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Abstract Background The medial prefrontal cortex (mPFC) is involved in complex functions containing multiple types of neurons in distinct subregions with preferential roles. The pyramidal neurons had wide-range projections to cortical and subcortical regions with subregional preferences. Using a combination of viral tracing and fluorescence micro-optical sectioning tomography (fMOST) in transgenic mice, we systematically dissected the whole-brain connectomes of intratelencephalic (IT) and pyramidal tract (PT) neurons in four mPFC subregions. Results IT and PT neurons of the same subregion projected to different target areas while receiving inputs from similar upstream regions with quantitative differences. IT and PT neurons all project to the amygdala and basal forebrain, but their axons target different subregions. Compared to subregions in the prelimbic area (PL) which have more connections with sensorimotor-related regions, the infralimbic area (ILA) has stronger connections with limbic regions. The connection pattern of the mPFC subregions along the anterior–posterior axis showed a corresponding topological pattern with the isocortex and amygdala but an opposite orientation correspondence with the thalamus. Conclusions By using transgenic mice and fMOST imaging, we obtained the subregional preference whole-brain connectomes of IT and pyramidal tract PT neurons in the mPFC four subregions. These results provide a comprehensive resource for directing research into the complex functions of the mPFC by offering anatomical dissections of the different subregions.

ObjectiveTo investigate the effect of calcium channel blockers (CCBs) on tacrolimus blood concentrations in renal transplant recipients with different CYP3A5 genotypes.MethodsThis retrospective cohort study included renal transplant recipients receiving tacrolimus-based immunosuppressive therapy with or without CCBs in combination. Patients were divided into combination and control groups based on whether or not they were combined with CCBs, and then further analyzed according to the type of CCBs (nifedipine/amlodipine/felodipine). Propensity score matching was conducted for the combination and the control groups using SPSS 22.0 software to reduce the impact of confounding factors. The effect of different CCBs on tacrolimus blood concentrations was evaluated, and subgroup analysis was performed according to the patients’ CYP3A5 genotypes to explore the role of CYP3A5 genotypes in drug-drug interactions between tacrolimus and CCBs.ResultsA total of 164 patients combined with CCBs were included in the combination groups. After propensity score matching, 83 patients with nifedipine were matched 1:1 with the control group, 63 patients with felodipine were matched 1:2 with 126 controls, and 18 patients with amlodipine were matched 1:3 with 54 controls. Compared with the controls, the three CCBs increased the dose-adjusted trough concentration (C0/D) levels of tacrolimus by 41.61%–45.57% (P < 0.001). For both CYP3A5 expressers (CYP3A5*1*1 or CYP3A5*1*3) and non-expressers (CYP3A5*3*3), there were significant differences in tacrolimus C0/D between patients using felodipine/nifedipine and those without CCBs (P < 0.001). However, among CYP3A5 non-expressers, C0/D values of tacrolimus were significantly higher in patients combined with amlodipine compared to the controls (P = 0.001), while for CYP3A5 expressers, the difference in tacrolimus C0/D values between patients with amlodipine and without was not statistically significant (P = 0.065).ConclusionCCBs (felodipine/nifedipine/amlodipine) can affect tacrolimus blood concentration levels by inhibiting its metabolism. The CYP3A5 genotype may play a role in the drug interaction between tacrolimus and amlodipine. Therefore, genetic testing for tacrolimus and therapeutic drug monitoring are needed when renal transplant recipients are concurrently using CCBs.

Abstract Ubiquitin-specific protease 3 (USP3) plays an important role in the progression of various tumors. However, the role of USP3 in osteosarcoma (OS) remains poorly understood. The aim of this study was to explore the biological function of USP3 in OS and the underlying molecular mechanism. We found that OS had higher USP3 expression compared with that of normal bone tissue, and high expression of USP3 was associated with poor prognosis in patients with OS. Overexpression of USP3 significantly increased OS cell proliferation, migration, and invasion. Mechanistically, USP3 led to the activation of the PI3K/AKT signaling pathway in OS by binding to EPHA2 and then reducing its protein degradation. Notably, the truncation mutant USP3-F2 (159–520) interacted with EPHA2, and amino acid 203 was found to play an important role in this process. And knockdown of EPHA2 expression reversed the pro-tumour effects of USP3-upregulating. Thus, our study indicates the USP3/EPHA2 axis may be a novel potential target for OS treatment.

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.

Individuals have different rumination patterns after experiencing traumatic events in different cultural backgrounds and situations. This study aimed to explore the experience of Chinese young and middle-aged patients with acute coronary syndrome (ACS) to understand the content and nature of their rumination. Sixteen participants were selected using the purposive sampling method in the First Affiliated Hospital of Soochow University from May 2023 to December 2023. Data were collected using semi-structured interviews and analyzed using Colaizzi’s seven-step phenomenological method. The participants went through two successive stages: non-adaptive rumination and adaptive rumination. During the initial admission phase, all the participants experienced varying degrees of non-adaptive rumination. Non-adaptive rumination included four sub-themes: worry or anxiety of daily activities and medical therapy (37.50%), fear of unpredictable outcomes and death (37.50%), sadness of maladjustment (25.00%), and remorse of carelessness (12.50%). During the period of stable condition and pre-discharge, the participants received health education and gradually all transitioned to adaptive rumination. Adaptive rumination included four sub-themes: tracing of disease processes (100%), enhancement of disease cognition (81.25%), improvement of health awareness (62.50%), and adjustment of lifestyle cognition (100%). In conclusion, although the Chinese young and middle-aged patients with ACS experienced negative emotions after a traumatic cardiac event, they gradually made positive changes, and optimism and information support played important roles in this transition. The results of this study provide a fundamental understanding of rumination experiences in Chinese young and middle-aged patients with ACS and provide new data for healthcare providers when designing intervention programs to enhance post-traumatic growth in these patients.

Abstract One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 μm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.

Abstract The study was design to investigate the functional roles of Wilms tumor 1-associated protein (WTAP), an enzyme catalyzes m6A modification, in the pathogenesis of osteoarthritis (OA) and further elucidate its possible regulatory mechanism. Herein, we discovered that WTAP was outstandingly upregulated in chondrocyte stimulated with Lipopolysaccharide (LPS) and cartilage tissue of patients with OA. Functional studies have demonstrated that WTAP knockdown enhances proliferation ability, suppresses apoptosis, and reduces extracellular matrix (ECM) degradation in an LPS—induced OA chondrocyte injury model and ameliorates cartilage damage in a destabilizing the medial meniscus (DMM)—induced OA mice model. Conversely, overexpression of WTAP contributes to the opposite effects. Mechanistically, our data has demonstrated that m6A modification mediated by WTAP promotes the maturation of pri-miR-92b to miR-92b-5p, thereby enhancing the targeted inhibitory function of miR-92b-5p on TIMP4. Furthermore, we have discovered that WTAP can directly facilitate the degradation of TIMP4 mRNAs in a YTHDF2-dependent manner. In a nutshell, our findings suggested that WTAP knockdown alleviated OA progression by modulating the miR-92b-5p/TIMP4 axis in an m6A-dependent manner. Our study disclosed that WTAP-mediated m6A modification displayed a crucial role in OA development and suggested that targeting WTAP could be a promising preventive and therapeutic target for patients with OA. Video Abstract

