of brain structures. We quantified the accuracy of the automatic registration using super-resolution vascular images obtained at the microscopic scale using Ultrasound Localization Microscopy and found a positioning error of 44 µm and 96 µm for intra-animal and inter-animal vascular registration, respectively. The proposed BPS approach outperforms the manual vascular landmark recognition performed by expert neuroscientists (inter-annotator errors of 215 µm and 259 µm). Using the online BPS approach coupled with the Allen Atlas, we demonstrated the capability of the system to position itself automatically over chosen anatomical structures and to obtain corresponding functional activation maps even in complex oblique planes. Finally, we show that the system can be used to acquire and estimate functional connectivity matrices automatically. The proposed functional ultrasound on-the-fly neuronavigation approach allows automatic brain navigation and could become a key asset to ensure standardized experiments and protocols for non-expert and expert researchers.

Comprehensive Evaluation of the 5XFAD Mouse Model for Preclinical Testing Applications: A MODEL-AD Study

The ability to investigate therapeutic interventions in animal models of neurodegenerative diseases depends on extensive characterization of the model(s) being used. There are numerous models that have been generated to study Alzheimer's disease (AD) and the underlying pathogenesis of the disease. While transgenic models have been instrumental in understanding AD mechanisms and risk factors, they are limited in the degree of characteristics displayed in comparison with AD in humans, and the full spectrum of AD effects has yet to be recapitulated in a single mouse model. The Model Organism Development and Evaluation for Late-Onset Alzheimer's Disease (MODEL-AD) consortium was assembled by the National Institute on Aging (NIA) to develop more robust animal models of AD with increased relevance to human disease, standardize the characterization of AD mouse models, improve preclinical testing in animals, and establish clinically relevant AD biomarkers, among other aims toward enhancing the translational value of AD models in clinical drug design and treatment development. Here we have conducted a detailed characterization of the 5XFAD mouse, including transcriptomics, electroencephalogram, in vivo imaging, biochemical characterization, and behavioral assessments. The data from this study is publicly available through the AD Knowledge Portal.

Comprehensive Evaluation of the 5XFAD Mouse Model for Preclinical Testing Applications: A MODEL-AD Study

The ability to investigate therapeutic interventions in animal models of neurodegenerative diseases depends on extensive characterization of the model(s) being used. There are numerous models that have been generated to study Alzheimer's disease (AD) and the underlying pathogenesis of the disease. While transgenic models have been instrumental in understanding AD mechanisms and risk factors, they are limited in the degree of characteristics displayed in comparison with AD in humans, and the full spectrum of AD effects has yet to be recapitulated in a single mouse model. The Model Organism Development and Evaluation for Late-Onset Alzheimer's Disease (MODEL-AD) consortium was assembled by the National Institute on Aging (NIA) to develop more robust animal models of AD with increased relevance to human disease, standardize the characterization of AD mouse models, improve preclinical testing in animals, and establish clinically relevant AD biomarkers, among other aims toward enhancing the translational value of AD models in clinical drug design and treatment development. Here we have conducted a detailed characterization of the 5XFAD mouse, including transcriptomics, electroencephalogram, in vivo imaging, biochemical characterization, and behavioral assessments. The data from this study is publicly available through the AD Knowledge Portal.

Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of cortical neurons. While each of these two modalities has distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging of genetically expressed GCaMP6f or electrophysiology with silicon probes. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging, which was partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could only reconcile differences in responsiveness when restricted to neurons with low contamination and an event rate above a minimum threshold. This work established how the biases of these two modalities impact functional metrics that are fundamental for characterizing sensory-evoked responses.

Rapid suppression and sustained activation of distinct cortical regions for a delayed sensory-triggered motor response

The neuronal mechanisms generating a delayed motor response initiated by a sensory cue remain elusive. Here, we tracked the precise sequence of cortical activity in mice transforming a brief whisker stimulus into delayed licking using wide-field calcium imaging, multiregion high-density electrophysiology, and time-resolved optogenetic manipulation. Rapid activity evoked by whisker deflection acquired two prominent features for task performance: (1) an enhanced excitation of secondary whisker motor cortex, suggesting its important role connecting whisker sensory processing to lick motor planning; and (2) a transient reduction of activity in orofacial sensorimotor cortex, which contributed to suppressing premature licking. Subsequent widespread cortical activity during the delay period largely correlated with anticipatory movements, but when these were accounted for, a focal sustained activity remained in frontal cortex, which was causally essential for licking in the response period. Our results demonstrate key cortical nodes for motor plan generation and timely execution in delayed goal-directed licking.

