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

The short-chain fatty acid acetate modulates orexin/hypocretin neurons: A novel mechanism in gut-brain axis regulation of energy homeostasis and feeding

The short-chain fatty acids (SCFAs) acetate, propionate and butyrate, the major products of intestinal microbial fermentation of dietary fibres, are involved in fine-tuning brain functions via the gut-brain axis. However, the effects of SCFAs in the hypothalamic neuronal network regulating several autonomic-brain functions are still unknown. Using NMR spectroscopy, we detected a reduction in brain acetate concentrations in the hypothalamus of obese leptin knockout ob/ob mice compared to lean wild-type littermates. Therefore, we investigated the effect of acetate on orexin/hypocretin neurons (hereafter referred as OX or OX-A neurons), a subset of hypothalamic neurons regulating energy homeostasis, which we have characterized in previous studies to be over-activated by the lack of leptin and enhancement of endocannabinoid tone in the hypothalamus of ob/ob mice. We found that acetate reduces food-intake in concomitance with a reduction of orexin neuronal activity in ob/ob mice. This was demonstrated by evaluating food-intake behaviour and orexin-A/c-FOS immunoreactivity coupled with patch-clamp recordings in Hcrt-eGFP neurons, quantification of prepro-orexin mRNA, and immunolabeling of GPR-43, the main acetate receptor. Our data provide new insights into the mechanisms of the effects of chronic dietary supplementation with acetate, or complex carbohydrates, on energy intake and body weight, which may be partly mediated by inhibition of orexinergic neuron activity.

Astrocyte switch to the hyperactive mode

Increasing pieces of evidence have suggested that astrocyte function has a strong influence on neuronal activity and plasticity, both in physiological and pathophysiological situations. In epilepsy, astrocytes have been shown to respond to epileptic neuronal seizures; however, whether they can act as a trigger for seizures has not been determined. Here, using the copper implantation method, spontaneous neuronal hyperactivity episodes were reliably induced during the week following implantation. With near 24-h continuous recording for over 1 week of the local field potential with in vivo electrophysiology and astrocyte cytosolic Ca2+ with the fiber photometry method, spontaneous occurrences of seizure episodes were captured. Approximately 1 day after the implantation, isolated aberrant astrocyte Ca2+ events were often observed before they were accompanied by neuronal hyperactivity, suggesting the role of astrocytes in epileptogenesis. Within a single developed episode, astrocyte Ca2+ increase preceded the neuronal hyperactivity by ~20 s, suggesting that actions originating from astrocytes could be the trigger for the occurrence of epileptic seizures. Astrocyte-specific stimulation by channelrhodopsin-2 or deep-brain direct current stimulation was capable of inducing neuronal hyperactivity. Injection of an astrocyte-specific metabolic inhibitor, fluorocitrate, was able to significantly reduce the magnitude of spontaneously occurring neuronal hyperactivity. These results suggest that astrocytes have a role in triggering individual seizures and the reciprocal astrocyte-neuron interactions likely amplify and exacerbate seizures. Therefore, future epilepsy treatment could be targeted at astrocytes to achieve epilepsy control.

Physiological characteristics of neurons in the mammillary bodies align with topographical organization of subicular inputs

The mammillary bodies (MBOs), a group of hypothalamic nuclei, play a pivotal role in memory formation and spatial navigation. They receive extensive inputs from the hippocampus through the fornix, but the physiological significance of these connections remains poorly understood. Damage to the MBOs is associated with various forms of anterograde amnesia. However, information about the physiological characteristics of the MBO is limited, primarily due to the limited number of studies that have directly monitored MBO activity along with population patterns of its upstream partners. Employing large-scale silicon probe recording in mice, we characterize MBO activity and its interaction with the subiculum across various brain states. We find that MBO cells are highly diverse in their relationship to theta, ripple, and slow oscillations. Several of the physiological features are inherited by the topographically organized inputs to MBO cells. Our study provides insights into the functional organization of the MBOs.

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.

Neutral or Detrimental Effects of TREM2 Agonist Antibodies in Preclinical Models of Alzheimer's Disease and Multiple Sclerosis

Human genetics and preclinical studies have identified key contributions of TREM2 to several neurodegenerative conditions, inspiring efforts to modulate TREM2 therapeutically. Here, we characterize the activities of three TREM2 agonist antibodies in multiple mixed-sex mouse models of Alzheimer's disease (AD) pathology and remyelination. Receptor activation and downstream signaling are explored in vitro, and active dose ranges are determined in vivo based on pharmacodynamic responses from microglia. For mice bearing amyloid-β (Aβ) pathology (PS2APP) or combined Aβ and tau pathology (TauPS2APP), chronic TREM2 agonist antibody treatment had limited impact on microglia engagement with pathology, overall pathology burden, or downstream neuronal damage. For mice with demyelinating injuries triggered acutely with lysolecithin, TREM2 agonist antibodies unexpectedly disrupted injury resolution. Likewise, TREM2 agonist antibodies limited myelin recovery for mice experiencing chronic demyelination from cuprizone. We highlight the contributions of dose timing and frequency across models. These results introduce important considerations for future TREM2-targeting approaches.

Noninvasive microvascular imaging in newborn rats using high-frequency ultrafast ultrasound

Ultrasound imaging stands as the predominant modality for neonatal health assessment, with recent advancements in ultrafast Doppler (μDoppler) technology offering significant promise in fields such as neonatal brain imaging. Combining μDoppler with high-frequency ultrasound (HF-μDoppler) presents a potential efficient avenue to enhance in vivo microvascular imaging in small animals, notably newborn rats, a crucial preclinical animal model for neonatal disease and development research. It is necessary to verify the imaging performance of HF-μDoppler in preclinical trials. This study investigates the microvascular imaging capabilities of HF-μDoppler using a 30 MHz high-frequency linear array probe in newborn rats. Results demonstrate the clarity of cerebral microvascular imaging in rats aged 1 to 7 postnatal days, extending to whole-body microvascular imaging, encompassing the central nervous system, including the brain and spinal cord. In conclusion, HF-μDoppler technology emerges as a reliable imaging tool, offering a new perspective for preclinical investigations into neonatal diseases and development.