Abstract Background Based on their anatomical location, rostral projections of nuclei are classified as ascending circuits, while caudal projections are classified as descending circuits. Upper brainstem neurons participate in complex information processing and specific sub-populations preferentially project to participating ascending or descending circuits. Cholinergic neurons in the upper brainstem have extensive collateralizations in both ascending and descending circuits; however, their single-cell projection patterns remain unclear because of the lack of comprehensive characterization of individual neurons. Results By combining fluorescent micro-optical sectional tomography with sparse labeling, we acquired a high-resolution whole-brain dataset of pontine-tegmental cholinergic neurons (PTCNs) and reconstructed their detailed morphology using semi-automatic reconstruction methods. As the main source of acetylcholine in some subcortical areas, individual PTCNs had abundant axons with lengths up to 60 cm and 5000 terminals and innervated multiple brain regions from the spinal cord to the cortex in both hemispheres. Based on various collaterals in the ascending and descending circuits, individual PTCNs were grouped into four subtypes. The morphology of cholinergic neurons in the pedunculopontine nucleus was more divergent, whereas the laterodorsal tegmental nucleus neurons contained richer axonal branches and dendrites. In the ascending circuits, individual PTCNs innervated the thalamus in three different patterns and projected to the cortex via two separate pathways. Moreover, PTCNs targeting the ventral tegmental area and substantia nigra had abundant collaterals in the pontine reticular nuclei, and these two circuits contributed oppositely to locomotion. Conclusions Our results suggest that individual PTCNs have abundant axons, and most project to various collaterals in the ascending and descending circuits simultaneously. They target regions with multiple patterns, such as the thalamus and cortex. These results provide a detailed organizational characterization of cholinergic neurons to understand the connexional logic of the upper brainstem.

Abstract Objectives Increasing evidence have demonstrated the N6-methyladenosine (m6A) plays critical roles in osteoarthritis (OA) progression, but the role of m6A in OA has not been completely illuminated. Herein, we investigated the function and underlying mechanism of m6A demethylase fat mass and obesity-associated protein (FTO) in OA progression. Materials and methods The FTO expression was detected in mice OA cartilage tissues and lipopolysaccharide (LPS)-stimulated chondrocytes. Gain-of-function assays was used to evaluate the role of FTO in OA cartilage injury in vitro and in vivo. The miRNA-sequencing, RNA-binding protein immunoprecipitation (RIP), luciferase reporter assay, and in vitro pri-miRNA processing assays were conducted to confirm that FTO modulated the pri-miR-3591 process in an m6A-dependent manner and then the binding sites of miR-3591-5p with PRKAA2. Results FTO was outstandingly downregulated in LPS-stimulated chondrocytes and OA cartilage tissues. FTO overexpression enhanced the proliferation, suppressed apoptosis, and decreased degradation of extracellular matrix in LPS-induced chondrocytes, whereas FTO knockdown contributed to the opposite effects. In vivo animal experiments showed that FTO overexpression markedly alleviated OA mice cartilage injury. Mechanically, FTO-mediated m6A demethylation of pri-miR-3591 leaded to a maturation block of miR-3591-5p, which relieved the inhibitory effect of miR-3591-5p on PRKAA2 and then promoted the increase of PRKAA2, thereby alleviating OA cartilage damage. Conclusions Our results attested that FTO alleviated the OA cartilage damage by mediating FTO/miR-3591-5p/PRKAA2 axis, which provided fresh insights into the therapeutic strategies for OA.

The main olfactory bulb is the key element of the olfactory pathway of rodents. To precisely dissect the neural pathway in the main olfactory bulb (MOB), it is necessary to construct the three-dimensional morphologies of the anatomical structures within it with micro-level resolution. However, the construction remains challenging due to the complicated shape of the anatomical structures in the main olfactory bulb and the high resolution of micro-optical images. To address these issues, we propose an interactive volume image segmentation method with micro-level resolution in the horizontal and axial direction. Firstly, we obtain the initial location of the anatomical structures by manual annotation and design a patch-based neural network to learn the complex texture feature of the anatomical structures. Then we randomly sample some patches to predict by the trained network and perform an annotation reconstruction based on intensity calculation to get the final location results of the anatomical structures. Our experiments were conducted using Nissl-stained brain images acquired by the Micro-optical sectioning tomography (MOST) system. Our method achieved a mean dice similarity coefficient (DSC) of 81.8% and obtain the best segmentation performance. At the same time, the experiment shows the three-dimensional morphology reconstruction results of the anatomical structures in the main olfactory bulb are smooth and consistent with their natural shapes, which addresses the possibility of constructing three-dimensional morphologies of the anatomical structures in the whole brain.

A new method, named array fluorescent micro-optical sectioning tomography (array-fMOST), is developed for identifying the three-dimensional information at single-cell resolution from multi-samples.

Vascular segmentation is a crucial task in biomedical image processing, which is significant for analyzing and modeling vascular networks under physiological and pathological states. With advances in fluorescent labeling and mesoscopic optical techniques, it has become possible to map the whole-mouse-brain vascular networks at capillary resolution. However, segmenting vessels from mesoscopic optical images is a challenging task. The problems, such as vascular signal discontinuities, vessel lumens, and background fluorescence signals in mesoscopic optical images, belong to global semantic information during vascular segmentation. Traditional vascular segmentation methods based on convolutional neural networks (CNNs) have been limited by their insufficient receptive fields, making it challenging to capture global semantic information of vessels and resulting in inaccurate segmentation results. Here, we propose SegVesseler, a vascular segmentation method based on Swin Transformer. SegVesseler adopts 3D Swin Transformer blocks to extract global contextual information in 3D images. This approach is able to maintain the connectivity and topology of blood vessels during segmentation. We evaluated the performance of our method on mouse cerebrovascular datasets generated from three different labeling and imaging modalities. The experimental results demonstrate that the segmentation effect of our method is significantly better than traditional CNNs and achieves state-of-the-art performance.

Summary: The neocortex mediates information processing through highly organized circuitry that contains various neuron types. Distinct populations of projection neurons in different cortical regions and layers make specific connections and participate in distinct physiological functions. Herein, with the fluorescence micro-optical sectioning tomography (fMOST) and transgenetic mice that targeted intratelencephalic (IT) and pyramidal tract (PT) neurons at specific layers, we dissected the long-range connectome of pyramidal neurons in six subregions of the sensorimtor cortex. The distribution of the input neurons indicated that IT and PT neurons in the same region received information from similar regions, while the neurons in different subregions received from the preferred neuron populations. Both the input and projection areas of these six subregions showed the transverse and longitudinal correspondence in the cortico-cortical, cortico-thalamic, and cortico-striatal circuits, which indicated that the connections were topologically organized. This study provides a comprehensive resource on the anatomical connections of cortical circuits.

