The posterior hippocampus (pHp) plays a major role in the processing and storage of drug-related cues and is linked to striatal-limbic brain circuits involved with craving and drug salience. We have recently reported that increased basal regional cerebral blood flow (rCBF) in a pHp loci, as measured by pseudo-continuous arterial spin labeling magnetic resonance imaging, predicted days to cocaine relapse following residential treatment. In this secondary analysis, we explored whether rCBF in this same pHp region would successfully predict 30-day point prevalence abstinence 60 days following residential treatment in an independent group of previously studied participants with cocaine dependence. rCBF was assessed with single photon emission computerized tomography during a saline infusion in 21 cocaine dependence and 22 healthy control participants. pHp rCBF was significantly higher in those endorsing substance use (n = 10) relative to both abstinent (n = 11) (p < 0.001) and control (p < 0.05) participants. There were no significant differences in measured demographic or clinical variables between the actively using and non-using participants. This replicative finding suggests that heightened pHp activation is a significant predictor of substance use in cocaine-dependent individuals, possibly reflecting a neural susceptibility to continued drug cues.

The connections between the claustrum and the cortex in mouse are systematically investigated with adeno-associated virus (AAV), an anterograde viral tracer. We first define the boundary and the three-dimensional structure of the claustrum based on a variety of molecular and anatomical data. From AAV injections into 42 neocortical and allocortical areas, we conclude that most cortical areas send bilateral projections to the claustrum, the majority being denser on the ipsilateral side. This includes prelimbic, infralimbic, medial, ventrolateral and lateral orbital, ventral retrosplenial, dorsal and posterior agranular insular, visceral, temporal association, dorsal and ventral auditory, ectorhinal, perirhinal, lateral entorhinal, and anteromedial, posteromedial, lateroposterior, laterointermediate, and postrhinal visual areas. In contrast, the cingulate and the secondary motor areas send denser projections to the contralateral claustrum than to the ipsilateral one. The gustatory, primary auditory, primary visual, rostrolateral visual, and medial entorhinal cortices send projections only to the ipsilateral claustrum. Primary motor, primary somatosensory and subicular areas barely send projections to either ipsi- or contralateral claustrum. Corticoclaustral projections are organized in a rough topographic manner, with variable projection strengths. We find that the claustrum, in turn, sends widespread projections preferentially to ipsilateral cortical areas with different projection strengths and laminar distribution patterns and to certain contralateral cortical areas. Our quantitative results show that the claustrum has strong reciprocal and bilateral connections with prefrontal and cingulate areas as well as strong reciprocal connections with the ipsilateral temporal and retrohippocampal areas, suggesting that it may play a crucial role in a variety of cognitive processes. J. Comp. Neurol. 525:1317-1346, 2017. © 2016 Wiley Periodicals, Inc.

Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole-brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high-resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), and 1,356 large-format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto- and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127-3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

The Neurodata Without Borders (NWB) initiative promotes data standardization in neuroscience to increase research reproducibility and opportunities. In the first NWB pilot project, neurophysiologists and software developers produced a common data format for recordings and metadata of cellular electrophysiology and optical imaging experiments. The format specification, application programming interfaces, and sample datasets have been released.

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD) patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD-associated communities might arise from opportunist growth of bacteria that can circumvent the host's nutrient-based mechanism for bacterial partner selection.

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain.

Generating a comprehensive description of cortical networks requires a large-scale, systematic approach. To that end, we have begun a pipeline project using multipatch electrophysiology, supplemented with two-photon optogenetics, to characterize connectivity and synaptic signaling between classes of neurons in adult mouse primary visual cortex (V1) and human cortex. We focus on producing results detailed enough for the generation of computational models and enabling comparison with future studies. Here, we report our examination of intralaminar connectivity within each of several classes of excitatory neurons. We find that connections are sparse but present among all excitatory cell classes and layers we sampled, and that most mouse synapses exhibited short-term depression with similar dynamics. Synaptic signaling between a subset of layer 2/3 neurons, however, exhibited facilitation. These results contribute to a body of evidence describing recurrent excitatory connectivity as a conserved feature of cortical microcircuits.