Recent Trends and Perspectives in Cerebral Organoids Imaging and Analysis

Purpose: Since their first generation in 2013, the use of cerebral organoids has spread exponentially. Today, the amount of generated data is becoming challenging to analyze manually. This review aims to overview the current image acquisition methods and to subsequently identify the needs in image analysis tools for cerebral organoids. Methods: To address this question, we went through all recent articles published on the subject and annotated the protocols, acquisition methods, and algorithms used. Results: Over the investigated period of time, confocal microscopy and bright-field microscopy were the most used acquisition techniques. Cell counting, the most common task, is performed in 20% of the articles and area; around 12% of articles calculate morphological parameters. Image analysis on cerebral organoids is performed in majority using ImageJ software (around 52%) and Matlab language (4%). Treatments remain mostly semi-automatic. We highlight the limitations encountered in image analysis in the cerebral organoid field and suggest possible solutions and implementations to develop. Conclusions: In addition to providing an overview of cerebral organoids cultures and imaging, this work highlights the need to improve the existing image analysis methods for such images and the need for specific analysis tools. These solutions could specifically help to monitor the growth of future standardized cerebral organoids.

An Optimized Mouse Brain Atlas for Automated Mapping and Quantification of Neuronal Activity Using iDISCO+ and Light Sheet Fluorescence Microscopy

In recent years, the combination of whole-brain immunolabelling, light sheet fluorescence microscopy (LSFM) and subsequent registration of data with a common reference atlas, has enabled 3D visualization and quantification of fluorescent markers or tracers in the adult mouse brain. Today, the common coordinate framework version 3 developed by the Allen's Institute of Brain Science (AIBS CCFv3), is widely used as the standard brain atlas for registration of LSFM data. However, the AIBS CCFv3 is based on histological processing and imaging modalities different from those used for LSFM imaging and consequently, the data differ in both tissue contrast and morphology. To improve the accuracy and speed by which LSFM-imaged whole-brain data can be registered and quantified, we have created an optimized digital mouse brain atlas based on immunolabelled and solvent-cleared brains. Compared to the AIBS CCFv3 atlas, our atlas resulted in faster and more accurate mapping of neuronal activity as measured by c-Fos expression, especially in the hindbrain. We further demonstrated utility of the LSFM atlas by comparing whole-brain quantitative changes in c-Fos expression following acute administration of semaglutide in lean and diet-induced obese mice. In combination with an improved algorithm for c-Fos detection, the LSFM atlas enables unbiased and computationally efficient characterization of drug effects on whole-brain neuronal activity patterns. In conclusion, we established an optimized reference atlas for more precise mapping of fluorescent markers, including c-Fos, in mouse brains processed for LSFM.

Assessing the replicability of spatial gene expression using atlas data from the adult mouse brain

High-throughput, spatially resolved gene expression techniques are poised to be transformative across biology by overcoming a central limitation in single-cell biology: the lack of information on relationships that organize the cells into the functional groupings characteristic of tissues in complex multicellular organisms. Spatial expression is particularly interesting in the mammalian brain, which has a highly defined structure, strong spatial constraint in its organization, and detailed multimodal phenotypes for cells and ensembles of cells that can be linked to mesoscale properties such as projection patterns, and from there, to circuits generating behavior. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain subdivisions, between the Allen Institute's in situ hybridization data from the adult mouse brain (Allen Brain Atlas (ABA)) and a similar dataset collected using spatial transcriptomics (ST). With the advent of tractable spatial techniques, for the first time, we are able to benchmark the Allen Institute's whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. We use regularized linear regression (LASSO), linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen Reference Atlas labels are classifiable using transcription in both data sets, but that performance is higher in the ABA than in ST. Furthermore, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bidirectionally. While an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. In general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability ultimately providing a valuable reference set for understanding the cell biology of the brain.

Whole-brain functional ultrasound imaging in awake head-fixed mice

Most brain functions engage a network of distributed regions. Full investigation of these functions thus requires assessment of whole brains; however, whole-brain functional imaging of behaving animals remains challenging. This protocol describes how to follow brain-wide activity in awake head-fixed mice using functional ultrasound imaging, a method that tracks cerebral blood volume dynamics. We describe how to set up a functional ultrasound imaging system with a provided acquisition software (miniScan), establish a chronic cranial window (timing surgery: ~3-4 h) and image brain-wide activity associated with a stimulus at high resolution (100 × 110 × 300 µm and 10 Hz per brain slice, which takes ~45 min per imaging session). We include codes that enable data to be registered to a reference atlas, production of 3D activity maps, extraction of the activity traces of ~250 brain regions and, finally, combination of data from multiple sessions (timing analysis averages ~2 h). This protocol enables neuroscientists to observe global brain processes in mice.