High-definition fluorescent micro-optical sectioning tomography is employed to resolve fine structures of multiple vessel types in the intact liver.

Short-term memory deficits are associated with prefrontal cortex dysfunction in Alzheimer’s disease. Here, the authors assessed extratelencephalic projection (ET) neurons and found reduced ET neural activity in the medial prefrontal cortex (mPFC) and showed ET neurons received fewer cholinergic inputs from the basal forebrain in 5×FAD mice which led to object recognition memory deficits.

Abstract Olfactory dysfunction is an early pre-motor symptom of Parkinson’s disease (PD) but the neural mechanisms underlying this dysfunction remain largely unknown. Aggregation of α-synuclein is observed in the olfactory bulb (OB) during the early stages of PD, indicating a relationship between α-synuclein pathology and hyposmia. Here we investigate whether and how α-synuclein aggregates modulate neural activity in the OB at the single-cell and synaptic levels. We induced α-synuclein aggregation specifically in the OB via overexpression of double-mutant human α-synuclein by an adeno-associated viral (AAV) vector. We found that α-synuclein aggregation in the OB decreased the ability of mice to detect odors and to perceive attractive odors. The spontaneous activity and odor-evoked firing rates of single mitral/tufted cells (M/Ts) were increased by α-synuclein aggregates with the amplitude of odor-evoked high-gamma oscillations increased. Furthermore, the decreased activity in granule cells (GCs) and impaired inhibitory synaptic function were responsible for the observed hyperactivity of M/Ts induced by α-synuclein aggregates. These results provide direct evidences of the role of α-synuclein aggregates on PD-related olfactory dysfunction and reveal the neural circuit mechanisms by which olfaction is modulated by α-synuclein pathology.

Abstract Axonal projection conveys neural information. The divergent and diverse projections of individual neurons imply the complexity of information flow. It is necessary to investigate the relationship between the projection and functional information at the single neuron level for understanding the rules of neural circuit assembly, but a gap remains due to a lack of methods to map the function to whole‐brain projection. Here an approach is developed to bridge two‐photon calcium imaging in vivo with high‐resolution whole‐brain imaging based on sparse labeling with the genetically encoded calcium indicator GCaMP6. Reliable whole‐brain projections are captured by the high‐definition fluorescent micro‐optical sectioning tomography (HD‐fMOST). A cross‐modality cell matching is performed and the functional annotation of whole‐brain projection at the single‐neuron level (FAWPS) is obtained. Applying it to the layer 2/3 (L2/3) neurons in mouse visual cortex, the relationship is investigated between functional preferences and axonal projection features. The functional preference of projection motifs and the correlation between axonal length in MOs and neuronal orientation selectivity, suggest that projection motif‐defined neurons form a functionally specific information flow, and the projection strength in specific targets relates to the information clarity. This pipeline provides a new way to understand the principle of neuronal information transmission.

Visualizing the relationships and interactions among different biological components in the whole brain is crucial to our understanding of brain structures and functions. However, an automatic multicolor whole-brain imaging technique is still lacking. Here, we developed a multicolor wide-field large-volume tomography (multicolor WVT) to simultaneously acquire fluorescent signals in blue, green, and red channels in the whole brain. To facilitate the segmentation of brain regions and anatomical annotation, we used 4′, 6-diamidino-2-phenylindole (DAPI) to provide cytoarchitecture through real-time counterstaining. We optimized the imaging planes and modes of three channels to overcome the axial chromatic aberration of the illumination path and avoid the crosstalk from DAPI to the green channel without the modification of system configuration. We also developed an automatic contour recognition algorithm based on DAPI-staining cytoarchitecture to shorten data acquisition time and reduce data redundancy. To demonstrate the potential of our system in deciphering the relationship of the multiple components of neural circuits, we acquired and quantified the brain-wide distributions of cholinergic neurons and input of ventral Caudoputamen (CP) with the anatomical annotation in the same brain. We further identified the cholinergic type of upstream neurons projecting to CP through the triple-color collocated analysis and quantified its proportions in the two brain-wide distributions. Both accounted for 0.22%, implying CP might be modulated by non-cholinergic neurons. Our method provides a new research tool for studying the different biological components in the same organ and potentially facilitates the understanding of the processing mechanism of neural circuits and other biological activities.

Modulation of neural circuits is essential for flexible sensory perception and decision-making in a changing environment. Cholinergic and GABAergic projections to the olfactory system from the horizontal limb of the diagonal band of Broca (HDB) in the basal forebrain are crucial for odor detection and olfactory learning. Although studies have demonstrated that HDB neurons respond during olfactory learning, how cholinergic and GABAergic neurons differ in their response dynamics and roles in olfactory learning remains unclear. In this study, we examined the response profiles of these two subpopulations of neurons during passive odor exposure and associative olfactory learning. We show that the excitatory responses in both cholinergic and GABAergic neurons tended to habituate during repeated passive odor exposure. However, while these habituated responses were also observed in GABAergic neurons during a go-go task, there was no such habituation in cholinergic neurons. Moreover, the responses to S+ and S− trials diverged in cholinergic neurons once mice learned a go/no-go task. Furthermore, the chemogenetic inactivation of cholinergic neurons in the HDB impaired odor discrimination. Together, these findings suggest that cholinergic neurons in the HDB reflect attention to positive reinforcement and may regulate odor discrimination via top–down inputs to the olfactory system.

The pontomesencephalic tegmentum, comprising the pedunculopontine nucleus and laterodorsal tegmental nucleus, is involved in various functions via complex connections; however, the organizational structure of these circuits in the whole brain is not entirely clear. Here, combining viral tracing with fluorescent micro-optical sectional tomography, we comprehensively investigated the input and output circuits of two cholinergic subregions in a continuous whole-brain dataset. We found that these nuclei receive abundant input with similar spatial distributions but with different quantitative measures and acquire similar neuromodulatory afferents from the ascending reticular activation system. Meanwhile, these cholinergic nuclei project to similar targeting areas throughout multiple brain regions and have different spatial preferences in 3D. Moreover, some cholinergic connections are unidirectional, including projections from the pedunculopontine nucleus and laterodorsal tegmental nucleus to the ventral posterior complex of the thalamus, and have different impacts on locomotion and anxiety. These results reveal the integrated cholinergic connectome of the midbrain, thus improving the present understanding of the organizational structure of the pontine-tegmental cholinergic system from its anatomical structure to its functional modulation.

