Mouse Brain Atlas Research Articles

Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices.

Long-range axonal projections of diverse classes of neocortical excitatory neurons likely contribute to brain-wide interactions processing sensory, cognitive and motor signals. Here, we performed light-sheet imaging of fluorescently labeled axons from genetically defined neurons located in posterior primary somatosensory barrel cortex and supplemental somatosensory cortex. We used convolutional networks to segment axon-containing voxels and quantified their distribution within the Allen Mouse Brain Atlas Common Coordinate Framework. Axonal density was analyzed for different classes of glutamatergic neurons using transgenic mouse lines selectively expressing Cre recombinase in layer 2/3 intratelencephalic projection neurons (Rasgrf2-dCre), layer 4 intratelencephalic projection neurons (Scnn1a-Cre), layer 5 intratelencephalic projection neurons (Tlx3-Cre), layer 5 pyramidal tract projection neurons (Sim1-Cre), layer 5 projection neurons (Rbp4-Cre), and layer 6 corticothalamic neurons (Ntsr1-Cre). We found distinct axonal projections from the different neuronal classes to many downstream brain areas, which were largely similar for primary and supplementary somatosensory cortices. Functional connectivity maps obtained from optogenetic activation of sensory cortex and wide-field imaging revealed topographically organized evoked activity in frontal cortex with neurons located more laterally in somatosensory cortex signaling to more anteriorly located regions in motor cortex, consistent with the anatomical projections. The current methodology therefore appears to quantify brain-wide axonal innervation patterns supporting brain-wide signaling.

Cell class-specific long-range axonal projections of neurons in mouse whisker-related somatosensory cortices

Long-range axonal projections of diverse classes of neocortical excitatory neurons likely contribute to brain-wide interactions processing sensory, cognitive and motor signals. Here, we performed light-sheet imaging of fluorescently labeled axons from genetically defined neurons located in posterior primary somatosensory barrel cortex and supplemental somatosensory cortex. We used convolutional networks to segment axon-containing voxels and quantified their distribution within the Allen Mouse Brain Atlas Common Coordinate Framework. Axonal density was analyzed for different classes of glutamatergic neurons using transgenic mouse lines selectively expressing Cre recombinase in layer 2/3 intratelencephalic projection neurons (Rasgrf2-dCre), layer 4 intratelencephalic projection neurons (Scnn1a-Cre), layer 5 intratelencephalic projection neurons (Tlx3-Cre), layer 5 pyramidal tract projection neurons (Sim1-Cre), layer 5 projection neurons (Rbp4-Cre), and layer 6 corticothalamic neurons (Ntsr1-Cre). We found distinct axonal projections from the different neuronal classes to many downstream brain areas, which were largely similar for primary and supplementary somatosensory cortices. Functional connectivity maps obtained from optogenetic activation of sensory cortex and wide-field imaging revealed topographically organized evoked activity in frontal cortex with neurons located more laterally in somatosensory cortex signaling to more anteriorly located regions in motor cortex, consistent with the anatomical projections. The current methodology therefore appears to quantify brain-wide axonal innervation patterns supporting brain-wide signaling.

Unsupervised pattern identification in spatial gene expression atlas reveals mouse brain regions beyond established ontology

The rapid growth of large-scale spatial gene expression data demands efficient and reliable computational tools to extract major trends of gene expression in their native spatial context. Here, we used stability-driven unsupervised learning (i.e., staNMF) to identify principal patterns (PPs) of 3D gene expression profiles and understand spatial gene distribution and anatomical localization at the whole mouse brain level. Our subsequent spatial correlation analysis systematically compared the PPs to known anatomical regions and ontology from the Allen Mouse Brain Atlas using spatial neighborhoods. We demonstrate that our stable and spatially coherent PPs, whose linear combinations accurately approximate the spatial gene data, are highly correlated with combinations of expert-annotated brain regions. These PPs yield a brain ontology based purely on spatial gene expression. Our PP identification approach outperforms principal component analysis and typical clustering algorithms on the same task. Moreover, we show that the stable PPs reveal marked regional imbalance of brainwide genetic architecture, leading to region-specific marker genes and gene coexpression networks. Our findings highlight the advantages of stability-driven machine learning for plausible biological discovery from dense spatial gene expression data, streamlining tasks that are infeasible by conventional manual approaches.