Multiscale Computational Model Reveals Nerve Response in a Mouse Model for Temporal Interference Brain Stimulation

There has been a growing interest in the non-invasive stimulation of specific brain tissues, while reducing unintended stimulation in surrounding regions, for the medical treatment of brain disorders. Traditional methods for non-invasive brain stimulation, such as transcranial direct current stimulation (tDCS) or transcranial magnetic stimulation (TMS), can stimulate brain regions, but they also simultaneously stimulate the brain and non-brain regions that lie between the target and the stimulation site of the source. Temporal interference (TI) stimulation has been suggested to selectively stimulate brain regions by superposing two alternating currents with slightly different frequencies injected through electrodes attached to the scalp. Previous studies have reported promising results for TI applied to the motor area in mice, but the mechanisms are yet to be clarified. As computational techniques can help reveal different aspects of TI, in this study, we computationally investigated TI stimulation using a multiscale model that computes the generated interference current pattern effects in a neural cortical model of a mouse head. The results indicated that the threshold increased with the carrier frequency and that the beat frequency did not influence the threshold. It was also found that the intensity ratio between the alternating currents changed the location of the responding nerve, which is in agreement with previous experiments. Moreover, particular characteristics of the envelope were investigated to predict the stimulation region intuitively. It was found that regions with high modulation depth (| maximum| − | minimum| values of the envelope) and low minimum envelope (near zero) corresponded with the activation region obtained via neural computation.

Convergence Circuit Mapping: Genetic Approaches From Structure to Function

Understanding the complex neural circuits that underpin brain function and behavior has been a long-standing goal of neuroscience. Yet this is no small feat considering the interconnectedness of neurons and other cell types, both within and across brain regions. In this review, we describe recent advances in mouse molecular genetic engineering that can be used to integrate information on brain activity and structure at regional, cellular, and subcellular levels. The convergence of structural inputs can be mapped throughout the brain in a cell type-specific manner by antero- and retrograde viral systems expressing various fluorescent proteins and genetic switches. Furthermore, neural activity can be manipulated using opto- and chemo-genetic tools to interrogate the functional significance of this input convergence. Monitoring neuronal activity is obtained with precise spatiotemporal resolution using genetically encoded sensors for calcium changes and specific neurotransmitters. Combining these genetically engineered mapping tools is a compelling approach for unraveling the structural and functional brain architecture of complex behaviors and malfunctioned states of neurological disorders.

CUBIC-Cloud provides an integrative computational framework toward community-driven whole-mouse-brain mapping

Recent advancements in tissue clearing technologies have offered unparalleled opportunities for researchers to explore the whole mouse brain at cellular resolution. With the expansion of this experimental technique, however, a scalable and easy-to-use computational tool is in demand to effectively analyze and integrate whole-brain mapping datasets. To that end, here we present CUBIC-Cloud, a cloud-based framework to quantify, visualize, and integrate mouse brain data. CUBIC-Cloud is a fully automated system where users can upload their whole-brain data, run analyses, and publish the results. We demonstrate the generality of CUBIC-Cloud by a variety of applications. First, we investigated the brain-wide distribution of five cell types. Second, we quantified Aβ plaque deposition in Alzheimer's disease model mouse brains. Third, we reconstructed a neuronal activity profile under LPS-induced inflammation by c-Fos immunostaining. Last, we show brain-wide connectivity mapping by pseudotyped rabies virus. Together, CUBIC-Cloud provides an integrative platform to advance scalable and collaborative whole-brain mapping.

Progress towards a cellularly resolved mouse mesoconnectome is empowered by data fusion and new neuroanatomy techniques

Over the past decade there has been a rapid improvement in techniques for obtaining large-scale cellular level data related to the mouse brain connectome. However, a detailed mapping of cell-type-specific projection patterns is lacking, which would, for instance, allow us to study the role of circuit motifs in cognitive processes. In this work, we review advanced neuroanatomical and data fusion techniques within the context of a proposed Multimodal Connectomic Integration Framework for augmenting the cellularly resolved mouse mesoconnectome. First, we emphasize the importance of registering data modalities to a common reference atlas. We then review a number of novel experimental techniques that can provide data for characterizing cell-types in the mouse brain. Furthermore, we examine a number of data integration strategies, which involve fine-grained cell-type classification, spatial inference of cell densities, latent variable models for the mesoconnectome and multi-modal factorisation. Finally, we discuss a number of use cases which depend on connectome augmentation techniques, such as model simulations of functional connectivity and generating mechanistic hypotheses for animal disease models.

A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation

The isocortex and hippocampal formation (HPF) in the mammalian brain play critical roles in perception, cognition, emotion, and learning. We profiled ∼1.3 million cells covering the entire adult mouse isocortex and HPF and derived a transcriptomic cell-type taxonomy revealing a comprehensive repertoire of glutamatergic and GABAergic neuron types. Contrary to the traditional view of HPF as having a simpler cellular organization, we discover a complete set of glutamatergic types in HPF homologous to all major subclasses found in the six-layered isocortex, suggesting that HPF and the isocortex share a common circuit organization. We also identify large-scale continuous and graded variations of cell types along isocortical depth, across the isocortical sheet, and in multiple dimensions in hippocampus and subiculum. Overall, our study establishes a molecular architecture of the mammalian isocortex and hippocampal formation and begins to shed light on its underlying relationship with the development, evolution, connectivity, and function of these two brain structures.

Embedding optimization reveals long-lasting history dependence in neural spiking activity

Information processing can leave distinct footprints on the statistics of neural spiking. For example, efficient coding minimizes the statistical dependencies on the spiking history, while temporal integration of information may require the maintenance of information over different timescales. To investigate these footprints, we developed a novel approach to quantify history dependence within the spiking of a single neuron, using the mutual information between the entire past and current spiking. This measure captures how much past information is necessary to predict current spiking. In contrast, classical time-lagged measures of temporal dependence like the autocorrelation capture how long-potentially redundant-past information can still be read out. Strikingly, we find for model neurons that our method disentangles the strength and timescale of history dependence, whereas the two are mixed in classical approaches. When applying the method to experimental data, which are necessarily of limited size, a reliable estimation of mutual information is only possible for a coarse temporal binning of past spiking, a so-called past embedding. To still account for the vastly different spiking statistics and potentially long history dependence of living neurons, we developed an embedding-optimization approach that does not only vary the number and size, but also an exponential stretching of past bins. For extra-cellular spike recordings, we found that the strength and timescale of history dependence indeed can vary independently across experimental preparations. While hippocampus indicated strong and long history dependence, in visual cortex it was weak and short, while in vitro the history dependence was strong but short. This work enables an information-theoretic characterization of history dependence in recorded spike trains, which captures a footprint of information processing that is beyond time-lagged measures of temporal dependence. To facilitate the application of the method, we provide practical guidelines and a toolbox.

A Skull-Removed Chronic Cranial Window for Ultrasound and Photoacoustic Imaging of the Rodent Brain

Ultrasound and photoacoustic imaging are emerging as powerful tools to study brain structures and functions. The skull introduces significant distortion and attenuation of the ultrasound signals deteriorating image quality. For biological studies employing rodents, craniotomy is often times performed to enhance image qualities. However, craniotomy is unsuitable for longitudinal studies, where a long-term cranial window is needed to prevent repeated surgeries. Here, we propose a mouse model to eliminate sound blockage by the top portion of the skull, while minimum physiological perturbation to the imaged object is incurred. With the new mouse model, no craniotomy is needed before each imaging experiment. The effectiveness of our method was confirmed by three imaging systems: photoacoustic computed tomography, ultrasound imaging, and photoacoustic mesoscopy. Functional photoacoustic imaging of the mouse brain hemodynamics was also conducted. We expect new applications to be enabled by the new mouse model for photoacoustic and ultrasound imaging.

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets

Understanding the function of the nervous system necessitates mapping the spatial distributions of its constituent cells defined by function, anatomy or gene expression. Recently, developments in tissue preparation and microscopy allow cellular populations to be imaged throughout the entire rodent brain. However, mapping these neurons manually is prone to bias and is often impractically time consuming. Here we present an open-source algorithm for fully automated 3D detection of neuronal somata in mouse whole-brain microscopy images using standard desktop computer hardware. We demonstrate the applicability and power of our approach by mapping the brain-wide locations of large populations of cells labeled with cytoplasmic fluorescent proteins expressed via retrograde trans-synaptic viral infection.

Organization of feedback projections to mouse primary visual cortex

Top-down, context-dependent modulation of visual processing has been a topic of wide interest, including in mouse primary visual cortex (V1). However, the organization of feedback projections to V1 is relatively unknown. Here, we investigated inputs to mouse V1 by injecting retrograde tracers. We developed a software pipeline that maps labeled cell bodies to corresponding brain areas in the Allen Reference Atlas. We identified more than 24 brain areas that provide inputs to V1 and quantified the relative strength of their projections. We also assessed the organization of the projections, based on either the organization of cell bodies in the source area (topography) or the distribution of projections across V1 (bias). Projections from most higher visual and some nonvisual areas to V1 showed both topography and bias. Such organization of feedback projections to V1 suggests that parts of the visual field are differentially modulated by context, which can be ethologically relevant for a navigating animal.

Distinct Transcriptomic Cell Types and Neural Circuits of the Subiculum and Prosubiculum along the Dorsal-Ventral Axis

Subicular regions play important roles in spatial processing and many cognitive functions, and these are mainly attributed to the subiculum (Sub) rather than the prosubiculum (PS). Using single-cell RNA sequencing, we identify 27 transcriptomic cell types residing in sub-domains of the Sub and PS. Based on in situ expression of reliable transcriptomic markers, the precise boundaries of the Sub and PS are consistently defined along the dorsoventral axis. Using these borders to evaluate Cre-line specificity and tracer injections, we find bona fide Sub projections topographically to structures important for spatial processing and navigation. In contrast, the PS sends its outputs to widespread brain regions crucial for motivation, emotion, reward, stress, anxiety, and fear. The Sub and PS, respectively, dominate dorsal and ventral subicular regions and receive different afferents. These results reveal two molecularly and anatomically distinct circuits centered in the Sub and PS, respectively, providing a consistent explanation for historical data and a clearer foundation for future studies.

Incentive motivation: 'wanting' roles of central amygdala circuitry

The central nucleus of amygdala (CeA) mediates positively-valenced reward motivation as well as negatively-valenced fear. Optogenetic or neurochemical stimulation of CeA circuitry can generate intense incentive motivation to pursue and consume a paired natural food, sex, or addictive drug reward, and even create maladaptive 'wanting what hurts' such as attraction to a shock rod. Evidence indicates CeA stimulations selectively amplify incentive motivation ('wanting') but not hedonic impact ('liking') of the same reward. Further, valence flips can occur for CeA contributions to motivational salience. That is, CeA stimulation can promote either incentive motivation or fearful motivation, even in the same individual, depending on situation. These findings may carry implications for understanding CeA roles in neuropsychiatric disorders involving aberrant motivational salience, ranging from addiction to paranoia and anxiety disorders.

Characterizing Cortex-Wide Dynamics with Wide-Field Calcium Imaging

The brain functions through coordinated activity among distributed regions. Wide-field calcium imaging, combined with improved genetically encoded calcium indicators, allows sufficient signal-to-noise ratio and spatiotemporal resolution to afford a unique opportunity to capture cortex-wide dynamics on a moment-by-moment basis in behaving animals. Recent applications of this approach have been uncovering cortical dynamics at unprecedented scales during various cognitive processes, ranging from relatively simple sensorimotor integration to more complex decision-making tasks. In this review, we will highlight recent scientific advances enabled by wide-field calcium imaging in behaving mice. We then summarize several technical considerations and future opportunities for wide-field imaging to uncover large-scale circuit dynamics.

Visual intracortical and transthalamic pathways carry distinct information to cortical areas

Sensory processing involves information flow between neocortical areas, assumed to rely on direct intracortical projections. However, cortical areas may also communicate indirectly via higher-order nuclei in the thalamus, such as the pulvinar or lateral posterior nucleus (LP) in the visual system of rodents. The fine-scale organization and function of these cortico-thalamo-cortical pathways remains unclear. We find that responses of mouse LP neurons projecting to higher visual areas likely derive from feedforward input from primary visual cortex (V1) combined with information from many cortical and subcortical areas, including superior colliculus. Signals from LP projections to different higher visual areas are tuned to specific features of visual stimuli and their locomotor context, distinct from the signals carried by direct intracortical projections from V1. Thus, visual transthalamic pathways are functionally specific to their cortical target, different from feedforward cortical pathways, and combine information from multiple brain regions, linking sensory signals with behavioral context.

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Transthalamic pathway through pulvinar indirectly connects lower to higher cortical areas

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This pathway combines input from V1 with that of many cortical and subcortical areas

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Pulvinar conveys distinct visual and motor information to different higher visual areas

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Direct intracortical and transthalamic pathways convey different information

A Versatile Tiling Light Sheet Microscope for Imaging of Cleared Tissues

We present a tiling light sheet microscope compatible with all tissue clearing methods for rapid multicolor 3D imaging of cleared tissues with micron-scale (4 × 4 × 10 μm³) to submicron-scale (0.3 × 0.3 × 1 μm³) spatial resolution. The resolving ability is improved to sub-100 nm (70 × 70 × 200 nm³) via tissue expansion. The microscope uses tiling light sheets to achieve higher spatial resolution and better optical sectioning ability than conventional light sheet microscopes. The illumination light is phase modulated to adjust the position and intensity profile of the light sheet based on the desired spatial resolution and imaging speed and to keep the microscope aligned. The ability of the microscope to align via phase modulation alone also ensures its accuracy for multicolor 3D imaging and makes the microscope reliable and easy to operate. Here we describe the working principle and design of the microscope. We demonstrate its utility by imaging various cleared tissues.