ABSTRACT In recent years, the chikungunya virus (CHIKV) has continued to spread from local epidemics to nonnative habitats until eventually reaching pandemic status. Nonendemic areas such as China have also emerged as potential epidemic areas of CHIKV. Serological detection of CHIKV is the key to diagnosing and controlling the prevalence of this virus. In this study, we review the progress of the serological detection of the envelope (E) protein in CHIKV, and we provide a novel research assay and ideas for the serological detection of CHIKV. The luciferase immunosorbent assay (LISA) does not require species-specific labeled secondary antibodies for detection, making it universally suitable for tracking samples from various animals or carriers. At present, most research on CHIKV antigen detection technology tends to combine two or more proteins to avoid the decrease in detection ability caused by antigen mutation. Our results indicate that two or more kinds of CHIKV E antigens combined with LISA detection can improve the detection rate of anti-CHIKV immunoglobulin G (IgG) antibodies in CHIKV-infected patient sera and detect antibodies in the early stage of infection accurately and sensitively. After 235 days of infection, the anti-CHIKV IgG antibodies could still be detected in CHIKV-infected patients. All serum samples were tested with a detection rate of 100% after combining various recombinant CHIKV E antigens. Our proposed CHIKV-specific LISA could be a useful tool for serum diagnosis of CHIKV infection and serum epidemic research in areas where CHIKV is endemic, which would help to manage potential epidemics in the future. IMPORTANCE At present, chikungunya virus (CHIKV) is still circulating in some parts of the world, and mutated strains have emerged, making it easier for the virus to spread among humans. With the continuous variation of CHIKV, its antigen variation leads to the decline of detection ability. In addition, the risk of transmission of CHIKV in areas where CHIKV is not endemic, such as China, has increased dramatically, which compels us to enhance the detection capacity of CHIKV and continuously monitor CHIKV antibody levels in the population. Real-time quantitative PCR (RT-PCR) detection technology will not be reliable when the infection time is chronic or in subclinical infection due to decreases in virus concentration, and an antibody detection technology must be adopted. In this study, multiple CHIKV envelope (E) antigens were used to detect anti-CHIKV IgG antibodies in serum for the first time. The new assay is characterized by convenient operation, high detection rate, and high sensitivity and has significance for early warning and monitoring. Moreover, it contributes to the prevention and control of CHIKV.

Abstract Background Corticotropin-releasing hormone (CRH) is an important neuromodulator that is widely distributed in the brain and plays a key role in mediating stress responses and autonomic functions. While the distribution pattern of fluorescently labeled CRH-expressing neurons has been studied in different transgenic mouse lines, a full appreciation of the broad diversity of this population and local neural connectivity can only come from integration of single-cell morphological information as a defining feature. However, the morphologies of single CRH neurons and the local circuits formed by these neurons have not been acquired at brain-wide and dendritic-scale levels. Results We screened the EYFP-expressing CRH-IRES-Cre;Ai32 mouse line to reveal the morphologies of individual CRH neurons throughout the whole mouse brain by using a fluorescence micro-optical sectioning tomography (fMOST) system. Diverse dendritic morphologies and projection fibers of CRH neurons were found in various brain regions. Follow-up reconstructions showed that hypothalamic CRH neurons had the smallest somatic volumes and simplest dendritic branches and that CRH neurons in several brain regions shared a common bipolar morphology. Further investigations of local CRH neurons in the medial prefrontal cortex unveiled somatic depth-dependent morphologies of CRH neurons that exhibited three types of mutual connections: basal dendrites (upper layer) with apical dendrites (layer 3); dendritic-somatic connections (in layer 2/3); and dendritic-dendritic connections (in layer 4). Moreover, hypothalamic CRH neurons were classified into two types according to their somatic locations and characteristics of dendritic varicosities. Rostral-projecting CRH neurons in the anterior parvicellular area had fewer and smaller dendritic varicosities, whereas CRH neurons in the periventricular area had more and larger varicosities that were present within dendrites projecting to the third ventricle. Arborization-dependent dendritic spines of CRH neurons were detected, among which the most sophisticated types were found in the amygdala and the simplest types were found in the hypothalamus. Conclusions By using the CRH-IRES-Cre;Ai32 mouse line and fMOST imaging, we obtained region-specific morphological distributions of CRH neurons at the dendrite level in the whole mouse brain. Taken together, our findings provide comprehensive brain-wide morphological information of stress-related CRH neurons and may facilitate further studies of the CRH neuronal system.

The ever-evolving mesoscopic scale optical imaging systems facilitate the new discoveries in the neuroscience research. They excel at providing a complete view of the long projections of a single neuron across the whole brain. Although the preparation protocols and the optical imaging systems are rapidly evolving, there are still some noise and artifacts interfering downstream data processing and analysis due to the defects in the imaging system or during the sample preparation. A specific denoising procedure is usually developed for one optical imaging system as a post-processing measure. However, the development of the optical imaging systems usually follows in an incremental manner. It would be better to adapt the denoising model to the new optical imaging system than training a denoising model from scratch. In this paper, the proposed learning schema and practice learn a new denoising model for a new optical imaging system based on the existing denoise models and bootstrap a denoising model without the ground-truth denoising labels. We achieve this through a CycleGAN based model and the fact that the optical imaging systems usually produce images both from the signal area and the fixture area. The experiments show that our proposed procedure can provide a comparable denoising performance against other state-of-the-art denoising methods for several optical neuroimaging datasets.

Abstract Background A tourniquet is a device commonly used to control massive hemorrhage during knee replacement surgery. However, the question remains whether the use of tourniquets affects the permeability of the bone cement around the knee prosthesis. Moreover, the long-term effects and stability of the knee prosthesis are still debatable. The aim of this study was to examine whether the use of a tourniquet increases the thickness of the cement mantle and affects the postoperative blood loss and pain during primary total knee arthroplasty (TKA) using meta-analysis. Methods We searched the Cochrane Central Library, MEDLINE, Embase, PubMed, CNKI, and Wang Fang databases for randomized controlled trials (RCTs) on primary TKA, from inception to November 2019. All RCTs in primary TKA with and without a tourniquet were included. The meta-analysis was conducted using RevMan 5.2 software. Results A total of eight RCTs (677 knees) were analyzed. We found no significant difference in the age and sex of the patients. The results showed that the application of tourniquet affects the thickness of the bone cement around the tibial prosthesis (WMD = 0.16, 95%CI = 0.11 to 0.21, p < 0.00001). However, in our study, there was no significant difference in postoperative blood loss between the two groups was observed (WMD = 12.07, 95%CI = − 78.63 to 102.77, p = 0.79). The use of an intraoperative tourniquet can increase the intensity of postoperative pain (WMD = 1.34, 95%, CI = 0.32 to 2.36, p = 0.01). Conclusions Tourniquet application increases the thickness of the bone cement around the prosthesis and may thus increase the stability and durability of the prosthesis after TKA. The application of an intraoperative tourniquet can increase the intensity of postoperative pain.

Abstract Background Neurons are the basic structural unit of the brain, and their morphology is a key determinant of their classification. The morphology of a neuronal circuit is a fundamental component in neuron modeling. Recently, single-neuron morphologies of the whole brain have been used in many studies. The correctness and completeness of semimanually traced neuronal morphology are credible. However, there are some inaccuracies in semimanual tracing results. The distance between consecutive nodes marked by humans is very long, spanning multiple voxels. On the other hand, the nodes are marked around the centerline of the neuronal fiber, not on the centerline. Although these inaccuracies do not seriously affect the projection patterns that these studies focus on, they reduce the accuracy of the traced neuronal skeletons. These small inaccuracies will introduce deviations into subsequent studies that are based on neuronal morphology files. Results We propose a neuronal digital skeleton optimization method to evaluate and make fine adjustments to a digital skeleton after neuron tracing. Provided that the neuronal fiber shape is smooth and continuous, we describe its physical properties according to two shape restrictions. One restriction is designed based on the grayscale image, and the other is designed based on geometry. These two restrictions are designed to finely adjust the digital skeleton points to the neuronal fiber centerline. With this method, we design the three-dimensional shape restriction workflow of neuronal skeleton adjustment computation. The performance of the proposed method has been quantitatively evaluated using synthetic and real neuronal image data. The results show that our method can reduce the difference between the traced neuronal skeleton and the centerline of the neuronal fiber. Furthermore, morphology metrics such as the neuronal fiber length and radius become more precise. Conclusions This method can improve the accuracy of a neuronal digital skeleton based on traced results. The greater the accuracy of the digital skeletons that are acquired, the more precise the neuronal morphologies that are analyzed will be.

The motor system controls muscle movement through lower motor neurons in the spinal cord and brainstem. Lower motor neurons are efferent neurons in the central nervous system (CNS) characterized by axonal projections that reach specific targets in the periphery. Lower motor neuron lesions result in the denervation and dysfunction of peripheral skeletal muscle. Great progress has been made to develop therapeutic strategies to transduce lower motor neurons with genes. However, the widespread distribution of lower motor neurons makes their specific, extensive, and efficient transduction a challenge. In this study, we demonstrated that, compared to the other tested recombinant adeno-associated virus (rAAV) serotypes, rAAV2-retro mediated the most efficient retrograde transduction of lower motor neurons in the spinal cord following intramuscular injection in neonatal mice. A single injection of rAAV2-retro in a single muscle enabled the efficient and extensive transduction of lower motor neurons in the spinal cord and brainstem rather than transducing only the lower motor neurons connected to the injected muscle. rAAV2-retro achieved the extensive transduction of lower motor neurons by the cerebrospinal fluid pathway. Our work suggests that gene delivery via the intramuscular injection of rAAV2-retro represents a promising tool in the development of gene therapy strategies for motor neuron diseases.

The ventral pallidum (VP) integrates reward signals to regulate cognitive, emotional, and motor processes associated with motivational salience. Previous studies have revealed that the VP projects axons to many cortical and subcortical structures. However, descriptions of the neuronal morphologies and projection patterns of the VP neurons at the single neuron level are lacking, thus hindering the understanding of the wiring diagram of the VP. In this study, we used recently developed progress in robust sparse labeling and fluorescence micro-optical sectioning tomography imaging system (fMOST) to label mediodorsal thalamus-projecting neurons in the VP and obtain high-resolution whole-brain imaging data. Based on these data, we reconstructed VP neurons and classified them into three types according to their fiber projection patterns. We systematically compared the axonal density in various downstream centers and analyzed the soma distribution and dendritic morphologies of the various subtypes at the single neuron level. Our study thus provides a detailed characterization of the morphological features of VP neurons, laying a foundation for exploring the neural circuit organization underlying the important behavioral functions of VP.

The brain modulates specific functions in its various regions. Understanding the organization of different cells in the whole brain is crucial for investigating brain functions. Previous studies have focused on several regions and have had difficulty analyzing serial tissue samples. In this study, we introduced a pipeline to acquire anatomical and histological information quickly and efficiently from serial sections. First, we developed a serial brain-slice-staining method to stain serial sections and obtained more than 98.5% of slices with high integrity. Subsequently, using the self-developed analysis software, we registered and quantified the signals of imaged sections to the Allen Mouse Brain Common Coordinate Framework, which is compatible with multimodal images and slant section planes. Finally, we validated the pipeline with immunostaining by analyzing the activity variance in the whole brain during acute stress in aging and young mice. By removing the problems resulting from repeated manual operations, this pipeline is widely applicable to serial brain slices from multiple samples in a rapid and convenient manner, which benefits to facilitate research in life sciences.

The glutamatergic and GABAergic neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) mediated diverse brain functions. However, their whole-brain neural connectivity has not been comprehensively mapped. Here we used the virus tracers to characterize the whole-brain inputs and outputs of glutamatergic and GABAergic neurons in VTA and SNc. We found that these neurons received similar inputs from upstream brain regions, but some quantitative differences were also observed. Neocortex and dorsal striatum provided a greater share of input to VTA glutamatergic neurons. Periaqueductal gray and lateral hypothalamic area preferentially innervated VTA GABAergic neurons. Specifically, superior colliculus provided the largest input to SNc glutamatergic neurons. Compared to input patterns, the output patterns of glutamatergic and GABAergic neurons in the VTA and SNc showed significant preference to different brain regions. Our results laid the anatomical foundation for understanding the functions of cell-type-specific neurons in VTA and SNc.

The dorsal raphe nucleus (DR) and median raphe nucleus (MR) contain populations of glutamatergic and GABAergic neurons that regulate diverse behavioral functions. However, their whole-brain input-output circuits remain incompletely elucidated. We used viral tracing combined with fluorescence micro-optical sectioning tomography to generate a comprehensive whole-brain atlas of inputs and outputs of glutamatergic and GABAergic neurons in the DR and MR. We found that these neurons received inputs from similar upstream brain regions. The glutamatergic and GABAergic neurons in the same raphe nucleus had divergent projection patterns with differences in critical brain regions. Specifically, MR glutamatergic neurons projected to the lateral habenula through multiple pathways. Correlation and cluster analysis revealed that glutamatergic and GABAergic neurons in the same raphe nucleus received heterogeneous inputs and sent different collateral projections. This connectivity atlas further elucidates the anatomical architecture of the raphe nuclei, which could facilitate better understanding of their behavioral functions.

Background: At present, the effects of upper limb movement are generally evaluated from the level of motor performance. The purpose of this study is to evaluate the response of the cerebral cortex to different upper limb movement patterns from the perspective of neurophysiology.Method: Thirty healthy adults (12 females, 18 males, mean age 23.9 ± 0.9 years) took resistance and non-resistance exercises under four trajectories (T1: left and right straight-line movement; T2: front and back straight-line movement; T3: clockwise and anticlockwise drawing circle movement; and T4: clockwise and anticlockwise character ⁕ movement). Each movement included a set of periodic motions composed of a 30-s task and a 30-s rest. Functional near-infrared spectroscopy (fNIRS) was used to measure cerebral blood flow dynamics. Primary somatosensory cortex (S1), supplementary motor area (SMA), pre-motor area (PMA), primary motor cortex (M1), and dorsolateral prefrontal cortex (DLPFC) were chosen as regions of interests (ROIs). Activation maps and symmetric heat maps were applied to assess the response of the cerebral cortex to different motion patterns.Result: The activation of the brain cortex was significantly increased during resistance movement for each participant. Specifically, S1, SMA, PMA, and M1 had higher participation during both non-resistance movement and resistance movement. Compared to non-resistance movement, the resistance movement caused an obvious response in the cerebral cortex. The task state and the resting state were distinguished more obviously in the resistance movement. Four trajectories can be distinguished under non-resistance movement.Conclusion: This study confirmed that the response of the cerebral motor cortex to different motion patterns was different from that of the neurophysiological level. It may provide a reference for the evaluation of resistance training effects in the future.