High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain

Brain development is a highly complex process regulated by numerous genes at the molecular and cellular levels. Brain tissue exhibits serial microstructural changes during the development process. High-resolution diffusion magnetic resonance imaging (dMRI) affords a unique opportunity to probe these changes in the developing brain non-destructively. In this study, we acquired multi-shell dMRI datasets at 32 µm isotropic resolution to investigate the tissue microstructure alterations, which we believe to be the highest spatial resolution dMRI datasets obtained for postnatal mouse brains. We adapted the Allen Developing Mouse Brain Atlas (ADMBA) to integrate quantitative MRI metrics and spatial transcriptomics. Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) metrics were used to quantify brain development at different postnatal days. We demonstrated that the differential evolutions of fiber orientation distributions contribute to the distinct development patterns in white matter (WM) and gray matter (GM). Furthermore, the genes enriched in the nervous system that regulate brain structure and function were expressed in spatial correlation with age-matched dMRI. This study is the first one providing high-resolution dMRI, including DTI, DKI, and NODDI models, to trace mouse brain microstructural changes in WM and GM during postnatal development. This study also highlighted the genotype-phenotype correlation of spatial transcriptomics and dMRI, which may improve our understanding of brain microstructure changes at the molecular level.

Preliminary Validation of Stereotaxic Injection Coordinates via Cryosectioning.

Stereotaxic injection of a specific brain region constitutes a fundamental experimental technique in basic neuroscience. Researchers commonly base their choice of stereotaxic injection parameters on mouse brain atlases or published materials that employed various populations/ages of mice and different stereotaxic equipment, necessitating further validation of the stereotaxic coordinate parameters. The efficacy of calcium imaging, chemogenetic, and optogenetic manipulations relies on the precise expression of reporter genes within the region of interest, often requiring several weeks of effort. Thus, it is a time-consuming task if the coordinates of the target brain region are not verified in advance. Using an appropriate dye instead of a virus and implementing cryosectioning, researchers can observe the injection site immediately following dye administration. This facilitates timely adjustments to coordinate parameters in cases where discrepancies exist between the actual injection site and the theoretical position. Such adjustments significantly enhance the accuracy of viral expression within the target region in subsequent experiments.

Can We Explain Thousands of Molecularly Identified Mouse Neuronal Types? From Knowing to Understanding.

At the end of 2023, the Whole Mouse Brain Atlas was announced, revealing that there are about 5300 molecularly defined neuronal types in the mouse brain. We ask whether brain models exist that contemplate how this is possible. The conventional columnar model, implicitly used by the authors of the Atlas, is incapable of doing so with only 20 brain columns (5 brain vesicles with 4 columns each). We argue that the definition of some 1250 distinct progenitor microzones, each producing at least 4-5 neuronal types over time, may be sufficient. Presently, this is nearly achieved by the prosomeric model amplified by the secondary dorsoventral and anteroposterior microzonation of progenitor areas, plus the clonal variation in cell types produced, on average, by each of them.

Analysis of androgen receptor expression and activity in the mouse brain

Androgen deprivation therapy (ADT) is the core treatment for advanced prostate cancer (PCa), with a proven survival benefit. ADT lowers circulating testosterone levels throughout the body, but with it comes a variety of reported side effects including fatigue, muscle wastage, weight gain, hot flushes and importantly cognitive impairment, depression, and mood swings. Testosterone has a key role in brain masculinization, but its direct effects are relatively poorly understood, due both to the brain’s extreme complexity and the fact that some of testosterone activities are driven via local conversion to oestrogen, especially during embryonic development. The exact roles, function, and location of the androgen receptor (AR) in the adult male brain are still being discovered, and therefore the cognitive side effects of ADT may be unrecognized or under-reported. The age of onset of several neurological diseases overlap with PCa, therefore, there is a need to separate ADT side effects from such co-morbidities. Here we analysed the activity and expression level of the AR in the adult mouse brain, using an ARE-Luc reporter mouse and immunohistochemical staining for AR in all the key brain regions via coronal slices. We further analysed our data by comparing to the Allen Mouse Brain Atlas. AR-driven luciferase activity and distinct nuclear staining for AR were seen in several key brain areas including the thalamus, hypothalamus, olfactory bulb, cerebral cortex, Purkinje cells of the cerebellum and the hindbrain. We describe and discuss the potential role of AR in these areas, to inform and enable extrapolation to potential side effects of ADT in humans.