Fully autonomous mouse behavioral and optogenetic experiments in home-cage

Goal-directed behaviors involve distributed brain networks. The small size of the mouse brain makes it amenable to manipulations of neural activity dispersed across brain areas, but existing optogenetic methods serially test a few brain regions at a time, which slows comprehensive mapping of distributed networks. Laborious operant conditioning training required for most experimental paradigms exacerbates this bottleneck. We present an autonomous workflow to survey the involvement of brain regions at scale during operant behaviors in mice. Naive mice living in a home-cage system learned voluntary head-fixation (>1 hr/day) and performed difficult decision-making tasks, including contingency reversals, for 2 months without human supervision. We incorporated an optogenetic approach to manipulate activity in deep brain regions through intact skull during home-cage behavior. To demonstrate the utility of this approach, we tested dozens of mice in parallel unsupervised optogenetic experiments, revealing multiple regions in cortex, striatum, and superior colliculus involved in tactile decision-making.

Spatial Transcriptomics: Molecular Maps of the Mammalian Brain

Maps of the nervous system inspire experiments and theories in neuroscience. Advances in molecular biology over the past decades have revolutionized the definition of cell and tissue identity. Spatial transcriptomics has opened up a new era in neuroanatomy, where the unsupervised and unbiased exploration of the molecular signatures of tissue organization will give rise to a new generation of brain maps. We propose that the molecular classification of brain regions on the basis of their gene expression profile can circumvent subjective neuroanatomical definitions and produce common reference frameworks that can incorporate cell types, connectivity, activity, and other modalities. Here we review the technological and conceptual advances made possible by spatial transcriptomics in the context of advancing neuroanatomy and discuss how molecular neuroanatomy can redefine mapping of the nervous system.

Novel manifestations of Warburg micro syndrome type 1 caused by a new splicing variant of RAB3GAP1: a case report

BACKGROUND

The present study aimed to determine the underlying genetic factors causing the possible Warburg micro syndrome (WARBM) phenotype in two Iranian patients.

CASE PRESENTATION

A 5-year-old female and a 4.5-year-old male were referred due to microcephaly, global developmental delay, and dysmorphic features. After doing neuroimaging and clinical examinations, due to the heterogeneity of neurodevelopmental disorders, we subjected 7 family members to whole-exome sequencing. Three candidate variants were confirmed by Sanger sequencing and allele frequency of each variant was also determined in 300 healthy ethnically matched people using the tetra-primer amplification refractory mutation system-PCR and PCR-restriction fragment length polymorphism. To show the splicing effects, reverse transcription-PCR (RT-PCR) and RT-qPCR were performed, followed by Sanger sequencing. A novel homozygous variant-NM_012233.2: c.151-5 T > G; p.(Gly51IlefsTer15)-in the RAB3GAP1 gene was identified as the most likely disease-causing variant. RT-PCR/RT-qPCR showed that this variant can activate a cryptic site of splicing in intron 3, changing the splicing and gene expression processes. We also identified some novel manifestations in association with WARBM type 1 to touch upon abnormal philtrum, prominent antitragus, downturned corners of the mouth, malaligned teeth, scrotal hypoplasia, low anterior hairline, hypertrichosis of upper back, spastic diplegia to quadriplegia, and cerebral white matter signal changes.

CONCLUSIONS

Due to the common phenotypes between WARBMs and Martsolf syndrome (MIM: 212720), we suggest using the "RABopathies" term that can in turn cover a broad range of manifestations. This study can per se increase the genotype-phenotype spectrum of WARBM type 1.

Constructing an adult orofacial premotor atlas in Allen mouse CCF

Premotor circuits in the brainstem project to pools of orofacial motoneurons to execute essential motor action such as licking, chewing, breathing, and in rodent, whisking. Previous transsynaptic tracing studies only mapped orofacial premotor circuits in neonatal mice, but the adult circuits remain unknown as a consequence of technical difficulties. Here, we developed a three-step monosynaptic transsynaptic tracing strategy to identify premotor neurons controlling vibrissa, tongue protrusion, and jaw-closing muscles in the adult mouse. We registered these different groups of premotor neurons onto the Allen mouse brain common coordinate framework (CCF) and consequently generated a combined 3D orofacial premotor atlas, revealing unique spatial organizations of distinct premotor circuits. We further uncovered premotor neurons that simultaneously innervate multiple motor nuclei and, consequently, are likely to coordinate different muscles involved in the same orofacial motor actions. Our method for tracing adult premotor circuits and registering to Allen CCF is generally applicable and should facilitate the investigations of motor controls of diverse behaviors.

The mouse prefrontal cortex: Unity in diversity

The prefrontal cortex (PFC) is considered to constitute the highest stage of neural integration and to be devoted to representation and production of actions. Studies in primates have laid the foundation for theories regarding the principles of prefrontal function and provided mechanistic insights. The recent surge of studies of the PFC in mice holds promise for evolvement of present theories and development of novel concepts, particularly regarding principles shared across mammals. Here we review recent empirical work on the mouse PFC capitalizing on the experimental toolbox currently privileged to studies in this species. We conclude that this line of research has revealed cellular and structural distinctions of the PFC and neuronal activity with direct relevance to theories regarding the functions of the PFC. We foresee that data-rich mouse studies will be key to shed light on the general prefrontal architecture and mechanisms underlying cognitive aspects of organized actions.

Prefrontal deep projection neurons enable cognitive flexibility via persistent feedback monitoring

Cognitive flexibility, the ability to alter strategy according to changing stimulus-response-reward relationships, is critical for updating learned behavior. Attentional set-shifting, a test of cognitive flexibility, depends on the activity of prefrontal cortex (PFC). It remains unclear, however, what role PFC neurons play to support set-shifting. Using optogenetics and two-photon calcium imaging, we demonstrate that medial PFC activity does not bias sensorimotor responses during set-shifting, but rather enables set-shifting by encoding trial feedback information, a role it has been known to play in other contexts. Unexpectedly, the functional properties of PFC cells did not vary with their efferent projection targets. Instead, representations of trial feedback formed a topological gradient, with cells more strongly selective for feedback information located further from the pial surface, where afferent input from the anterior cingulate cortex was denser. These findings identify a critical role for deep PFC projection neurons in enabling set-shifting through behavioral feedback monitoring.

3D Whole-Brain Imaging Approaches to Study Brain Tumors

Simple Summary

Brain tumors integrate into the brain and consist of tumor cells with different molecular alterations. During brain tumor pathogenesis, a variety of cell types surround the tumors to either inhibit or promote tumor growth. These cells are collectively referred to as the tumor microenvironment. Three-dimensional and/or longitudinal visualization approaches are needed to understand the growth of these tumors in time and space. In this review, we present three imaging modalities that are suitable or that can be adapted to study the volumetric distribution of malignant or tumor-associated cells in the brain. In addition, we highlight the potential clinical utility of some of the microscopy approaches for brain tumors using exemplars from solid tumors.

Abstract

Although our understanding of the two-dimensional state of brain tumors has greatly expanded, relatively little is known about their spatial structures. The interactions between tumor cells and the tumor microenvironment (TME) occur in a three-dimensional (3D) space. This volumetric distribution is important for elucidating tumor biology and predicting and monitoring response to therapy. While static 2D imaging modalities have been critical to our understanding of these tumors, studies using 3D imaging modalities are needed to understand how malignant cells co-opt the host brain. Here we summarize the preclinical utility of in vivo imaging using two-photon microscopy in brain tumors and present ex vivo approaches (light-sheet fluorescence microscopy and serial two-photon tomography) and highlight their current and potential utility in neuro-oncology using data from solid tumors or pathological brain as examples.

Constructing the rodent stereotaxic brain atlas: a survey

The stereotaxic brain atlas is a fundamental reference tool commonly used in the field of neuroscience. Here we provide a brief history of brain atlas development and clarify three key conceptual elements of stereotaxic brain atlasing: brain image, atlas, and stereotaxis. We also refine four technical indices for evaluating the construction of atlases: the quality of staining and labeling, the granularity of delineation, spatial resolution, and the precision of spatial location and orientation. Additionally, we discuss state-of-the-art technologies and their trends in the fields of image acquisition, stereotaxic coordinate construction, image processing, anatomical structure recognition, and publishing: the procedures of brain atlas illustration. We believe that the use of single-cell resolution and micron-level location precision will become a future trend in the study of the stereotaxic brain atlas, which will greatly benefit the development of neuroscience.

Brain microvasculature has a common topology with local differences in geometry that match metabolic load

The microvasculature underlies the supply networks that support neuronal activity within heterogeneous brain regions. What are common versus heterogeneous aspects of the connectivity, density, and orientation of capillary networks? To address this, we imaged, reconstructed, and analyzed the microvasculature connectome in whole adult mice brains with sub-micrometer resolution. Graph analysis revealed common network topology across the brain that leads to a shared structural robustness against the rarefaction of vessels. Geometrical analysis, based on anatomically accurate reconstructions, uncovered a scaling law that links length density, i.e., the length of vessel per volume, with tissue-to-vessel distances. We then derive a formula that connects regional differences in metabolism to differences in length density and, further, predicts a common value of maximum tissue oxygen tension across the brain. Last, the orientation of capillaries is weakly anisotropic with the exception of a few strongly anisotropic regions; this variation can impact the interpretation of fMRI data.

SNT: a unifying toolbox for quantification of neuronal anatomy

SNT is an end-to-end framework for neuronal morphometry and whole-brain connectomics that supports tracing, proof-editing, visualization, quantification and modeling of neuroanatomy. With an open architecture, a large user base, community-based documentation, support for complex imagery and several model organisms, SNT is a flexible resource for the broad neuroscience community. SNT is both a desktop application and multi-language scripting library, and it is available through the Fiji distribution of ImageJ.

The Surviving Sepsis Campaign: Research Priorities for Coronavirus Disease 2019 in Critical Illness

OBJECTIVES

To identify research priorities in the management, pathophysiology, and host response of coronavirus disease 2019 in critically ill patients.

DESIGN

The Surviving Sepsis Research Committee, a multiprofessional group of 17 international experts representing the European Society of Intensive Care Medicine and Society of Critical Care Medicine, was virtually convened during the coronavirus disease 2019 pandemic. The committee iteratively developed the recommendations and subsequent document.

METHODS

Each committee member submitted a list of what they believed were the most important priorities for coronavirus disease 2019 research. The entire committee voted on 58 submitted questions to determine top priorities for coronavirus disease 2019 research.

RESULTS

The Surviving Sepsis Research Committee provides 13 priorities for coronavirus disease 2019. Of these, the top six priorities were identified and include the following questions: 1) Should the approach to ventilator management differ from the standard approach in patients with acute hypoxic respiratory failure?, 2) Can the host response be modulated for therapeutic benefit?, 3) What specific cells are directly targeted by severe acute respiratory syndrome coronavirus 2, and how do these cells respond?, 4) Can early data be used to predict outcomes of coronavirus disease 2019 and, by extension, to guide therapies?, 5) What is the role of prone positioning and noninvasive ventilation in nonventilated patients with coronavirus disease?, and 6) Which interventions are best to use for viral load modulation and when should they be given?

CONCLUSIONS

Although knowledge of both biology and treatment has increased exponentially in the first year of the coronavirus disease 2019 pandemic, significant knowledge gaps remain. The research priorities identified represent a roadmap for investigation in coronavirus disease 2019.

Visualizing anatomically registered data with brainrender

Three-dimensional (3D) digital brain atlases and high-throughput brain-wide imaging techniques generate large multidimensional datasets that can be registered to a common reference frame. Generating insights from such datasets depends critically on visualization and interactive data exploration, but this a challenging task. Currently available software is dedicated to single atlases, model species or data types, and generating 3D renderings that merge anatomically registered data from diverse sources requires extensive development and programming skills. Here, we present brainrender: an open-source Python package for interactive visualization of multidimensional datasets registered to brain atlases. Brainrender facilitates the creation of complex renderings with different data types in the same visualization and enables seamless use of different atlas sources. High-quality visualizations can be used interactively and exported as high-resolution figures and animated videos. By facilitating the visualization of anatomically registered data, brainrender should accelerate the analysis, interpretation, and dissemination of brain-wide multidimensional data.

Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques

In multicellular and even single-celled organisms, individual components are interconnected at multiscale levels to produce enormously complex biological networks that help these systems maintain homeostasis for development and environmental adaptation. Systems biology studies initially adopted network analysis to explore how relationships between individual components give rise to complex biological processes. Network analysis has been applied to dissect the complex connectivity of mammalian brains across different scales in time and space in The Human Brain Project. In plant science, network analysis has similarly been applied to study the connectivity of plant components at the molecular, subcellular, cellular, organic, and organism levels. Analysis of these multiscale networks contributes to our understanding of how genotype determines phenotype. In this review, we summarized the theoretical framework of plant multiscale networks and introduced studies investigating plant networks by various experimental and computational modalities. We next discussed the currently available analytic methodologies and multi-level imaging techniques used to map multiscale networks in plants. Finally, we highlighted some of the technical challenges and key questions remaining to be addressed in this emerging field.

Uncovering Statistical Links Between Gene Expression and Structural Connectivity Patterns in the Mouse Brain

Finding links between genes and structural connectivity is of the utmost importance for unravelling the underlying mechanism of the brain connectome. In this study we identify links between the gene expression and the axonal projection density in the mouse brain, by applying a modified version of the Linked ICA method to volumetric data from the Allen Institute for Brain Science for identifying independent sources of information that link both modalities at the voxel level. We performed separate analyses on sets of projections from the visual cortex, the caudoputamen and the midbrain reticular nucleus, and we determined those brain areas, injections and genes that were most involved in independent components that link both gene expression and projection density data, while we validated their biological context through enrichment analysis. We identified representative and literature-validated cortico-midbrain and cortico-striatal projections, whose gene subsets were enriched with annotations for neuronal and synaptic function and related developmental and metabolic processes. The results were highly reproducible when including all available projections, as well as consistent with factorisations obtained using the Dictionary Learning and Sparse Coding technique. Hence, Linked ICA yielded reproducible independent components that were preserved under increasing data variance. Taken together, we have developed and validated a novel paradigm for linking gene expression and structural projection patterns in the mouse mesoconnectome, which can power future studies aiming to relate genes to brain function.