Whisker detection is crucial to adapt to the environment for some animals, but how the nervous system processes and integrates whisker information is still an open question. It is well-known that two main parallel pathways through Ventral posteromedial thalamic nucleus (VPM) ascend to the barrel cortex, and classical theory suggests that the cross-talk from trigeminal nucleus interpolaris (Sp5i) to principal nucleus (Pr5) between the main parallel pathways contributes to the multi-whisker integration in barrel columns. Moreover, some studies suggest there are other cross-streams between the parallel pathways. To confirm their existence, in this study we used a dual-viral labeling strategy and high-resolution, large-volume light imaging to get the complete morphology of individual VPM neurons and trace their projections. We found some new thalamocortical projections from the ventral lateral part of VPM (VPMvl) to barrel columns. In addition, the retrograde-viral labeling and imaging results showed there were the large trigeminothalamic projections from Sp5i to the dorsomedial section of VPM (VPMdm). Our results reveal new cross-streams between the parallel pathways through VPM, which may involve the execution of multi-whisker integration in barrel columns.

Summary: Cutting tissues into ultrathin slices is highly desired in sectioning-based organ-wide imaging. However, it is difficult to perform tissue cutting at a high speed with excellent quality. Here, we design a precision vibratome based on a paired double parallelogram flexure, which enables a vibrating blade to move strictly along a straight line. Meanwhile, we develop a high-speed cutting method that does not compromise cutting quality, which the vibratome operated at a high frequency mode. The characterized parasitic motion errors of a 180-Hz vibratome were less than 300 nm. It achieved a cutting speed six times that of an 85-Hz vibratome with acceptable quality. The capacity of the vibratome was investigated by organ-wide imaging, and the results revealed that it can be adapted in different tissues, such as the mouse brain and liver. This new vibratome shows great potential in speeding up organ-wide imaging applications especially for large volume biotissues.

Neuron tracing, as the essential step for neural circuit building and brain information flow analyzing, plays an important role in the understanding of brain organization and function. Though lots of methods have been proposed, automatic and accurate neuron tracing from optical images remains challenging. Current methods often had trouble in tracing the complex tree-like distorted structures and broken parts of neurite from a noisy background. To address these issues, we propose a method for accurate neuron tracing using content-aware adaptive voxel scooping on a convolutional neural network (CNN) predicted probability map. First, a 3D residual CNN was applied as preprocessing to predict the object probability and suppress high noise. Then, instead of tracing on the binary image produced by maximum classification, an adaptive voxel scooping method was presented for successive neurite tracing on the probability map, based on the internal content properties (distance, connectivity, and probability continuity along direction) of the neurite. Last, the neuron tree graph was built using the length first criterion. The proposed method was evaluated on the public BigNeuron datasets and fluorescence micro-optical sectioning tomography (fMOST) datasets and outperformed current state-of-art methods on images with neurites that had broken parts and complex structures. The high accuracy tracing proved the potential of the proposed method for neuron tracing on large-scale.

The popularity of mesoscopic whole-brain imaging techniques has increased dramatically, but these techniques generate teravoxel-sized volumetric image data. Visualizing or interacting with these massive data is both necessary and essential in the bioimage analysis pipeline; however, due to their size, researchers have difficulty using typical computers to process them. The existing solutions do not consider applying web visualization and three-dimensional (3D) volume rendering methods simultaneously to reduce the number of data copy operations and provide a better way to visualize 3D structures in bioimage data. Here, we propose webTDat, an open-source, web-based, real-time 3D visualization framework for mesoscopic-scale whole-brain imaging datasets. webTDat uses an advanced rendering visualization method designed with an innovative data storage format and parallel rendering algorithms. webTDat loads the primary information in the image first and then decides whether it needs to load the secondary information in the image. By performing validation on TB-scale whole-brain datasets, webTDat achieves real-time performance during web visualization. The webTDat framework also provides a rich interface for annotation, making it a useful tool for visualizing mesoscopic whole-brain imaging data.

Axonopathy is a pathological feature observed in both Alzheimer’s disease (AD) patients and animal models. However, identifying the temporal and regional progression of axonopathy during AD development remains elusive. Using the fluorescence micro-optical sectioning tomography system, we acquired whole-brain datasets in the early stage of 5xFAD/Thy1-GFP-M mice. We reported that among GFP labeled axons, GFP-positive axonopathy first formed in the lateral septal nucleus, subiculum, and medial mammillary nucleus. The axonopathy further increased in most brain regions during aging. However, most of the axonopathic varicosities disappeared significantly in the medial mammillary nucleus after 8 weeks old. Continuous three-dimensional datasets showed that axonopathy in the medial mammillary nucleus was mainly located on axons from hippocampal GFP-positive neurons. Using the rabies viral tracer in combination with immunohistochemistry, we found that axons in the medial mammillary nucleus from the subiculum were susceptible to lesions that prior to the occurrence of behavioral disorders. In conclusion, we created an early-stage spatiotemporal map of axonopathy in 5xFAD/Thy1-GFP-M mice and identified specific neural circuits which are vulnerable to axon lesions in an AD mouse model. These findings underline the importance of early interventions for AD, and may contribute to the understanding of its progression and its early symptom treatment.

Summary: Resin embedding is widely used to dissect the fine structure of bio-tissue with electron and optical microscopy. However, it is difficult to embed large-volume tissues with resin. Here, we modified the formula of LR-White resin to prevent the sample cracking during polymerization process and applied this method to the intact brains of mouse, ferret, and macaque. Meanwhile, we increased the fluorescence preservation rate for green fluorescent protein (GFP) from 73 ± 4.0% to 126 ± 3.0% and tdTomato from 60 ± 3.3% to 117 ± 2.8%. Combined with the whole-brain imaging system, we acquired the cytoarchitectonic information and the circuit information such as individual axon and boutons which were labeled with multiple fluorescent proteins. This method shows great potential in the study of continuous fine microstructure information in large-volume tissues from different species, which can facilitate the neuroscience research and help the understanding of the structure-function relationship in complex bio-tissues.