A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity

The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features-e.g. diffusion parameters-or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.

Brain image data processing using collaborative data workflows on Texera

In the realm of neuroscience, mapping the three-dimensional (3D) neural circuitry and architecture of the brain is important for advancing our understanding of neural circuit organization and function. This study presents a novel pipeline that transforms mouse brain samples into detailed 3D brain models using a collaborative data analytics platform called "Texera." The user-friendly Texera platform allows for effective interdisciplinary collaboration between team members in neuroscience, computer vision, and data processing. Our pipeline utilizes the tile images from a serial two-photon tomography/TissueCyte system, then stitches tile images into brain section images, and constructs 3D whole-brain image datasets. The resulting 3D data supports downstream analyses, including 3D whole-brain registration, atlas-based segmentation, cell counting, and high-resolution volumetric visualization. Using this platform, we implemented specialized optimization methods and obtained significant performance enhancement in workflow operations. We expect the neuroscience community can adopt our approach for large-scale image-based data processing and analysis.

Functional ultrasound imaging and neuronal activity: how accurate is the spatiotemporal match?

Over the last decade, functional ultrasound (fUS) has risen as a critical tool in functional neuroimaging, leveraging hemodynamic changes to infer neural activity indirectly. Recent studies have established a strong correlation between neural spike rates (SR) and functional ultrasound signals. However, understanding their spatial distribution and variability across different brain areas is required to thoroughly interpret fUS signals. In this regard, we conducted simultaneous fUS imaging and Neuropixels recordings during stimulus-evoked activity in awake mice within three regions the visual pathway. Our findings indicate that the temporal dynamics of fUS and SR signals are linearly correlated, though the correlation coefficients vary among visual regions. Conversely, the spatial correlation between the two signals remains consistent across all regions with a spread of approximately 300 micrometers. Finally, we introduce a model that integrates the spatial and temporal components of the fUS signal, allowing for a more accurate interpretation of fUS images.

Structured connectivity in the output of the cerebellar cortex

The spatial organization of a neuronal circuit is critically important for its function since the location of neurons is often associated with function. In the cerebellum, the major output of the cerebellar cortex are synapses made from Purkinje cells onto neurons in the cerebellar nuclei, yet little has been known about the spatial organization of these synapses. We explored this question using whole-cell electrophysiology and optogenetics in acute sagittal cerebellar slices to produce spatial connectivity maps of cerebellar cortical output in mice. We observed non-random connectivity where Purkinje cell inputs clustered in cerebellar transverse zones: while many nuclear neurons received inputs from a single zone, several multi-zonal connectivity motifs were also observed. Single neurons receiving input from all four zones were overrepresented in our data. These findings reveal that the output of the cerebellar cortex is spatially structured and represents a locus for multimodal integration in the cerebellum.

Gapr for large-scale collaborative single-neuron reconstruction

Whole-brain analysis of single-neuron morphology is crucial for unraveling the complex structure of the brain. However, large-scale neuron reconstruction from terabyte and even petabyte data of mammalian brains generated by state-of-the-art light microscopy is a daunting task. Here, we developed 'Gapr' (Gapr accelerates projectome reconstruction) that streamlines deep learning-based automatic reconstruction, 'automatic proofreading' that reduces human workloads at high-confidence sites, and high-throughput collaborative proofreading by crowd users through the Internet. Furthermore, Gapr offers a seamless user interface that ensures high proofreading speed per annotator, on-demand conversion for handling large datasets, flexible workflows tailored to diverse datasets and rigorous error tracking for quality control. Finally, we demonstrated Gapr's efficacy by reconstructing over 4,000 neurons in mouse brains, revealing the morphological diversity in cortical interneurons and hypothalamic neurons. Here, we present Gapr as a solution for large-scale single-neuron reconstruction projects.

Widefield in vivo imaging system with two fluorescence and two reflectance channels, a single sCMOS detector, and shielded illumination

Significance

Widefield microscopy of the entire dorsal part of mouse cerebral cortex enables large-scale ("mesoscopic") imaging of different aspects of neuronal activity with spectrally compatible fluorescent indicators as well as hemodynamics via oxy- and deoxyhemoglobin absorption. Versatile and cost-effective imaging systems are needed for large-scale, color-multiplexed imaging of multiple fluorescent and intrinsic contrasts.

Aim

We aim to develop a system for mesoscopic imaging of two fluorescent and two reflectance channels.

Approach

Excitation of red and green fluorescence is achieved through epi-illumination. Hemoglobin absorption imaging is achieved using 525- and 625-nm light-emitting diodes positioned around the objective lens. An aluminum hemisphere placed between objective and cranial window provides diffuse illumination of the brain. Signals are recorded sequentially by a single sCMOS detector.

Results

We demonstrate the performance of our imaging system by recording large-scale spontaneous and stimulus-evoked neuronal, cholinergic, and hemodynamic activity in awake, head-fixed mice with a curved "crystal skull" window expressing the red calcium indicator jRGECO1a and the green acetylcholine sensorGRAB ACh 3.0 . Shielding of illumination light through the aluminum hemisphere enables concurrent recording of pupil diameter changes.

Conclusions

Our widefield microscope design with a single camera can be used to acquire multiple aspects of brain physiology and is compatible with behavioral readouts of pupil diameter.

Single-neuron projectome-guided analysis reveals the neural circuit mechanism underlying endogenous opioid antinociception

Endogenous opioid antinociception is a self-regulatory mechanism that reduces chronic pain, but its underlying circuit mechanism remains largely unknown. Here, we showed that endogenous opioid antinociception required the activation of mu-opioid receptors (MORs) in GABAergic neurons of the central amygdala nucleus (CEA) in a persistent-hyperalgesia mouse model. Pharmacogenetic suppression of these CEAMOR neurons, which mimics the effect of MOR activation, alleviated the persistent hyperalgesia. Furthermore, single-neuron projection analysis revealed multiple projectome-based subtypes of CEAMOR neurons, each innervating distinct target brain regions. We found that the suppression of axon branches projecting to the parabrachial nucleus (PB) of one subtype of CEAMOR neurons alleviated persistent hyperalgesia, indicating a subtype- and axonal-branch-specific mechanism of action. Further electrophysiological analysis revealed that suppression of a distinct CEA-PB disinhibitory circuit controlled endogenous opioid antinociception. Thus, this study identified the central neural circuit that underlies endogenous opioid antinociception, providing new insight into the endogenous pain modulatory mechanisms.