Cross-modality mapping using image varifolds to align tissue-scale atlases to molecular-scale measures with application to 2D brain sections

This paper explicates a solution to building correspondences between molecular-scale transcriptomics and tissue-scale atlases. This problem arises in atlas construction and cross-specimen/technology alignment where specimens per emerging technology remain sparse and conventional image representations cannot efficiently model the high dimensions from subcellular detection of thousands of genes. We address these challenges by representing spatial transcriptomics data as generalized functions encoding position and high-dimensional feature (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling regions as homogeneous random fields with unknown transcriptomic feature distribution. We solve simultaneously for the minimizing geodesic diffeomorphism of coordinates through LDDMM and for these latent feature densities. We map tissue-scale mouse brain atlases to gene-based and cell-based transcriptomics data from MERFISH and BARseq technologies and to histopathology and cross-species atlases to illustrate integration of diverse molecular and cellular datasets into a single coordinate system as a means of comparison and further atlas construction.

Ex vivo method for rapid quantification of post traumatic brain injury lesion volumes using ultrasound

BackgroundStudies of traumatic brain injury often involve the quantification of the lesion volume as a major outcome measure. The determination of lesion volume typically employs the cutting and mounting of brain tissue, and the calculation of the cross-sectional area of the lesion within each section of brain after histological staining. This is a time consuming and laborious task often requiring many weeks to determine the lesion volume for an individual brain. MethodsIn this report we present a method for determining the lesion volume within the brain following traumatic brain injury that involves the use of ultrasound imaging. With this process the lesion volume can be determined within a time period of 90 min per brain rather than weeks and months. Moreover, we have developed a pipeline that will combine the cross-sectional ultrasound images of the brain with the Allen Mouse Brain Atlas to provide the precise anatomical structures that are affected by traumatic injury to the brain. The anatomical detail was lastly paired with behavioral data showing neurological deficits correlated with specific areas of brain injury. ResultsThe accuracy and precision of this method was shown to be highly consistent with the traditional histological approach. Additionally, the mapping process and behavioral data show that neurological recovery from 1 to 3 weeks post injury is not correlated with gross anatomical recovery of the TBI lesion in our TBI model. ConclusionTogether these approaches will enhance the pipeline for processing brain tissue in experimental conditions where the lesion volume is an important outcome parameter and provide more high resolution information about the identity of the damaged regions of the brain.

Sex matters: The MouseX DW-ALLEN Atlas for mice diffusion-weighted MR imaging

Overcoming sex bias in preclinical research requires not only including animals of both sexes in the experiments, but also developing proper tools to handle such data. Recent work revealed sensitivity of diffusion-weighted MRI to glia morphological changes in response to inflammatory stimuli, opening up exciting possibilities to characterize inflammation in a variety of preclinical models of pathologies, the great majority of them available in mice. However, there are limited resources dedicated to mouse imaging, like those required for the data processing and analysis. To fill this gap, we build a mouse MRI template of both structural and diffusion contrasts, with anatomical annotation according to the Allen Mouse Brain Atlas, the most detailed public resource for mouse brain investigation. To achieve a standardized resource, we use a large cohort of animals in vivo, and include animals of both sexes. To prove the utility of this resource to integrate imaging and molecular data, we demonstrate significant association between the mean diffusivity from MRI and gene expression-based glia density. To demonstrate the need of equitable sex representation, we compared across sexes the warp fields needed to match a male-based template, and our template built with both sexes. Then, we use both templates for analysing mice imaging data obtained in animals of different ages, demonstrating that using a male-based template creates spurious significant sex effects, not present otherwise. All in all, our MouseX DW-ALLEN Atlas will be a widely useful resource getting us one step closer to equitable healthcare.

The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases.

Neuroscientists employ a range of methods and generate increasing amounts of data describing brain structure and function. The anatomical locations from which observations or measurements originate represent a common context for data interpretation, and a starting point for identifying data of interest. However, the multimodality and abundance of brain data pose a challenge for efforts to organize, integrate, and analyze data based on anatomical locations. While structured metadata allow faceted data queries, different types of data are not easily represented in a standardized and machine-readable way that allow comparison, analysis, and queries related to anatomical relevance. To this end, three-dimensional (3D) digital brain atlases provide frameworks in which disparate multimodal and multilevel neuroscience data can be spatially represented. We propose to represent the locations of different neuroscience data as geometric objects in 3D brain atlases. Such geometric objects can be specified in a standardized file format and stored as location metadata for use with different computational tools. We here present the Locare workflow developed for defining the anatomical location of data elements from rodent brains as geometric objects. We demonstrate how the workflow can be used to define geometric objects representing multimodal and multilevel experimental neuroscience in rat or mouse brain atlases. We further propose a collection of JSON schemas (LocareJSON) for specifying geometric objects by atlas coordinates, suitable as a starting point for co-visualization of different data in an anatomical context and for enabling spatial data queries.