This protocol is a practical guide to the N-methyl-D-glucamine (NMDG) protective recovery method of brain slice preparation. Numerous recent studies have validated the utility of this method for enhancing neuronal preservation and overall brain slice viability. The implementation of this technique by early adopters has facilitated detailed investigations into brain function using diverse experimental applications and spanning a wide range of animal ages, brain regions, and cell types. Steps are outlined for carrying out the protective recovery brain slice technique using an optimized NMDG artificial cerebrospinal fluid (aCSF) media formulation and enhanced procedure to reliably obtain healthy brain slices for patch clamp electrophysiology. With this updated approach, a substantial improvement is observed in the speed and reliability of gigaohm seal formation during targeted patch clamp recording experiments while maintaining excellent neuronal preservation, thereby facilitating challenging experimental applications. Representative results are provided from multi-neuron patch clamp recording experiments to assay synaptic connectivity in neocortical brain slices prepared from young adult transgenic mice and mature adult human neurosurgical specimens. Furthermore, the optimized NMDG protective recovery method of brain slicing is compatible with both juvenile and adult animals, thus resolving a limitation of the original methodology. In summary, a single media formulation and brain slicing procedure can be implemented across various species and ages to achieve excellent viability and tissue preservation.

There is a significant interest in the neuroscience community in the development of large-scale network models that would integrate diverse sets of experimental data to help elucidate mechanisms underlying neuronal activity and computations. Although powerful numerical simulators (e.g., NEURON, NEST) exist, data-driven large-scale modeling remains challenging due to difficulties involved in setting up and running network simulations. We developed a high-level application programming interface (API) in Python that facilitates building large-scale biophysically detailed networks and simulating them with NEURON on parallel computer architecture. This tool, termed "BioNet", is designed to support a modular workflow whereby the description of a constructed model is saved as files that could be subsequently loaded for further refinement and/or simulation. The API supports both NEURON's built-in as well as user-defined models of cells and synapses. It is capable of simulating a variety of observables directly supported by NEURON (e.g., spikes, membrane voltage, intracellular [Ca++]), as well as plugging in modules for computing additional observables (e.g. extracellular potential). The high-level API platform obviates the time-consuming development of custom code for implementing individual models, and enables easy model sharing via standardized files. This tool will help refocus neuroscientists on addressing outstanding scientific questions rather than developing narrow-purpose modeling code.

To investigate whether single nucleotide polymorphisms (SNPs) in the vascular endothelial growth factor (VEGF) gene are associated with diabetic retinopathy (DR) in a cohort of Chinese patients with type 2 diabetes mellitus (T2DM).

The Cre/lox system is widely used in mice to achieve cell-type-specific gene expression. However, a strong and universally responding system to express genes under Cre control is still lacking. We have generated a set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra. The robust native fluorescence of these reporters enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo. Using these reporters and a high-throughput in situ hybridization platform, we are systematically profiling Cre-directed gene expression throughout the mouse brain in several Cre-driver lines, including new Cre lines targeting different cell types in the cortex. Our expression data are displayed in a public online database to help researchers assess the utility of various Cre-driver lines for cell-type-specific genetic manipulation.

Neurones are noisy elements. Noise arises from both intrinsic and extrinsic sources, and manifests itself as fluctuations in the membrane potential. These fluctuations limit the accuracy of a neurone's output but have also been suggested to play a computational role. We present a detailed study of the amplitude and spectrum of voltage noise recorded at the soma of layer IV-V pyramidal neurones in slices taken from rat neocortex. The dependence of the noise on holding potential, synaptic activity and Na+ conductance is systematically analysed. We demonstrate that voltage noise increases non-linearly as the cell depolarizes (from a standard deviation (s.d.) of 0.19 mV at -75 mV to an s.d. of 0.54 mV at -55 mV). The increase in voltage noise is accompanied by an increase in the cell impedance, due to voltage dependence of Na+ conductance. The impedance increase accounts for the majority (70%) of the voltage noise increase. The increase in voltage noise and impedance is restricted to the low-frequency range (0.2-2 Hz). At the high frequency range (5-100 Hz) the voltage noise is dominated by synaptic activity. In our slice preparation, synaptic noise has little effect on the cell impedance. A minimal model reproduces qualitatively these data. Our results imply that ion channel noise contributes significantly to membrane voltage fluctuations at the subthreshold voltage range, and that Na+ conductance plays a key role in determining the amplitude of this noise by acting as a voltage-dependent amplifier of low-frequency transients.