In the olfactory bulb, olfactory information is translated into ensemble representations by mitral/tufted cells, and these representations change dynamically in a context-dependent manner. In particular, odor representations in mitral/tufted cells display pattern separation during odor discrimination learning. Although granule cells provide major inhibitory input to mitral/tufted cells and play an important role in pattern separation and olfactory learning, the dynamics of odor responses in granule cells during odor discrimination learning remain largely unknown. Here, we studied odor responses in granule cells of the olfactory bulb using fiber photometry recordings in awake behaving mice. We found that odors evoked reliable, excitatory responses in the granule cell population. Intriguingly, during odor discrimination learning, odor responses in granule cells exhibited improved separation and contained information about odor value. In conclusion, we show that granule cells in the olfactory bulb display learning-related plasticity, suggesting that they may mediate pattern separation in mitral/tufted cells.

Digital reconstruction or tracing of 3D tree-like neuronal structures from optical microscopy images is essential for understanding the functionality of neurons and reveal the connectivity of neuronal networks. Despite the existence of numerous tracing methods, reconstructing a neuron from highly noisy images remains challenging, particularly for neurites with low and inhomogeneous intensities. Conducting deep convolutional neural network (CNN)-based segmentation prior to neuron tracing facilitates an approach to solving this problem via separation of weak neurites from a noisy background. However, large manual annotations are needed in deep learning-based methods, which is labor-intensive and limits the algorithm’s generalization for different datasets. In this study, we present a weakly supervised learning method of a deep CNN for neuron reconstruction without manual annotations. Specifically, we apply a 3D residual CNN as the architecture for discriminative neuronal feature extraction. We construct the initial pseudo-labels (without manual segmentation) of the neuronal images on the basis of an existing automatic tracing method. A weakly supervised learning framework is proposed via iterative training of the CNN model for improved prediction and refining of the pseudo-labels to update training samples. The pseudo-label was iteratively modified via mining and addition of weak neurites from the CNN predicted probability map on the basis of their tubularity and continuity. The proposed method was evaluated on several challenging images from the public BigNeuron and Diadem datasets, to fMOST datasets. Owing to the adaption of 3D deep CNNs and weakly supervised learning, the presented method demonstrates effective detection of weak neurites from noisy images and achieves results similar to those of the CNN model with manual annotations. The tracing performance was significantly improved by the proposed method on both small and large datasets (>100 GB). Moreover, the proposed method proved to be superior to several novel tracing methods on original images. The results obtained on various large-scale datasets demonstrated the generalization and high precision achieved by the proposed method for neuron reconstruction.

Mapping the cytoarchitecture of the whole brain can reveal the organizational logic of neural systems. However, this remains a significant challenge, especially for gyrencephalic brains with a large volume. Here we propose an integrated pipeline for generating a cytoarchitectonic atlas with single-cell resolution of the whole brain. To analyze a large-volume brain, we used a modified en-bloc Nissl staining protocol to achieve uniform staining of large-scale brain specimens from ferret (Mustela putorius furo). By combining whole-brain imaging and big data processing, we established strategies for parsing cytoarchitectural information at a voxel resolution of 0.33 μm × 0.33 μm × 1 μm and terabyte-scale data analysis. Using the cytoarchitectonic datasets for adult ferret brain, we identified giant pyramidal neurons in ferret brains and provide the first report of their morphological diversity, neurochemical phenotype, and distribution patterns in the whole brain in three dimensions. This pipeline will facilitate studies on the organization and development of the mammalian brains, from that of rodents to the gyrencephalic brains of ferret and even primates.

Summary: Ventral hippocampus (vHIP) and medial prefrontal cortex (mPFC) are both critical regions for social behaviors. However, how their interactions affect social behavior is not well understood. By viral tracing, optogenetics, chemogenetics, and fiber photometry, we demonstrated that inhibition of vHIP or direct projections from vHIP to mPFC impaired social memory expression. Via rabies retrograde tracing, we found that all three major GABAergic neurons in mPFC received direct inputs from vHIP. Activation of parvalbumin positive (PV+) neurons in mPFC but not somatostatin positive (SST+) neurons can rescue the social memory impairment caused by vHIP inhibition. Furthermore, fiber photometry results demonstrated that social behaviors preferentially recruited PV+ neurons and inhibition of hippocampal neurons disrupted the activity of PV+ neurons during social interactions. These results revealed a new mechanism of how vHIP and mPFC regulate social behavior in complementarity with the existing neural circuitry mechanism. : Behavioral Neuroscience; Neuroscience; Systems Neuroscience Subject Areas: Behavioral Neuroscience, Neuroscience, Systems Neuroscience

The segmentation of brain region contours in three dimensions is critical for the analysis of different brain structures, and advanced approaches are emerging continuously within the field of neurosciences. With the development of high-resolution micro-optical imaging, whole-brain images can be acquired at the cellular level. However, brain regions in microscopic images are aggregated by discrete neurons with blurry boundaries, the complex and variable features of brain regions make it challenging to accurately segment brain regions. Manual segmentation is a reliable method, but is unrealistic to apply on a large scale. Here, we propose an automated brain region segmentation framework, DeepBrainSeg, which is inspired by the principle of manual segmentation. DeepBrainSeg incorporates three feature levels to learn local and contextual features in different receptive fields through a dual-pathway convolutional neural network (CNN), and to provide global features of localization by image registration and domain-condition constraints. Validated on biological datasets, DeepBrainSeg can not only effectively segment brain-wide regions with high accuracy (Dice ratio > 0.9), but can also be applied to various types of datasets and to datasets with noises. It has the potential to automatically locate information in the brain space on the large scale.

Summary: Understanding the mechanisms of activity-dependent gene transcription underlying adaptive behaviors is challenging at neuronal-subtype resolution. Using cell-type specific molecular analysis in agouti-related peptide (AgRP) neurons, we reveal that the profound hunger-induced transcriptional changes greatly depend on plant homeodomain finger protein 6 (PHF6), a transcriptional repressor enriched in AgRP neurons. Loss of PHF6 in the satiated mice results in a hunger-state-shifting transcriptional profile, while hunger fails to further induce a rapid and robust activity-dependent gene transcription in PHF6-deficient AgRP neurons. We reveal that PHF6 binds to the promoters of a subset of immediate-early genes (IEGs) and that this chromatin binding is dynamically regulated by hunger state. Depletion of PHF6 decreases hunger-driven feeding motivation and makes the mice resistant to body weight gain under repetitive fasting-refeeding conditions. Our work identifies a neuronal subtype-specific transcriptional repressor that modulates transcriptional profiles in different nutritional states and enables adaptive eating behavior. : Gan et al. show that PHF6 is a transcriptional repressor enriched in AgRP neurons and regulates immediate-early gene (IEG) expression. Depletion of PHF6 in AgRP neurons decreases hunger-driven feeding motivation and makes the mice resistant to body weight gain under repetitive fasting/refeeding conditions. Keywords: PHF6, hunger-driven feeding behavior, AgRP neuron, activity-dependent gene transcription, immediate-early genes, IEGs, Börjeson-Forssman-Lehmann syndrome, BFLS

Serotonin neurons of the dorsal and median raphe nuclei (DR, MR) collectively innervate the entire forebrain and midbrain, modulating diverse physiology and behavior. To gain a fundamental understanding of their molecular heterogeneity, we used plate-based single-cell RNA-sequencing to generate a comprehensive dataset comprising eleven transcriptomically distinct serotonin neuron clusters. Systematic in situ hybridization mapped specific clusters to the principal DR, caudal DR, or MR. These transcriptomic clusters differentially express a rich repertoire of neuropeptides, receptors, ion channels, and transcription factors. We generated novel intersectional viral-genetic tools to access specific subpopulations. Whole-brain axonal projection mapping revealed that DR serotonin neurons co-expressing vesicular glutamate transporter-3 preferentially innervate the cortex, whereas those co-expressing thyrotropin-releasing hormone innervate subcortical regions in particular the hypothalamus. Reconstruction of 50 individual DR serotonin neurons revealed diverse and segregated axonal projection patterns at the single-cell level. Together, these results provide a molecular foundation of the heterogenous serotonin neuronal phenotypes.

Abstract Corticofugal projection neurons are key components in connecting the neocortex and the subcortical regions. In the barrel field, these neurons have various projection targets and play crucial roles in the rodent whisker sensorimotor system. However, the projection features of corticofugal projection neurons at the single-axon level are far from comprehensive elucidation. Based on a brain-wide positioning system with high-resolution imaging for Thy1-GFP M-line mice brains, we reconstructed and analyzed more than one hundred corticofugal projection neurons in both layer V and VI of barrel cortex. The dual-color imaging made it possible to locate the neurons’ somata, trace their corresponding dendrites and axons and then distinguish the neurons as L5 type I/II or L6 type. The corticofugal projection pattern showed significant diversity across individual neurons. Usually, the L5 type I neurons have greater multi-region projection potential. The thalamus and the midbrain are the most frequent projection targets among the investigated multidirectional projection neurons, and the hypothalamus is particularly unique in that it only appears in multidirectional projection situations. Statistically, the average branch length of apical dendrites in multi-region projection groups is larger than that of single-region projection groups. This study demonstrated a single-axon-level analysis for barrel corticofugal projection neurons, which could provide a micro-anatomical basis for interpreting whisker sensorimotor circuit function.

The excitatory neurons in the visual cortex are of great significance for us in understanding brain functions. However, the diverse neuron types and their morphological properties have not been fully deciphered. In this paper, we applied the brain-wide positioning system (BPS) to image the entire brain of two Thy1-eYFP H-line male mice at 0.2 μm × 0.2 μm × 1 μm voxel resolution. A total of 103 neurons were reconstructed in layers 5 and 6 of the visual cortex with single-axon-level resolution. Based on the complete topology of neurons and the inherent positioning function of the imaging method, we classified the observed neurons into six types according to their apical dendrites and somata location: star pyramidal cells in layer 5 (L5-sp), slender-tufted pyramidal cells in layer 5 (L5-st), tufted pyramidal cells in layer 5 (L5-tt), spiny stellate-like cells in layer 6 (L6-ss), star pyramidal cells in layer 6 (L6-sp), and slender-tufted pyramidal cells in layer 6 (L6-st). By examining the axonal projection patterns of individual neurons, they can be categorized into three modes: ipsilateral circuit connection neurons, callosal projection neurons and corticofugal projection neurons. Correlating the two types of classifications, we have found that there are at least two projection modes comprised in the former defined neuron types except for L5-tt. On the other hand, each projection mode may consist of four dendritic types defined in this study. The axon projection mode only partially correlates with the apical dendrite feature. This work has demonstrated a paradigm for resolving the visual cortex through single-neuron-level quantification and has shown potential to be extended to reveal the connectome of other defined sensory and motor systems.

Long-range neuronal circuits play an important role in motor and sensory information processing. Determining direct synaptic inputs of excited and inhibited neurons is important for understanding the circuit mechanisms involved in regulating movement. Here, we used the monosynaptic rabies tracing technique, combined with fluorescent micro-optical sectional tomography, to characterize the brain-wide input to the motor cortex (MC). The whole brain dataset showed that the main excited and inhibited neurons in the MC received inputs from similar brain regions with a quantitative difference. With 3D reconstruction we found that the distribution of input neurons, that target the primary and secondary MC, had different patterns. In the cortex, the neurons projecting to the primary MC mainly distributed in the lateral and anterior portion, while those to the secondary MC distributed in the medial and posterior portion. The input neurons in the subcortical areas also showed the topographic shift model, as in the thalamus, the neurons distributed as outer and inner shells while the neurons in the claustrum and amygdala were in the ventral and dorsal part, respectively. These results lay the anatomical foundation to understanding the organized pattern of motor circuits and the functional differences between the primary and secondary MC.

Reconstruction of neuronal morphology from images involves mainly the extraction of neuronal skeleton points. It is an indispensable step in the quantitative analysis of neurons. Due to the complex morphology of neurons, many widely used tracing methods have difficulties in accurately acquiring skeleton points near branch points or in structures with tortuosity. Here, we propose two models to solve these problems. One is based on an L1-norm minimization model, which can better identify tortuous structure, namely, a local structure with large curvature skeleton points; the other detects an optimized branch point by considering the combination patterns of all neurites that link to this point. We combined these two models to achieve optimized skeleton detection for a neuron. We validate our models in various datasets including MOST and BigNeuron. In addition, we demonstrate that our method can optimize the traced skeletons from large-scale images. These characteristics of our approach indicate that it can reduce manual editing of traced skeletons and help to accelerate the accurate reconstruction of neuronal morphology.

Recent technical advancements in neural engineering allow for precise recording and control of neural circuits simultaneously, opening up new opportunities for closed-loop neural control. In this work, a rapid spike sorting system was developed based on template matching to rapidly calculate instantaneous firing rates for each neuron in a multi-unit extracellular recording setting. Cluster templates were first generated by a desktop computer using a non-parameter spike sorting algorithm (Super-paramagnetic clustering) and then transferred to a field-programmable gate array digital circuit for rapid sorting through template matching. Two different matching techniques-Euclidean distance (ED) and correlational matching (CM)-were compared for the accuracy of sorting and the performance of calculating firing rates. The performance of the system was first verified using publicly available artificial data and was further confirmed with pre-recorded neural spikes from an anesthetized Mongolian gerbil. Real-time recording and sorting from an awake mouse were also conducted to confirm the system performance in a typical behavioral neuroscience experimental setting. Experimental results indicated that high sorting accuracies were achieved for both template-matching methods, but CM can better handle spikes with non-Gaussian spike distributions, making it more robust for in vivo recording. The technique was also compared to several other off-line spike sorting algorithms and the results indicated that the sorting accuracy is comparable but sorting time is significantly shorter than these other techniques. A low sorting latency of under 2 ms and a maximum spike sorting rate of 941 spikes/second have been achieved with our hybrid hardware/software system. The low sorting latency and fast sorting rate allow future system developments of neural circuit modulation through analyzing neural activities in real-time.