PET Imaging of Rho‐Associated Protein Kinase 2 in A Mouse Model of Alzheimer’s Disease

AbstractBackgroundRho‐associated protein kinase 2 (ROCK2) activity is implicated in Alzheimer’s disease (AD) and other central nervous system (CNS) disorders 1. In this study, we investigated the relative expression levels of ROCK2 in APP/PS1 transgenic AD mice and age‐matched wild‐type (WT) C57BL/6J mice using the ROCK2‐specific PET radioligand, [11C]ROCK201.MethodsThe ROCK2 tracer [11C]ROCK201 was synthesized according to the previously published procedure 2. PET scans were performed in a Focus‐220 scanner on 12‐month‐old APP/PS1 transgenic mice (n = 8) and WT controls (n = 5). Self‐blocking scans were performed 10 min post injection (p.i.) of the unlabeled ROCK201 (i.v., 3.3 mg/kg). Regions of interest (ROIs) were extracted from the Ma‐Benveniste‐Mirrione mouse brain atlas and regional time‐activity curves (TACs) were obtained by applying template ROIs to the averaged PET images (0 to 60 min p.i.). Distribution volume ratio (DVR) values were generated using the simplified reference tissue model 2 (SRTM2) on the 60‐min dynamic PET imaging data, with cerebellum (CB) as the reference region. ROCK2 protein expression levels were assessed immunohistochemically in brain tissues of 12‐month‐old APP/PS1 (N = 3) and WT (N = 3) mice.ResultsUptake of [11C]ROCK201 was observed throughout the mouse brain, with peak SUV of 2.6. TACs were consistently higher in the hippocampus of APP/PS1 mice than controls, within 20 min p.i. (Fig. 1a). Reduced uptake was observed in self‐blocking studies, indicating specific binding of [11C]ROCK201 in the rodent brain (Fig. 1a). TACs were well fitted with SRTM2. Compared with age‐matched WT controls, the DVR(CB) in the hippocampus of APP/PS1 mice was 9.3% higher than that of WT mice (p = 0.03) (Fig. 1b). Consistent with PET imaging results, ROCK2 protein expression is elevated by 49±2% in the CA1 of APP/PS1 mice compared to that of WT mice (Fig. 1c).ConclusionsWe demonstrated the uptake and detection sensitivity of the radioligand [11C]ROCK201 in the mouse brain, with higher tracer uptake in the hippocampi of APP/PS1 mice as compared to WT mice, supporting the use of [11C]ROCK201 in preclinical AD drug discovery and development.

PET Imaging of Rho‐Associated Protein Kinase 2 in A Mouse Model of Alzheimer’s Disease

AbstractBackgroundRho‐associated protein kinase 2 (ROCK2) activity is implicated in Alzheimer’s disease (AD) and other central nervous system (CNS) disorders 1. In this study, we investigated the relative expression levels of ROCK2 in APP/PS1 transgenic AD mice and age‐matched wild‐type (WT) C57BL/6J mice using the ROCK2‐specific PET radioligand, [11C]ROCK201.MethodThe ROCK2 tracer [11C]ROCK201 was synthesized according to the previously published procedure 2. PET scans were performed in a Focus‐220 scanner on 12‐month‐old APP/PS1 transgenic mice (n = 8) and WT controls (n = 5). Self‐blocking scans were performed 10 min post injection (p.i.) of the unlabeled ROCK201 (i.v., 3.3 mg/kg). Regions of interest (ROIs) were extracted from the Ma‐Benveniste‐Mirrione mouse brain atlas and regional time‐activity curves (TACs) were obtained by applying template ROIs to the averaged PET images (0 to 60 min p.i.). Distribution volume ratio (DVR) values were generated using the simplified reference tissue model 2 (SRTM2) on the 60‐min dynamic PET imaging data, with cerebellum (CB) as the reference region. ROCK2 protein expression levels were assessed immunohistochemically in brain tissues of 12‐month‐old APP/PS1 (N = 3) and WT (N = 3) mice.ResultUptake of [11C]ROCK201 was observed throughout the mouse brain, with peak SUV of 2.6. TACs were consistently higher in the hippocampus of APP/PS1 mice than controls, within 20 min p.i. (Fig. 1a). Reduced uptake was observed in self‐blocking studies, indicating specific binding of [11C]ROCK201 in the rodent brain (Fig. 1a). TACs were well fitted with SRTM2. Compared with age‐matched WT controls, the DVR(CB) in the hippocampus of APP/PS1 mice was 9.3% higher than that of WT mice (p = 0.03) (Fig. 1b). Consistent with PET imaging results, ROCK2 protein expression is elevated by 49±2% in the CA1 of APP/PS1 mice compared to that of WT mice (Fig. 1c).ConclusionWe demonstrated the uptake and detection sensitivity of the radioligand [11C]ROCK201 in the mouse brain, with higher tracer uptake in the hippocampi of APP/PS1 mice as compared to WT mice, supporting the use of [11C]ROCK201 in preclinical AD drug discovery and development.

Functional Dissection of Ipsilateral and Contralateral Neural Activity Propagation Using Voltage-Sensitive Dye Imaging in Mouse Prefrontal Cortex.

Prefrontal cortex (PFC) intrahemispheric activity and the interhemispheric connection have a significant impact on neuropsychiatric disorder pathology. This study aimed to generate a functional map of FC intrahemispheric and interhemispheric connections. Functional dissection of mouse PFCs was performed using the voltage-sensitive dye (VSD) imaging method with high speed (1 ms/frame), high resolution (256 × 256 pixels), and a large field of view (∼10 mm). Acute serial 350 μm slices were prepared from the bregma covering the PFC and numbered 1-5 based on their distance from the bregma (i.e., 1.70, 1.34, 0.98, 0.62, and 0.26 mm) with reference to the Mouse Brain Atlas (Paxinos and Franklin, 2008). The neural response to electrical stimulation was measured at nine sites and then averaged, and a functional map of the propagation patterns was created. Intracortical propagation was observed in slices 3-5, encompassing the anterior cingulate cortex (ACC) and corpus callosum (CC). The activity reached area 33 of the ACC. Direct white matter stimulation activated area 33 in both hemispheres. Similar findings were obtained via DiI staining of the CC. Imaging analysis revealed directional biases in neural signals traveling within the ACC, whereby the signal transmission speed and probability varied based on the signal direction. Specifically, the spread of neural signals from cg2 to cg1 was stronger than that from cingulate cortex area 1(cg1) to cingulate cortex area 2(cg2), which has implications for interhemispheric functional connections. These findings highlight the importance of understanding the PFC functional anatomy in evaluating neuromodulators like serotonin and dopamine, as well as other factors related to neuropsychiatric diseases.

Prediction of Stroke Outcome in Mice Based on Noninvasive MRI and Behavioral Testing.

Prediction of poststroke outcome using the degree of subacute deficit or magnetic resonance imaging is well studied in humans. While mice are the most commonly used animals in preclinical stroke research, systematic analysis of outcome predictors is lacking. We intended to incorporate heterogeneity into our retrospective study to broaden the applicability of our findings and prediction tools. We therefore analyzed the effect of 30, 45, and 60 minutes of arterial occlusion on the variance of stroke volumes. Next, we built a heterogeneous cohort of 215 mice using data from 15 studies that included 45 minutes of middle cerebral artery occlusion and various genotypes. Motor function was measured using a modified protocol for the staircase test of skilled reaching. Phases of subacute and residual deficit were defined. Magnetic resonance images of stroke lesions were coregistered on the Allen Mouse Brain Atlas to characterize stroke topology. Different random forest prediction models that either used motor-functional deficit or imaging parameters were generated for the subacute and residual deficits. Variance of stroke volumes was increased by 45 minutes of arterial occlusion compared with 60 minutes. The inclusion of various genotypes enhanced heterogeneity further. We detected both a subacute and residual motor-functional deficit after stroke in mice and different recovery trajectories could be observed. In mice with small cortical lesions, lesion volume was the best predictor of the subacute deficit. The residual deficit could be predicted most accurately by the degree of the subacute deficit. When using imaging parameters for the prediction of the residual deficit, including information about the lesion topology increased prediction accuracy. A subset of anatomic regions within the ischemic lesion had particular impact on the prediction of long-term outcomes. Prediction accuracy depended on the degree of functional impairment. For the first time, we developed and validated a robust tool for the prediction of functional outcomes after experimental stroke in mice using a large and genetically heterogeneous cohort. These results are discussed in light of study design and imaging limitations. In the future, using outcome prediction can improve the design of preclinical studies and guide intervention decisions.

AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures

Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.

Mouse brain glycomics – Insights from exploring the Allen Brain Atlas and the implications for the neuroimmune brain

The Allen Institute Mouse Brain Atlas, with visualisation using the Brain Explorer software, offers a 3-dimensional view of region-specific RNA expression of thousands of mouse genes. In this Viewpoint, we focused on the region-specific expression of genes related to cellular glycosylation, and discuss their relevance towards psychoneuroimmunology. Using specific examples, we show that the Atlas validates existing observations reported by others, identifies previously unknown potential region-specific glycan features, and highlights the need to promote collaborations between glycobiology and psychoneuroimmunology researchers.

Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI

Diffusion magnetic resonance imaging (dMRI) tractography has yielded intriguing insights into brain circuits and their relationship to behavior in response to gene mutations or neurological diseases across a number of species. Still, existing tractography approaches suffer from limited sensitivity and specificity, leading to uncertain interpretation of the reconstructed connections. Hence, in this study, we aimed to optimize the imaging and computational pipeline to achieve the best possible spatial overlaps between the tractography and tracer-based axonal projection maps within the mouse brain corticothalamic network. We developed a dMRI-based atlas of the mouse forebrain with structural labels imported from the Allen Mouse Brain Atlas (AMBA). Using the atlas and dMRI tractography, we first reconstructed detailed node-to-node mouse brain corticothalamic structural connectivity matrices using different imaging and tractography parameters. We then investigated the effects of each condition for accurate reconstruction of the corticothalamic projections by quantifying the similarities between the tractography and the tracer data from the Allen Mouse Brain Connectivity Atlas (AMBCA). Our results suggest that these parameters significantly affect tractography outcomes and our atlas can be used to investigate macroscopic structural connectivity in the mouse brain. Furthermore, tractography in mouse brain gray matter still face challenges and need improved imaging and tractography methods.

A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting.

Brain atlases are widely used in neuroscience as resources for conducting experimental studies, and for integrating, analyzing, and reporting data from animal models. A variety of atlases are available, and it may be challenging to find the optimal atlas for a given purpose and to perform efficient atlas-based data analyses. Comparing findings reported using different atlases is also not trivial, and represents a barrier to reproducible science. With this perspective article, we provide a guide to how mouse and rat brain atlases can be used for analyzing and reporting data in accordance with the FAIR principles that advocate for data to be findable, accessible, interoperable, and re-usable. We first introduce how atlases can be interpreted and used for navigating to brain locations, before discussing how they can be used for different analytic purposes, including spatial registration and data visualization. We provide guidance on how neuroscientists can compare data mapped to different atlases and ensure transparent reporting of findings. Finally, we summarize key considerations when choosing an atlas and give an outlook on the relevance of increased uptake of atlas-based tools and workflows for FAIR data sharing.

Molecular identity of the lateral lemniscus nuclei in the adult mouse brain.

The dorsal (DLL), intermediate (ILL), and ventral (VLL) lateral lemniscus nuclei are relay centers in the central auditory pathway of the brainstem, commonly referred to as the lateral lemniscus nuclei (LLN). The LLN are situated in the prepontine and pontine hindbrain, from rhombomeres 1 to 4, extending from the more rostral DLL to the caudal VLL, with the ILL lying in between. These nuclei can be distinguished morphologically and by topological and connectivity criteria, and here, we set out to further characterize the molecular nature of each LLN. We searched in situ hybridization studies in the Allen Mouse Brain Atlas for genes differentially expressed along the rostrocaudal axis of the brainstem, identifying 36 genes from diverse functional families expressed in the LLN. Available information in the databases indicated that 7 of these 36 genes are either associated with or potentially related to hearing disorders. In conclusion, the LLN are characterized by specific molecular profiles that reflect their rostrocaudal organization into the three constituent nuclei. This molecular regionalization may be involved in the etiology of some hearing disorders, in accordance with previous functional studies of these genes.