Betulinic acid (BA) is a complex lupane triterpenoid with unique antineoplastic activity. However, its antiproliferative activity is far from satisfaction. In order to improve its anticancer efficacy, betulinic acid was conjugated with a nitric oxide (NO)-releasing moiety to get a novel hybrid, BA-78.

The Allen Institute for Brain Science is a non-profit private institution dedicated to basic brain science with an internal organization more commonly found in large physics projects-large teams generating complete, accurate and permanent resources for the mouse and human brain. It can also be viewed as an experiment in the sociology of neuroscience. We here describe some of the singular differences to more academic, PI-focused institutions.

The neocortex contains a multitude of cell types that are segregated into layers and functionally distinct areas. To investigate the diversity of cell types across the mouse neocortex, here we analysed 23,822 cells from two areas at distant poles of the mouse neocortex: the primary visual cortex and the anterior lateral motor cortex. We define 133 transcriptomic cell types by deep, single-cell RNA sequencing. Nearly all types of GABA (γ-aminobutyric acid)-containing neurons are shared across both areas, whereas most types of glutamatergic neurons were found in one of the two areas. By combining single-cell RNA sequencing and retrograde labelling, we match transcriptomic types of glutamatergic neurons to their long-range projection specificity. Our study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct areas of the adult mouse cortex.

The relationship between clinical prognosis and transforming growth factor-β (TGF-β) receptor mutations in Chinese pediatric patients with idiopathic/hereditary pulmonary arterial hypertension (IPAH/HPAH) remains unclear. We retrospectively studied the clinical characteristics and outcomes of pediatric patients with IPAH/HPAH who visited our Hospital from September 2008 to December 2020. One hundred and five pediatric patients with IPAH/HPAH were included, 46 of whom carried TGF-β receptor mutations with a mean age at diagnosis of 82.8 ± 52.7 months, and 67 of them underwent right cardiac catheterization examinations and acute vasodilator testing. The result showed that mutation carriers demonstrated higher pulmonary vascular resistance (p = 0.012), higher right atrial pressure (p = 0.026), and lower cardiac index (p = 0.003). The 1-, 2-, and 3-year survival rates of mutation carriers were 79.4%, 61.5% and 55.6%, respectively, compared with 96.6%, 91.1%, and 85.4% for nonmutation carriers (p = 0.0001). The prognosis of mutation carriers was significantly worse than that of nonmutation carriers. TGF-β receptor gene mutation is an independent risk factor for death (p = 0.049, odd raito = 3.809, 95% confidence interval 1.006-14.429). In conclusion, TGF-β receptor mutation is an important genetic factor for the onset of IPAH/PAH in Chinese pediatric patients. Those who carrying TGF-β receptor mutations have a poor clinical prognosis. Therefore, TGF-β receptor gene screening for pediatric patients with PAH and more aggressive treatment for mutation carriers are recommended.

Cardiovascular disease is a leading cause of morbidity and mortality in individuals with Down syndrome. Congenital heart disease is the most common cardiovascular condition in this group, present in up to 50% of people with Down syndrome and contributing to poor outcomes. Additional factors contributing to cardiovascular outcomes include pulmonary hypertension; coexistent pulmonary, endocrine, and metabolic diseases; and risk factors for atherosclerotic disease. Moreover, disparities in the cardiovascular care of people with Down syndrome compared with the general population, which vary across different geographies and health care systems, further contribute to cardiovascular mortality; this issue is often overlooked by the wider medical community. This review focuses on the diagnosis, prevalence, and management of cardiovascular disease encountered in people with Down syndrome and summarizes available evidence in 10 key areas relating to Down syndrome and cardiac disease, from prenatal diagnosis to disparities in care in areas of differing resource availability. All specialists and nonspecialist clinicians providing care for people with Down syndrome should be aware of best clinical practice in all aspects of care of this distinct population.

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

Recent studies suggest that there is a potential connection between obstructive sleep apnea (OSA) and osteoporosis through dysregulation of bone metabolism. Orexin-A, a neuroprotective peptide secreted by the hypothalamus, is at a lower level in the plasma of OSA patients, which regulates appetite, energy expenditure and sleep-wake states. However, the protective effect of orexin-A on bone metabolism in OSA is unclear.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits.