The mouse cortico-basal ganglia-thalamic network.

The cortico-basal ganglia-thalamo-cortical loop is one of the fundamental network motifs in the brain. Revealing its structural and functional organization is critical to understanding cognition, sensorimotor behaviour, and the natural history of many neurological and neuropsychiatric disorders. Classically, this network is conceptualized to contain three information channels: motor, limbic and associative1-4. Yet this three-channel view cannot explain the myriad functions of the basal ganglia. We previously subdivided the dorsal striatum into 29 functional domains on the basis of the topography of inputs from the entire cortex5. Here we map the multi-synaptic output pathways of these striatal domains through the globus pallidus external part (GPe), substantia nigra reticular part (SNr), thalamic nuclei and cortex. Accordingly, we identify 14 SNr and 36 GPe domains and a direct cortico-SNr projection. The striatonigral direct pathway displays a greater convergence of striatal inputs than the more parallel striatopallidal indirect pathway, although direct and indirect pathways originating from the same striatal domain ultimately converge onto the same postsynaptic SNr neurons. Following the SNr outputs, we delineate six domains in the parafascicular and ventromedial thalamic nuclei. Subsequently, we identify six parallel cortico-basal ganglia-thalamic subnetworks that sequentially transduce specific subsets of cortical information through every elemental node of the cortico-basal ganglia-thalamic loop. Thalamic domains relay this output back to the originating corticostriatal neurons of each subnetwork in a bona fide closed loop.

Cellular anatomy of the mouse primary motor cortex.

An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input-output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture.

Organization of the inputs and outputs of the mouse superior colliculus.

The superior colliculus (SC) receives diverse and robust cortical inputs to drive a range of cognitive and sensorimotor behaviors. However, it remains unclear how descending cortical input arising from higher-order associative areas coordinate with SC sensorimotor networks to influence its outputs. Here, we construct a comprehensive map of all cortico-tectal projections and identify four collicular zones with differential cortical inputs: medial (SC.m), centromedial (SC.cm), centrolateral (SC.cl) and lateral (SC.l). Further, we delineate the distinctive brain-wide input/output organization of each collicular zone, assemble multiple parallel cortico-tecto-thalamic subnetworks, and identify the somatotopic map in the SC that displays distinguishable spatial properties from the somatotopic maps in the neocortex and basal ganglia. Finally, we characterize interactions between those cortico-tecto-thalamic and cortico-basal ganglia-thalamic subnetworks. This study provides a structural basis for understanding how SC is involved in integrating different sensory modalities, translating sensory information to motor command, and coordinating different actions in goal-directed behaviors.

Connectivity characterization of the mouse basolateral amygdalar complex.

The basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

An open access mouse brain flatmap and upgraded rat and human brain flatmaps based on current reference atlases.

Here we present a flatmap of the mouse central nervous system (CNS) (brain) and substantially enhanced flatmaps of the rat and human brain. Also included are enhanced representations of nervous system white matter tracts, ganglia, and nerves, and an enhanced series of 10 flatmaps showing different stages of rat brain development. The adult mouse and rat brain flatmaps provide layered diagrammatic representation of CNS divisions, according to their arrangement in corresponding reference atlases: Brain Maps 4.0 (BM4, rat) (Swanson, The Journal of Comparative Neurology, 2018, 526, 935-943), and the first version of the Allen Reference Atlas (mouse) (Dong, The Allen reference atlas, (book + CD-ROM): A digital color brain atlas of the C57BL/6J male mouse, 2007). To facilitate comparative analysis, both flatmaps are scaled equally, and the divisional hierarchy of gray matter follows a topographic arrangement used in BM4. Also included with the mouse and rat brain flatmaps are cerebral cortex atlas level contours based on the reference atlases, and direct graphical and tabular comparison of regional parcellation. To encourage use of the brain flatmaps, they were designed and organized, with supporting reference tables, for ease-of-use and to be amenable to computational applications. We demonstrate how they can be adapted to represent novel parcellations resulting from experimental data, and we provide a proof-of-concept for how they could form the basis of a web-based graphical data viewer and analysis platform. The mouse, rat, and human brain flatmap vector graphics files (Adobe Reader/Acrobat viewable and Adobe Illustrator editable) and supporting tables are provided open access; they constitute a broadly applicable neuroscience toolbox resource for researchers seeking to map and perform comparative analysis of brain data.

