Leonard Kuan

A mesoscale connectome of the mouse brain

Comprehensive knowledge of the brain’s wiring diagram is fundamental for understanding how the nervous system processes information at both local and global scales. However, with the singular exception of the C. elegans microscale connectome, there are no complete connectivity data sets in other species. Here we report a brain-wide, cellular-level, mesoscale connectome for the mouse. The Allen Mouse Brain Connectivity Atlas uses enhanced green fluorescent protein (EGFP)-expressing adeno-associated viral vectors to trace axonal projections from defined regions and cell types, and high-throughput serial two-photon tomography to image the EGFP-labelled axons throughout the brain. This systematic and standardized approach allows spatial registration of individual experiments into a common three dimensional (3D) reference space, resulting in a whole-brain connectivity matrix. A computational model yields insights into connectional strength distribution, symmetry and other network properties. Virtual tractography illustrates 3D topography among interconnected regions. Cortico-thalamic pathway analysis demonstrates segregation and integration of parallel pathways. The Allen Mouse Brain Connectivity Atlas is a freely available, foundational resource for structural and functional investigations into the neural circuits that support behavioural and cognitive processes in health and disease.

A High-Resolution Spatiotemporal Atlas of Gene Expression of the Developing Mouse Brain

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for ∼2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (http://developingmouse.brain-map.org).

Exploration and visualization of gene expression with neuroanatomy in the adult mouse brain

BackgroundSpatially mapped large scale gene expression databases enable quantitative comparison of data measurements across genes, anatomy, and phenotype. In most ongoing efforts to study gene expression in the mammalian brain, significant resources are applied to the mapping and visualization of data. This paper describes the implementation and utility of Brain Explorer, a 3D visualization tool for studying in situ hybridization-based (ISH) expression patterns in the Allen Brain Atlas, a genome-wide survey of 21,000 expression patterns in the C57BL\6J adult mouse brain.ResultsBrain Explorer enables users to visualize gene expression data from the C57Bl/6J mouse brain in 3D at a resolution of 100 μm3, allowing co-display of several experiments as well as 179 reference neuro-anatomical structures. Brain Explorer also allows viewing of the original ISH images referenced from any point in a 3D data set. Anatomic and spatial homology searches can be performed from the application to find data sets with expression in specific structures and with similar expression patterns. This latter feature allows for anatomy independent queries and genome wide expression correlation studies.ConclusionThese tools offer convenient access to detailed expression information in the adult mouse brain and the ability to perform data mining and visualization of gene expression and neuroanatomy in an integrated manner.

Neuroinformatics of the Allen Mouse Brain Connectivity Atlas

The Allen Mouse Brain Connectivity Atlas is a mesoscale whole brain axonal projection atlas of the C57Bl/6J mouse brain. Anatomical trajectories throughout the brain were mapped into a common 3D space using a standardized platform to generate a comprehensive and quantitative database of inter-areal and cell-type-specific projections. This connectivity atlas has several desirable features, including brain-wide coverage, validated and versatile experimental techniques, a single standardized data format, a quantifiable and integrated neuroinformatics resource, and an open-access public online database (http://connectivity.brain-map.org/). Meaningful informatics data quantification and comparison is key to effective use and interpretation of connectome data. This relies on successful definition of a high fidelity atlas template and framework, mapping precision of raw data sets into the 3D reference framework, accurate signal detection and quantitative connection strength algorithms, and effective presentation in an integrated online application. Here we describe key informatics pipeline steps in the creation of the Allen Mouse Brain Connectivity Atlas and include basic application use cases.

NeuroBlast: a 3D spatial homology search tool for gene expression

Background Finding genes with a similar spatial expression pattern as a known gene could potentially reveal novel or unknown genes involved in similar processes or pathways. The Allen Brain Atlas (ABA) [1] is an effort to produce a genomewide mapping of the gene expression in the adult C57BL/ 6J mouse brain. To date, more than 21,000 genes have been assayed using a high-throughput in situ hybridization (ISH) platform and the resulting image data is publicly available at http://brain-map.org. A major goal of the ABA project is to employ image analysis techniques to search the ABA data for particular expression patterns such as spatial gene expression homologues. Methods Each ISH image series is processed through an automated anatomic mapping pipeline with the goal of determining expression sites and the spatial localization of these sites with respect to a 3D reference brain. Expression statistics is then aggregated with respect to individual 200 μm3 cubes in reference space thereby reducing data complexity from > 2 × 108 pixels per series to ~2.5 × 104 cubes. Since every image series is spatially mapped with accurate registration to the same 3D reference space, we can compare expression statistics on a global scale in approximately the same 200 μm3 spatial extent for all series. The most straightforward approach to finding spatial homologues from Sixteenth Annual Computational Neuroscience Meeting: CNS*2007 Toronto, Canada. 7–12 July 2007

The allen brain atlas: delivering neuroscience to the web on a genome wide scale

The Allen Brain Atlas (ABA), publicly available at http:// www.brain-map.org, presents the expression patterns of more than 21,500 genes in the adult mouse brain. The project has produced more than 600 Terabytes of cellular level in situ hybridization data whose images have been reconstructed and mapped into whole brain 3D volumes for search and viewing. In this application paper we outline the bioinformatics, data integration, and presentation approach to the ABA and the creation a fully automated high-throughput pipeline to deliver this data set to the Web.

Exploration and visualization of connectivity in the adult mouse brain

The Allen Mouse Brain Connectivity Atlas is a mesoscale whole brain axonal projection atlas of the C57Bl/6J mouse brain. All data were aligned to a common template in 3D space to generate a comprehensive and quantitative database of inter-areal and cell-type-specific projections. A suite of computational tools were developed to search and visualize the projection labeling experiments, available at http://connectivity.brain-map.org. We present three use cases illustrating how these publicly-available tools can be used to perform analyses of long range brain region connectivity. The use cases make extensive use of advanced visualization tools integrated with the atlas including projection density histograms, 3D computed anterograde and retrograde projection paths, and multi-specimen projection composites. These tools offer convenient access to detailed axonal projection information in the adult mouse brain and the ability to perform data analysis and visualization of projection fields and neuroanatomy in an integrated manner.

A large-scale, standardized physiological survey reveals higher order coding throughout the mouse visual cortex

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of neural activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes cortical activity from nearly 60,000 neurons collected from 6 visual areas, 4 layers, and 12 transgenic mouse lines from 221 adult mice, in response to a systematic set of visual stimuli. Using this dataset, we reveal functional differences across these dimensions and show that visual cortical responses are sparse but correlated. Surprisingly, responses to different stimuli are largely independent, e.g. whether a neuron responds to natural scenes provides no information about whether it responds to natural movies or to gratings. We show that these phenomena cannot be explained by standard local filter-based models, but are consistent with multi-layer hierarchical computation, as found in deeper layers of standard convolutional neural networks.

An anatomic transcriptional atlas of human glioblastoma

Anatomically correct tumor genomics Glioblastoma is the most lethal form of human brain cancer. The genomic alterations and gene expression profiles characterizing this tumor type have been widely studied. Puchalski et al. created the Ivy Glioblastoma Atlas, a freely available online resource for the research community. The atlas, a collaborative effort between bioinformaticians and pathologists, maps molecular features of glioblastomas, such as transcriptional signatures, to histologically defined anatomical regions of the tumors. The relationships identified in this atlas, in conjunction with associated databases of clinical and genomic information, could provide new insights into the pathogenesis, diagnosis, and treatment of glioblastoma. Science, this issue p. 660 An online resource maps the molecular genetic features of glioblastoma, a lethal brain cancer, to its anatomic features. Glioblastoma is an aggressive brain tumor that carries a poor prognosis. The tumor’s molecular and cellular landscapes are complex, and their relationships to histologic features routinely used for diagnosis are unclear. We present the Ivy Glioblastoma Atlas, an anatomically based transcriptional atlas of human glioblastoma that aligns individual histologic features with genomic alterations and gene expression patterns, thus assigning molecular information to the most important morphologic hallmarks of the tumor. The atlas and its clinical and genomic database are freely accessible online data resources that will serve as a valuable platform for future investigations of glioblastoma pathogenesis, diagnosis, and treatment.

The organization of intracortical connections by layer and cell class in the mouse brain

The mammalian cortex is a laminar structure composed of many cell types densely interconnected in complex ways. Recent systematic efforts to map the mouse mesoscale connectome provide comprehensive projection data on interareal connections, but not at the level of specific cell classes or layers within cortical areas. We present here a significant expansion of the Allen Mouse Brain Connectivity Atlas, with ∼1,000 new axonal projection mapping experiments across nearly all isocortical areas in 49 Cre driver lines. Using 13 lines selective for cortical layer-specific projection neuron classes, we identify the differential contribution of each layer/class to the overall intracortical connectivity patterns. We find layer 5 (L5) projection neurons account for essentially all intracortical outputs. L2/3, L4, and L6 neurons contact a subset of the L5 cortical targets. We also describe the most common axon lamination patterns in cortical targets. Most patterns are consistent with previous anatomical rules used to determine hierarchical position between cortical areas (feedforward, feedback), with notable exceptions. While diverse target lamination patterns arise from every source layer/class, L2/3 and L4 neurons are primarily associated with feedforward type projection patterns and L6 with feedback. L5 has both feedforward and feedback projection patterns. Finally, network analyses revealed a modular organization of the intracortical connectome. By labeling interareal and intermodule connections as feedforward or feedback, we present an integrated view of the intracortical connectome as a hierarchical network.