Hemorrhagic Shock and Resuscitation Causes Excessive Dopaminergic Signaling in the mPFC and Cognitive Dysfunction

Peri-operative hemorrhagic shock and resuscitation (HSR), a severe traumatic stress, is closely associated with post-operative anxiety, depression, and cognitive dysfunction, subsequently causing a serious burden on families and society. Following the co-release of corticotropin-releasing factor and catecholamine, traumatic stress activates dopaminergic neurons, increasing the addictive behavior and neurocognitive impairment risks. This study investigates the association between cognitive dysfunction and dopaminergic neurons in the mPFC under HSR conditions. This study established an HSR model by bleeding and re-transfusion in the mice. After HSR exposure, a dopamine D1 receptor antagonist, SKF-83566, was administered intraperitoneally for three consecutive days. Novel object recognition (NOR), conditioned fearing (FC), and conditioned place preference (CPP) were used to assess cognitive changes 16 days after HSR exposure. Local field potential (LFP) in the mPFC was also investigated during the novel object exploration. Compared with the mice exposed to sham, there was a significant decrease in the object recognition index, a reduction in context- and tone-related freezing time, an increase in CPP values, a downregulation of β-power but upregulation of γ-power in the mPFC in the mice exposed to HSR. Moreover, the mice exposed to HSR showed significantly upregulated TH-positive cell number, cleaved caspase-1- and TH-positive cells, and interleukin (IL)-1β/18 expression in the mPFC compared with sham; SKF-83566 could partially reverse these alternations. The HSR caused excessive dopaminergic signaling and cognitive dysfunction in the mPFC, a condition that might be ameliorated using a dopamine D1 receptor inhibitor.

Deep 3D histology powered by tissue clearing, omics and AI

To comprehensively understand tissue and organism physiology and pathophysiology, it is essential to create complete three-dimensional (3D) cellular maps. These maps require structural data, such as the 3D configuration and positioning of tissues and cells, and molecular data on the constitution of each cell, spanning from the DNA sequence to protein expression. While single-cell transcriptomics is illuminating the cellular and molecular diversity across species and tissues, the 3D spatial context of these molecular data is often overlooked. Here, I discuss emerging 3D tissue histology techniques that add the missing third spatial dimension to biomedical research. Through innovations in tissue-clearing chemistry, labeling and volumetric imaging that enhance 3D reconstructions and their synergy with molecular techniques, these technologies will provide detailed blueprints of entire organs or organisms at the cellular level. Machine learning, especially deep learning, will be essential for extracting meaningful insights from the vast data. Further development of integrated structural, molecular and computational methods will unlock the full potential of next-generation 3D histology.

Assessment of neurovascular uncoupling: APOE status is a key driver of early metabolic and vascular dysfunction

BACKGROUND

Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein Eε4 (APOEε4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection.

METHODS

PET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology.

RESULTS

All hAPOE strains showed AD phenotype progression by 8 months, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (↓ glucose uptake, ↑ perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated Type-2 uncoupling (↑ glucose uptake, ↓ perfusion), while immunopathology confirmed cell specific contributions.

DISCUSSION

This work highlights APOEε4 status in AD progression manifests as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker.

HIGHLIGHTS

We developed a novel analytical method to analyze PET imaging of 18F-FDG and 64Cu-PTSM data in both sexes of aging C57BL/6J, and hAPOEε3/ε3, hAPOEε4/ε4, and hAPOEε3/ε4 mice to assess metabolism-perfusion profiles termed neurovascular uncoupling. This analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (decreased glucose uptake, increased perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated significant Type-2 uncoupling (increased glucose uptake, decreased perfusion) by 8 months which aligns with immunopathology and transcriptomic signatures. This work highlights that there may be different mechanisms underlying age related changes in APOEε4/ε4 compared with APOEε3/ε4. We predict that these changes may be driven by immunological activation and response, and may serve as an early diagnostic biomarker.

Acetylcholine Neurons Become Cholinergic during Three Time Windows in the Developing Mouse Brain

Acetylcholine (ACh) neurons in the central nervous system are required for the coordination of neural network activity during higher brain functions, such as attention, learning, and memory, as well as locomotion. Disturbed cholinergic signaling has been described in many neurodevelopmental and neurodegenerative disorders. Furthermore, cotransmission of other signaling molecules, such as glutamate and GABA, with ACh has been associated with essential roles in brain function or disease. However, it is unknown when ACh neurons become cholinergic during development. Thus, understanding the timeline of how the cholinergic system develops and becomes active in the healthy brain is a crucial part of understanding brain development. To study this, we used transgenic mice to selectively label ACh neurons with tdTomato. We imaged serial sectioned brains and generated whole-brain reconstructions at different time points during pre- and postnatal development. We found three crucial time windows-two in the prenatal and one in the postnatal brain-during which most ACh neuron populations become cholinergic in the brain. We also found that cholinergic gene expression is initiated in cortical ACh interneurons, while the cerebral cortex is innervated by cholinergic projection neurons from the basal forebrain. Taken together, we show that ACh neuron populations are present and become cholinergic before postnatal day 12, which is the onset of major sensory processes, such as hearing and vision. We conclude that the birth of ACh neurons and initiation of cholinergic gene expression are temporally separated during development but highly coordinated by brain anatomical structure.

Deep brain stimulation of the Tbr1-deficient mouse model of autism spectrum disorder at the basolateral amygdala alters amygdalar connectivity, whole-brain synchronization, and social behaviors

Autism spectrum disorders (ASDs) are considered neural dysconnectivity syndromes. To better understand ASD and uncover potential treatments, it is imperative to know and dissect the connectivity deficits under conditions of autism. Here, we apply a whole-brain immunostaining and quantification platform to demonstrate impaired structural and functional connectivity and aberrant whole-brain synchronization in a Tbr1+/- autism mouse model. We express a channelrhodopsin variant oChIEF fused with Citrine at the basolateral amygdala (BLA) to outline the axonal projections of BLA neurons. By activating the BLA under blue light theta-burst stimulation (TBS), we then evaluate the effect of BLA activation on C-FOS expression at a whole brain level to represent neural activity. We show that Tbr1 haploinsufficiency almost completely disrupts contralateral BLA axonal projections and results in mistargeting in both ipsilateral and contralateral hemispheres, thereby globally altering BLA functional connectivity. Based on correlated C-FOS expression among brain regions, we further show that Tbr1 deficiency severely disrupts whole-brain synchronization in the absence of salient stimulation. Tbr1+/- and wild-type (WT) mice exhibit opposing responses to TBS-induced amygdalar activation, reducing synchronization in WT mice but enhancing it in Tbr1+/- mice. Whole-brain modular organization and intermodule connectivity are also affected by Tbr1 deficiency and amygdalar activation. Following BLA activation by TBS, the synchronizations of the whole brain and the default mode network, a specific subnetwork highly relevant to ASD, are enhanced in Tbr1+/- mice, implying a potential ameliorating effect of amygdalar stimulation on brain function. Indeed, TBS-mediated BLA activation increases nose-to-nose social interactions of Tbr1+/- mice, strengthening evidence for the role of amygdalar connectivity in social behaviors. Our high-resolution analytical platform reveals the inter- and intrahemispheric connectopathies arising from ASD. Our study emphasizes the defective synchronization at a whole-brain scale caused by Tbr1 deficiency and implies a potential beneficial effect of deep brain stimulation at the amygdala for TBR1-linked autism.

Decoding state-dependent cortical-cerebellar cellular functional connectivity in the mouse brain

The cortex and cerebellum form multi-synaptic reciprocal connections. We investigate the functional connectivity between single spiking cerebellar neurons and the population activity of the mouse dorsal cortex using mesoscale imaging. Cortical representations of individual cerebellar neurons vary significantly across different brain states but are drawn from a common set of cortical networks. These cortical-cerebellar connectivity features are observed in mossy fibers and Purkinje cells as well as neurons in different cerebellar lobules, albeit with variations across cell types and regions. Complex spikes of Purkinje cells preferably associate with the sensorimotor cortex, whereas simple spikes display more diverse cortical connectivity patterns. The spontaneous functional connectivity patterns align with cerebellar neurons' functional responses to external stimuli in a modality-specific manner. The tuning properties of subsets of cerebellar neurons differ between anesthesia and awake states, mirrored by state-dependent changes in their long-range functional connectivity patterns with mesoscale cortical activity.

Cerebral cortical functional hyperconnectivity in a mouse model of spinocerebellar ataxia type 8 (SCA8)

Spinocerebellar Ataxia Type 8 (SCA8) is an inherited neurodegenerative disease caused by a bidirectionally expressed CTG●CAG expansion mutation in the ATXN-8 and ATXN8-OS genes. While primarily a motor disorder, psychiatric and cognitive symptoms have been reported. It is difficult to elucidate how the disease alters brain function in areas with little or no degeneration producing both motor and cognitive symptoms. Using transparent polymer skulls and CNS-wide GCaMP6f expression, we studied neocortical networks throughout SCA8 progression using wide-field Ca2+ imaging in a transgenic mouse model of SCA8. We observed that neocortical networks in SCA8+ mice were hyperconnected globally which led to network configurations with increased global efficiency and centrality. At the regional level, significant network changes occurred in nearly all cortical regions, however mainly involved sensory and association cortices. Changes in functional connectivity in anterior motor regions worsened later in the disease. Near perfect decoding of animal genotype was obtained using a generalized linear model based on canonical correlation strengths between activity in cortical regions. The major contributors to decoding were concentrated in the somatosensory, higher visual and retrosplenial cortices and occasionally extended into the motor regions, demonstrating that the areas with the largest network changes are predictive of disease state.

Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development

Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.

Multimodal identification of the mouse brain using simultaneous Ca 2+ imaging and fMRI

Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the workhorse in this arena, BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI) suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed. Here, we apply simultaneous wide-field fluorescence calcium imaging and BOLD-fMRI in mice to interrogate individual differences using a connectome-based identification framework adopted from the human fMRI literature. This approach yields high spatiotemporal resolution cell-type specific signals (here, from glia, excitatory, as well as inhibitory interneurons) from the whole cortex. We found mouse multimodal connectome- based identification to be successful and explored various features of these data.

The transcriptomic and spatial organization of telencephalic GABAergic neuronal types

The telencephalon of the mammalian brain comprises multiple regions and circuit pathways that play adaptive and integrative roles in a variety of brain functions. There is a wide array of GABAergic neurons in the telencephalon; they play a multitude of circuit functions, and dysfunction of these neurons has been implicated in diverse brain disorders. In this study, we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished by utilizing 611,423 single-cell transcriptomes from the comprehensive and high-resolution transcriptomic and spatial cell type atlas for the adult whole mouse brain we have generated, supplemented with an additional single-cell RNA-sequencing dataset containing 99,438 high-quality single-cell transcriptomes collected from the pre- and postnatal developing mouse brain. We present a hierarchically organized adult telencephalic GABAergic neuronal cell type taxonomy of 7 classes, 52 subclasses, 284 supertypes, and 1,051 clusters, as well as a corresponding developmental taxonomy of 450 clusters across different ages. Detailed charting efforts reveal extraordinary complexity where relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types can often be found in distant and diverse brain regions indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Additionally, we find various spatial dimensions of both discrete and continuous variations among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal and most pallidal GABAergic neuronal types emerge simultaneously during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell type taxonomy can serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community.

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Interactive data exploration websites for large-scale electrophysiology

Methodological advances in neuroscience have enabled the collection of massive datasets which demand innovative approaches for scientific communication. Existing platforms for data storage lack intuitive tools for data exploration, limiting our ability to interact effectively with these brain-wide datasets. We introduce two public websites: (Data and Atlas) developed for the International Brain Laboratory which provide access to millions of behavioral trials and hundreds of thousands of individual neurons. These interfaces allow users to discover both the raw and processed brain-wide data released by the IBL at the scale of the whole brain, individual sessions, trials, and neurons. By hosting these data interfaces as websites they are available cross-platform with no installation. By releasing each site's code as a modular open-source framework, other researchers can easily develop their own web interfaces and explore their own data. As neuroscience datasets continue to expand, customizable web interfaces offer a glimpse into a future of streamlined data exploration and act as blueprints for future tools.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Characterizing defective lipid metabolism in the lateral septum of mice treated with olanzapine: implications for its side effects

Schizophrenia significantly impacts cognitive and behavioral functions and is primarily treated with second-generation antipsychotics (SGAs) such as olanzapine. Despite their efficacy, these drugs are linked to serious metabolic side effects which can diminish patient compliance, worsen psychiatric symptoms and increase cardiovascular disease risk. This study explores the hypothesis that SGAs affect the molecular determinants of synaptic plasticity and brain activity, particularly focusing on the lateral septum (LS) and its interactions within hypothalamic circuits that regulate feeding and energy expenditure. Utilizing functional ultrasound imaging, RNA sequencing, and weighted gene co-expression network analysis, we identified significant alterations in the functional connection between the hypothalamus and LS, along with changes in gene expression in the LS of mice following prolonged olanzapine exposure. Our analysis revealed a module closely linked to increases in body weight and adiposity, featuring genes primarily involved in lipid metabolism pathways, notably Apoa1, Apoc3, and Apoh. These findings suggest that olanzapine may influence body weight and adiposity through its impact on lipid metabolism-related genes in the LS. Therefore, the neural circuits connecting the LS and LH, along with the accompanying alterations in lipid metabolism, are likely crucial factors contributing to the weight gain and metabolic side effects associated with olanzapine treatment.

Data-driven fine-grained region discovery in the mouse brain with transformers

Technologies such as spatial transcriptomics offer unique opportunities to define the spatial organization of the mouse brain. We developed an unsupervised training scheme and novel transformer-based deep learning architecture to detect spatial domains across the whole mouse brain using spatial transcriptomics data. Our model learns local representations of molecular and cellular statistical patterns which can be clustered to identify spatial domains within the brain from coarse to fine-grained. Discovered domains are spatially regular, even with several hundreds of spatial clusters. They are also consistent with existing anatomical ontologies such as the Allen Mouse Brain Common Coordinate Framework version 3 (CCFv3) and can be visually interpreted at the cell type or transcript level. We demonstrate our method can be used to identify previously uncatalogued subregions, such as in the midbrain, where we uncover gradients of inhibitory neuron complexity and abundance. Notably, these subregions cannot be discovered using other methods. We apply our method to a separate multi-animal whole-brain spatial transcriptomic dataset and show that our method can also robustly integrate spatial domains across animals.

Gene count normalization in single-cell imaging-based spatially resolved transcriptomics

BACKGROUND

Recent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted genes and their locations in fixed tissues. Normalization of gene expression data is often needed to account for technical factors that may confound underlying biological signals.

RESULTS

Here, we investigate the potential impact of different gene count normalization methods with different targeted gene panels in the analysis and interpretation of im-SRT data. Using different simulated gene panels that overrepresent genes expressed in specific tissue regions or cell types, we demonstrate how normalization methods based on detected gene counts per cell differentially impact normalized gene expression magnitudes in a region- or cell type-specific manner. We show that these normalization-induced effects may reduce the reliability of downstream analyses including differential gene expression, gene fold change, and spatially variable gene analysis, introducing false positive and false negative results when compared to results obtained from gene panels that are more representative of the gene expression of the tissue's component cell types. These effects are not observed with normalization approaches that do not use detected gene counts for gene expression magnitude adjustment, such as with cell volume or cell area normalization.

CONCLUSIONS

We recommend using non-gene count-based normalization approaches when feasible and evaluating gene panel representativeness before using gene count-based normalization methods if necessary. Overall, we caution that the choice of normalization method and gene panel may impact the biological interpretation of the im-SRT data.

Simple spike patterns and synaptic mechanisms encoding sensory and motor signals in Purkinje cells and the cerebellar nuclei

Whisker stimulation in awake mice evokes transient suppression of simple spike probability in crus I/II Purkinje cells. Here, we investigated how simple spike suppression arises synaptically, what it encodes, and how it affects cerebellar output. In vitro, monosynaptic parallel fiber (PF)-excitatory postsynaptic currents (EPSCs) facilitated strongly, whereas disynaptic inhibitory postsynaptic currents (IPSCs) remained stable, maximizing relative inhibitory strength at the onset of PF activity. Short-term plasticity thus favors the inhibition of Purkinje spikes before PFs facilitate. In vivo, whisker stimulation evoked a 2-6 ms synchronous spike suppression, just 6-8 ms (∼4 synaptic delays) after sensory onset, whereas active whisker movements elicited broadly timed spike rate increases that did not modulate sensory-evoked suppression. Firing in the cerebellar nuclei (CbN) inversely correlated with disinhibition from sensory-evoked simple spike suppressions but was decoupled from slow, non-synchronous movement-associated elevations of Purkinje firing rates. Synchrony thus allows the CbN to high-pass filter Purkinje inputs, facilitating sensory-evoked cerebellar outputs that can drive movements.

Connecto-informatics at the mesoscale: current advances in image processing and analysis for mapping the brain connectivity

Mapping neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow aging and diseases. Developments in imaging technology, such as microscopy and labeling tools, have allowed researchers to visualize this connectivity through high-resolution brain-wide imaging. With this, image processing and analysis have become more crucial. However, despite the wealth of neural images generated, access to an integrated image processing and analysis pipeline to process these data is challenging due to scattered information on available tools and methods. To map the neural connections, registration to atlases and feature extraction through segmentation and signal detection are necessary. In this review, our goal is to provide an updated overview of recent advances in these image-processing methods, with a particular focus on fluorescent images of the mouse brain. Our goal is to outline a pathway toward an integrated image-processing pipeline tailored for connecto-informatics. An integrated workflow of these image processing will facilitate researchers' approach to mapping brain connectivity to better understand complex brain networks and their underlying brain functions. By highlighting the image-processing tools available for fluroscent imaging of the mouse brain, this review will contribute to a deeper grasp of connecto-informatics, paving the way for better comprehension of brain connectivity and its implications.

The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex

Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.

Repairing the in situ hybridization missing data in the hippocampus region by using a 3D residual U-Net model

The hippocampus is a critical brain region. Transcriptome data provides valuable insights into the structure and function of the hippocampus at the gene level. However, transcriptome data is often incomplete. To address this issue, we use the convolutional neural network model to repair the missing voxels in the hippocampus region, based on Allen institute coronal slices in situ hybridization (ISH) dataset. Moreover, we analyze the gene expression correlation between coronal and sagittal dataset in the hippocampus region. The results demonstrated that the trend of gene expression correlation between the coronal and sagittal datasets remained consistent following the repair of missing data in the coronal ISH dataset. In the last, we use repaired ISH dataset to identify novel genes specific to hippocampal subregions. Our findings demonstrate the accuracy and effectiveness of using deep learning method to repair ISH missing data. After being repaired, ISH has the potential to improve our comprehension of the hippocampus's structure and function.

3-Dimensional Reconstruction From Histopathological Sections: A Systematic Review

Although pathological tissue analysis is typically performed on single 2-dimensional (2D) histologic reference slides, 3-dimensional (3D) reconstruction from a sequence of histologic sections could provide novel opportunities for spatial analysis of the extracted tissue. In this review, we analyze recent works published after 2018 and report information on the extracted tissue types, the section thickness, and the number of sections used for reconstruction. By analyzing the technological requirements for 3D reconstruction, we observe that software tools exist, both free and commercial, which include the functionality to perform 3D reconstruction from a sequence of histologic images. Through the analysis of the most recent works, we provide an overview of the workflows and tools that are currently used for 3D reconstruction from histologic sections and address points for future work, such as a missing common file format or computer-aided analysis of the reconstructed model.

Efferent projections of Nps-expressing neurons in the parabrachial region

In the brain, connectivity determines function. Neurons in the parabrachial nucleus (PB) relay diverse information to widespread brain regions, but the connections and functions of PB neurons that express Nps (neuropeptide S, NPS) remain mysterious. Here, we use Cre-dependent anterograde tracing and whole-brain analysis to map their output connections. While many other PB neurons project ascending axons through the central tegmental tract, NPS axons reach the forebrain via distinct periventricular and ventral pathways. Along the periventricular pathway, NPS axons target the tectal longitudinal column and periaqueductal gray, then continue rostrally to target the paraventricular nucleus of the thalamus. Along the ventral pathway, NPS axons blanket much of the hypothalamus but avoid the ventromedial and mammillary nuclei. They also project prominently to the ventral bed nucleus of the stria terminalis, A13 cell group, and magnocellular subparafasciular nucleus. In the hindbrain, NPS axons have fewer descending projections, targeting primarily the superior salivatory nucleus, nucleus of the lateral lemniscus, and periolivary region. Combined with what is known already about NPS and its receptor, the output pattern of Nps-expressing neurons in the PB region predicts roles in threat response and circadian behavior.

A miniaturized mesoscope for the large-scale single-neuron-resolved imaging of neuronal activity in freely behaving mice

Exploring the relationship between neuronal dynamics and ethologically relevant behaviour involves recording neuronal-population activity using technologies that are compatible with unrestricted animal behaviour. However, head-mounted microscopes that accommodate weight limits to allow for free animal behaviour typically compromise field of view, resolution or depth range, and are susceptible to movement-induced artefacts. Here we report a miniaturized head-mounted fluorescent mesoscope that we systematically optimized for calcium imaging at single-neuron resolution, for increased fields of view and depth of field, and for robustness against motion-generated artefacts. Weighing less than 2.5 g, the mesoscope enabled recordings of neuronal-population activity at up to 16 Hz, with 4 μm resolution over 300 μm depth-of-field across a field of view of 3.6 × 3.6 mm2 in the cortex of freely moving mice. We used the mesoscope to record large-scale neuronal-population activity in socially interacting mice during free exploration and during fear-conditioning experiments, and to investigate neurovascular coupling across multiple cortical regions.

Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice

The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow for simultaneous access to nearly all 0f the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.

The mouse motor system contains multiple premotor areas and partially follows human organizational principles

While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher-order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we show that axonal tracer, functional connectivity, myelin mapping, gene expression, and optogenetics data contradict this notion. Our analyses reveal three premotor areas in the mouse, anterior-lateral motor cortex (ALM), anterior-lateral M2 (aM2), and posterior-medial M2 (pM2), with distinct structural, functional, and behavioral properties. By using the same techniques across mice and humans, we show that ALM has strikingly similar functional and microstructural properties to human anterior ventral premotor areas and that aM2 and pM2 amalgamate properties of human pre-SMA and cingulate cortex. These results provide evidence for the existence of multiple premotor areas in the mouse and chart a comparative map between the motor systems of humans and mice.

Organization of corticocortical and thalamocortical top-down inputs in the primary visual cortex

Unified visual perception requires integration of bottom-up and top-down inputs in the primary visual cortex (V1), yet the organization of top-down inputs in V1 remains unclear. Here, we used optogenetics-assisted circuit mapping to identify how multiple top-down inputs from higher-order cortical and thalamic areas engage V1 excitatory and inhibitory neurons. Top-down inputs overlap in superficial layers yet segregate in deep layers. Inputs from the medial secondary visual cortex (V2M) and anterior cingulate cortex (ACA) converge on L6 Pyrs, whereas ventrolateral orbitofrontal cortex (ORBvl) and lateral posterior thalamic nucleus (LP) inputs are processed in parallel in Pyr-type-specific subnetworks (Pyr←ORBvl and Pyr←LP) and drive mutual inhibition between them via local interneurons. Our study deepens understanding of the top-down modulation mechanisms of visual processing and establishes that V2M and ACA inputs in L6 employ integrated processing distinct from the parallel processing of LP and ORBvl inputs in L5.

Repetitive mild closed-head injury induced synapse loss and increased local BOLD-fMRI signal homogeneity

Repeated mild head injuries due to sports, or domestic violence and military service are increasingly linked to debilitating symptoms in the long term. Although symptoms may take decades to manifest, potentially treatable neurobiological alterations must begin shortly after injury. Better means to diagnose and treat traumatic brain injuries, requires an improved understanding of the mechanisms underlying progression and means through which they can be measured. Here, we employ a repetitive mild closed-head injury (rmTBI) and chronic variable stress (CVS) mouse model to investigate emergent structural and functional brain abnormalities. Brain imaging is achieved with [ 18 F]SynVesT-1 positron emission tomography, with the synaptic vesicle glycoprotein 2A ligand marking synapse density and BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI). Animals were scanned six weeks after concluding rmTBI/Stress procedures. Injured mice showed widespread decreases in synaptic density coupled with an i ncrease in local BOLD-fMRI synchrony detected as regional homogeneity. Injury-affected regions with higher synapse density showed a greater increase in fMRI regional homogeneity. Taken together, these observations may reflect compensatory mechanisms following injury. Multimodal studies are needed to provide deeper insights into these observations.

Classification of psychedelic drugs based on brain-wide imaging of cellular c-Fos expression

Psilocybin, ketamine, and MDMA are psychoactive compounds that exert behavioral effects with distinguishable but also overlapping features. The growing interest in using these compounds as therapeutics necessitates preclinical assays that can accurately screen psychedelics and related analogs. We posit that a promising approach may be to measure drug action on markers of neural plasticity in native brain tissues. We therefore developed a pipeline for drug classification using light sheet fluorescence microscopy of immediate early gene expression at cellular resolution followed by machine learning. We tested male and female mice with a panel of drugs, including psilocybin, ketamine, 5-MeO-DMT, 6-fluoro-DET, MDMA, acute fluoxetine, chronic fluoxetine, and vehicle. In one-versus-rest classification, the exact drug was identified with 67% accuracy, significantly above the chance level of 12.5%. In one-versus-one classifications, psilocybin was discriminated from 5-MeO-DMT, ketamine, MDMA, or acute fluoxetine with >95% accuracy. We used Shapley additive explanation to pinpoint the brain regions driving the machine learning predictions. Our results support a novel approach for screening psychoactive drugs with psychedelic properties.

SpatialPrompt: spatially aware scalable and accurate tool for spot deconvolution and domain identification in spatial transcriptomics

Efficiently mapping of cell types in situ remains a major challenge in spatial transcriptomics. Most spot deconvolution tools ignore spatial coordinate information and perform extremely slow on large datasets. Here, we introduce SpatialPrompt, a spatially aware and scalable tool for spot deconvolution and domain identification. SpatialPrompt integrates gene expression, spatial location, and single-cell RNA sequencing (scRNA-seq) dataset as reference to accurately infer cell-type proportions of spatial spots. SpatialPrompt uses non-negative ridge regression and graph neural network to efficiently capture local microenvironment information. Our extensive benchmarking analysis on Visium, Slide-seq, and MERFISH datasets demonstrated superior performance of SpatialPrompt over 15 existing tools. On mouse hippocampus dataset, SpatialPrompt achieves spot deconvolution and domain identification within 2 minutes for 50,000 spots. Overall, domain identification using SpatialPrompt was 44 to 150 times faster than existing methods. We build a database housing 40 plus curated scRNA-seq datasets for seamless integration with SpatialPrompt for spot deconvolution.

A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale

Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 μm × 0.65 μm × 3 μm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain's 3D anatomical structure.

SpaNCMG: improving spatial domains identification of spatial transcriptomics using neighborhood-complementary mixed-view graph convolutional network

The advancement of spatial transcriptomics (ST) technology contributes to a more profound comprehension of the spatial properties of gene expression within tissues. However, due to challenges of high dimensionality, pronounced noise and dynamic limitations in ST data, the integration of gene expression and spatial information to accurately identify spatial domains remains challenging. This paper proposes a SpaNCMG algorithm for the purpose of achieving precise spatial domain description and localization based on a neighborhood-complementary mixed-view graph convolutional network. The algorithm enables better adaptation to ST data at different resolutions by integrating the local information from KNN and the global structure from r-radius into a complementary neighborhood graph. It also introduces an attention mechanism to achieve adaptive fusion of different reconstructed expressions, and utilizes KPCA method for dimensionality reduction. The application of SpaNCMG on five datasets from four sequencing platforms demonstrates superior performance to eight existing advanced methods. Specifically, the algorithm achieved highest ARI accuracies of 0.63 and 0.52 on the datasets of the human dorsolateral prefrontal cortex and mouse somatosensory cortex, respectively. It accurately identified the spatial locations of marker genes in the mouse olfactory bulb tissue and inferred the biological functions of different regions. When handling larger datasets such as mouse embryos, the SpaNCMG not only identified the main tissue structures but also explored unlabeled domains. Overall, the good generalization ability and scalability of SpaNCMG make it an outstanding tool for understanding tissue structure and disease mechanisms. Our codes are available at https://github.com/ZhihaoSi/SpaNCMG.

Establishing neuroanatomical correspondences across mouse and marmoset brain structures

Interest in the common marmoset is growing due to evolutionarily proximity to humans compared to laboratory mice, necessitating a comparison of mouse and marmoset brain architectures, including connectivity and cell type distributions. Creating an actionable comparative platform is challenging since these brains have distinct spatial organizations and expert neuroanatomists disagree. We propose a general theoretical framework to relate named atlas compartments across taxa and use it to establish a detailed correspondence between marmoset and mice brains. Contrary to conventional wisdom that brain structures may be easier to relate at higher levels of the atlas hierarchy, we find that finer parcellations at the leaf levels offer greater reconcilability despite naming discrepancies. Utilizing existing atlases and associated literature, we created a list of leaf-level structures for both species and establish five types of correspondence between them. One-to-one relations were found between 43% of the structures in mouse and 47% in marmoset, whereas 25% of mouse and 10% of marmoset structures were not relatable. The remaining structures show a set of more complex mappings which we quantify. Implementing this correspondence with volumetric atlases of the two species, we make available a computational tool for querying and visualizing relationships between the corresponding brains. Our findings provide a foundation for computational comparative analyses of mesoscale connectivity and cell type distributions in the laboratory mouse and the common marmoset.

Where Top-Down Meets Bottom-Up: Cell-Type Specific Connectivity Map of the Whisker System

Sensorimotor computation integrates bottom-up world state information with top-down knowledge and task goals to form action plans. In the rodent whisker system, a prime model of active sensing, evidence shows neuromodulatory neurotransmitters shape whisker control, affecting whisking frequency and amplitude. Since neuromodulatory neurotransmitters are mostly released from subcortical nuclei and have long-range projections that reach the rest of the central nervous system, mapping the circuits of top-down neuromodulatory control of sensorimotor nuclei will help to systematically address the mechanisms of active sensing. Therefore, we developed a neuroinformatic target discovery pipeline to mine the Allen Institute's Mouse Brain Connectivity Atlas. Using network connectivity analysis, we identified new putative connections along the whisker system and anatomically confirmed the existence of 42 previously unknown monosynaptic connections. Using this data, we updated the sensorimotor connectivity map of the mouse whisker system and developed the first cell-type-specific map of the network. The map includes 157 projections across 18 principal nuclei of the whisker system and neuromodulatory neurotransmitter-releasing. Performing a graph network analysis of this connectome, we identified cell-type specific hubs, sources, and sinks, provided anatomical evidence for monosynaptic inhibitory projections into all stages of the ascending pathway, and showed that neuromodulatory projections improve network-wide connectivity. These results argue that beyond the modulatory chemical contributions to information processing and transfer in the whisker system, the circuit connectivity features of the neuromodulatory networks position them as nodes of sensory and motor integration.

Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model

Alzheimer's disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.

Direct neuronal protection by the protease-activated receptor PAR4 antagonist ML354 after experimental stroke in mice

BACKGROUND AND PURPOSE

Thrombo-inflammation is a key feature of stroke pathophysiology and provides multiple candidate drug targets. Thrombin exerts coagulation-independent actions via protease-activated receptors (PAR), of which PAR1 has been implicated in stroke-associated neuroinflammation. The role of PAR4 in this context is less clear. This study examined if the selective PAR4 antagonist ML354 provides neuroprotection in experimental stroke and explored the underlying mechanisms.

EXPERIMENTAL APPROACH

Mouse primary cortical neurons were exposed to oxygen-glucose deprivation (OGD) and simulated reperfusion ± ML354. For comparison, functional Ca2+-imaging was performed upon acute stimulation with a PAR4 activating peptide or glutamate. Male mice underwent sham operation or transient middle cerebral artery occlusion (tMCAO), with ML354 or vehicle treatment beginning at recanalization. A subset of mice received a platelet-depleting antibody. Stroke size and functional outcomes were assessed. Abundance of target genes, proteins, and cell markers was determined in cultured cells and tissues by qPCR, immunoblotting, and immunofluorescence.

KEY RESULTS

Stroke up-regulated PAR4 expression in cortical neurons in vitro and in vivo. OGD augments spontaneous and PAR4-mediated neuronal activity; ML354 suppresses OGD-induced neuronal excitotoxicity and apoptosis. ML354 applied in vivo after tMCAO reduced infarct size, apoptotic markers, macrophage accumulation, and interleukin-1β expression. Platelet depletion did not affect infarct size in mice with tMCAO ± ML354.

CONCLUSIONS AND IMPLICATIONS

Selective PAR4 inhibition during reperfusion improves infarct size and neurological function after experimental stroke by blunting neuronal excitability, apoptosis, and local inflammation. PAR4 antagonists may provide additional neuroprotective benefits in patients with acute stroke beyond their canonical antiplatelet action.

Direct comparison of Hoxb8-driven reporter distribution in the brains of four transgenic mouse lines: towards a spinofugal projection atlas

Introduction

Hox genes govern rostro-caudal identity along the developing spinal cord, which has a well-defined division of function between dorsal (sensory) and ventral (motor) halves. Here we exploit developmental Hoxb8 expression, normally restricted to the dorsal cord below the obex, to genetically label spinal cord-to-brain ("spinofugal") axons.

Methods

We crossed two targeted (knock-in) and two non-targeted recombinase-expressing lines (Hoxb8-IRES-Cre and Hoxb8-T2AFlpO; Hoxb8-Cre and Hoxb8-FlpO, respectively) with appropriate tdtomato-expressing reporter strains. Serial sectioning, confocal and superresolution microscopy, as well as light-sheet imaging was used to reveal robust labeling of ascending axons and their terminals in expected and unexpected regions.

Results

This strategy provides unprecedented anatomical detail of ascending spinal tracts anterior to the brainstem, and reveals a previously undescribed decussating tract in the ventral hypothalamus (the spinofugal hypothalamic decussating tract, or shxt). The absence of Hoxb8-suppressing elements led to multiple instances of ectopic reporter expression in Hoxb8-Cre mice (retinal ganglion and vomeronasal axons, anterior thalamic nuclei and their projections to the anterior cingulate and retrosplenial cortices and subiculum, and a population of astrocytes at the cephalic flexure) and Hoxb8-FlpO mice (Cajal-Retzius cells of the dentate gyrus, and mesenchymal cells of the choroid plexus). While targeted transgenic lines were similar in terms of known spinofugal projections, Hoxb8-IRES-Cre reporters had an additional projection to the core of the facial motor nucleus, and more abundant Hoxb8-lineage microglia scattered throughout the brain than Hoxb8-T2A-FlpO (or any other) mice, suggesting dysregulated Hoxb8-driven reporter expression in one or both lines.

Discussion

This work complements structural and connectivity atlases of the mouse central nervous system, and provides a platform upon which their reactions to injury or disease can be studied. Ectopic Hoxb8-driven recombinase expression may also be a useful tool to study structure and function of other cell populations in non-targeted lines.