Brainwide Genetic Sparse Cell Labeling to Illuminate the Morphology of Neurons and Glia with Cre-Dependent MORF Mice.

Cajal recognized that the elaborate shape of neurons is fundamental to their function in the brain. However, there are no simple and generalizable genetic methods to study neuronal or glial cell morphology in the mammalian brain. Here, we describe four mouse lines conferring Cre-dependent sparse cell labeling based on mononucleotide repeat frameshift (MORF) as a stochastic translational switch. Notably, the optimized MORF3 mice, with a membrane-bound multivalent immunoreporter, confer Cre-dependent sparse and bright labeling of thousands of neurons, astrocytes, or microglia in each brain, revealing their intricate morphologies. MORF3 mice are compatible with imaging in tissue-cleared thick brain sections and with immuno-EM. An analysis of 151 MORF3-labeled developing retinal horizontal cells reveals novel morphological cell clusters and axonal maturation patterns. Our study demonstrates a conceptually novel, simple, generalizable, and scalable mouse genetic solution to sparsely label and illuminate the morphology of genetically defined neurons and glia in the mammalian brain.

Precise segmentation of densely interweaving neuron clusters using G-Cut.

Characterizing the precise three-dimensional morphology and anatomical context of neurons is crucial for neuronal cell type classification and circuitry mapping. Recent advances in tissue clearing techniques and microscopy make it possible to obtain image stacks of intact, interweaving neuron clusters in brain tissues. As most current 3D neuronal morphology reconstruction methods are only applicable to single neurons, it remains challenging to reconstruct these clusters digitally. To advance the state of the art beyond these challenges, we propose a fast and robust method named G-Cut that is able to automatically segment individual neurons from an interweaving neuron cluster. Across various densely interconnected neuron clusters, G-Cut achieves significantly higher accuracies than other state-of-the-art algorithms. G-Cut is intended as a robust component in a high throughput informatics pipeline for large-scale brain mapping projects.

Integration of gene expression and brain-wide connectivity reveals the multiscale organization of mouse hippocampal networks.

Understanding the organization of the hippocampus is fundamental to understanding brain function related to learning, memory, emotions, and diseases such as Alzheimer's disease. Physiological studies in humans and rodents have suggested that there is both structural and functional heterogeneity along the longitudinal axis of the hippocampus. However, the recent discovery of discrete gene expression domains in the mouse hippocampus has provided the opportunity to re-evaluate hippocampal connectivity. To integrate mouse hippocampal gene expression and connectivity, we mapped the distribution of distinct gene expression patterns in mouse hippocampus and subiculum to create the Hippocampus Gene Expression Atlas (HGEA). Notably, previously unknown subiculum gene expression patterns revealed a hidden laminar organization. Guided by the HGEA, we constructed the most detailed hippocampal connectome available using Mouse Connectome Project ( http://www.mouseconnectome.org ) tract tracing data. Our results define the hippocampus' multiscale network organization and elucidate each subnetwork's unique brain-wide connectivity patterns.

The mouse cortico-striatal projectome.

Different cortical areas are organized into distinct intracortical subnetworks. The manner in which descending pathways from the entire cortex interact subcortically as a network remains unclear. We developed an open-access comprehensive mesoscale mouse cortico-striatal projectome: a detailed connectivity projection map from the entire cerebral cortex to the dorsal striatum or caudoputamen (CP) in rodents. On the basis of these projections, we used new computational neuroanatomical tools to identify 29 distinct functional striatal domains. Furthermore, we characterized different cortico-striatal networks and how they reconfigure across the rostral-caudal extent of the CP. The workflow was also applied to select cortico-striatal connections in two different mouse models of disconnection syndromes to demonstrate its utility for characterizing circuitry-specific connectopathies. Together, our results provide the structural basis for studying the functional diversity of the dorsal striatum and disruptions of cortico-basal ganglia networks across a broad range of disorders.

High-resolution characterization of a PACAP-EGFP transgenic mouse model for mapping PACAP-expressing neurons.

Pituitary adenylate cyclase-activating polypeptide (PACAP, gene name Adcyap1) regulates a wide variety of neurological and physiological functions, including metabolism and cognition, and plays roles in of multiple forms of stress. Because of its preferential expression in nerve fibers, it has often been difficult to trace and identify the endogenous sources of the peptide in specific populations of neurons. Here, we introduce a transgenic mouse line that harbors in its genome a bacterial artificial chromosome containing an enhanced green fluorescent protein (EGFP) expression cassette inserted upstream of the PACAP ATG translation initiation codon. Analysis of expression in brain sections of these mice using a GFP antibody reveals EGFP expression in distinct neuronal perikarya and dendritic arbors in several major brain regions previously reported to express PACAP from using a variety of approaches, including radioimmunoassay, in situ hybridization, and immunohistochemistry with and without colchicine. EGFP expression in neuronal perikarya was modulated in a manner similar to PACAP gene expression in motor neurons after peripheral axotomy in the ipsilateral facial motor nucleus in the brainstem, providing an example in which the transgene undergoes proper regulation in vivo. These mice and the high-resolution map obtained are expected to be useful in understanding the anatomical patterns of PACAP expression and its plasticity in the mouse. J. Comp. Neurol. 524:3827-3848, 2016. © 2016 Wiley Periodicals, Inc.

Rapid-onset hypoglycemia suppresses Fos expression in discrete parts of the ventromedial nucleus of the hypothalamus.

The consensus view of the ventromedial nucleus of the hypothalamus (VMH) is that it is a key node in the rodent brain network controlling sympathoadrenal counterregulatory responses to hypoglycemia. To identify the location of hypoglycemia-responsive neurons in the VMH, we performed a high spatial resolution Fos analysis in the VMH of rats made hypoglycemic with intraperitoneal injections of insulin. We examined Fos expression in the four constituent parts of VMH throughout its rostrocaudal extent and determined their relationship to blood glucose concentrations. Hypoglycemia significantly decreased Fos expression only in the dorsomedial and central parts of the VMH, but not its anterior or ventrolateral parts. Moreover, the number of Fos-expressing neurons was significantly and positively correlated in the two responsive regions with terminal blood glucose concentrations. We also measured Fos responses in the paraventricular nucleus of the hypothalamus (PVH) and in several levels of the periaqueductal gray (PAG), which receives strong projections from the VMH. We found the expected and highly significant increase in Fos in the neuroendocrine PVH, which was negatively correlated to terminal blood glucose concentrations, but no significant differences were seen in any part of the PAG. Our results show that there are distinct populations of VMH neurons whose Fos expression is suppressed by hypoglycemia, and their numbers correlate with blood glucose. These findings support a clear division of glycemic control functions within the different parts of the VMH.

Neural networks of the mouse neocortex.

Numerous studies have examined the neuronal inputs and outputs of many areas within the mammalian cerebral cortex, but how these areas are organized into neural networks that communicate across the entire cortex is unclear. Over 600 labeled neuronal pathways acquired from tracer injections placed across the entire mouse neocortex enabled us to generate a cortical connectivity atlas. A total of 240 intracortical connections were manually reconstructed within a common neuroanatomic framework, forming a cortico-cortical connectivity map that facilitates comparison of connections from different cortical targets. Connectivity matrices were generated to provide an overview of all intracortical connections and subnetwork clusterings. The connectivity matrices and cortical map revealed that the entire cortex is organized into four somatic sensorimotor, two medial, and two lateral subnetworks that display unique topologies and can interact through select cortical areas. Together, these data provide a resource that can be used to further investigate cortical networks and their corresponding functions.

Dissociating the conditioning and the anorectic effects of estradiol in female rats.

The present series of experiments challenges the ability of the hormone estradiol to act as an unconditioned stimulus in the conditioned taste avoidance (CTA) learning paradigm. We hypothesize that reductions in sucrose consumption observed after pairing it with estradiol are not indicative of associative learning, but due to the unconditioned expression of estradiol's anorectic effects during the time of CTA assessment. Three experiments in which a sucrose solution was paired with estradiol were conducted to test this hypothesis. Experiment 1 demonstrated that female rats expressed a reduction in post-pairing sucrose consumption even though the anorectic effects of estradiol had subsided. Experiment 2 showed that although a low dose of estradiol produced anorexia, it did not elicit post-pairing reductions in sucrose consumption. Experiment 3 revealed that contingent pairing was a requirement for post-pairing reduction in sucrose consumption even when testing was done at a time when anorexia is expressed. These findings demonstrate the dissociability of the conditioning and anorectic effects of estradiol, providing evidence against the hypothesis. The results are discussed in terms of independent neural mechanisms underlying the disparate behaviors.