A mesoscale connectome of the mouse brain

By S. W. Oh, Julie A. Harris, L. Ng, B. Winslow, Nicholas Cain, Stefan Mihalas, Quanxin Wang, C. Lau, L. Kuan, A. Henry and 24 more. Nature, 2014

2,461 citations recorded by the source corpus.

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.

Subfields: Cell Biology, Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/aa0af55eb8dabf91ad8aafc77f5b5566cdef4ae0

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Citations in the corpus

Multi-scale brain networks (2016, neutral): “, 2015), and brain areas in mouse (Oh et al., 2014) and macaque (Markov et al.”
Artificial Neural Networks for Neuroscientists: A Primer (2020, background): “The extensive long-range connectivity across brain areas (Felleman and Van Essen, 1991; Markov et al., 2014; Oh et al., 2014) can be included in ANNs.”
Schizophrenia, Dopamine and the Striatum: From Biology to Symptoms (2019, background): “Recent methodological advances have further refined our understanding of corticostriatal architecture [9,10].”
Astrocyte crosstalk in CNS inflammation (2020, background): “Analogous approaches have transformed our understanding of neural circuits (Chen et al., 2019; Huang et al., 2020; Kebschull et al., 2016; Oh et al., 2014).”
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation (2020, positive): “…mapping experiments in Allen Mouse Brain Connectivity Atlas (http://connectivity.brain-map.org/; experiments 166269090, 166458363 and 181860879) (Oh et al., 2014) showed that neurons labeled via Scnn1a-Tg3-Cre transgene in RSP have long-range projections to both cortical and subcortical targets.”
Network neuroscience (2017, background): “High-throughput tracing and imaging approaches (which require careful monitoring of sensitivity and specificity) have resulted in network data sets recording the connections among ‘local processing units’ in Drosophila 17 as well as interregional projections in the mouse 18 .”
Modular Brain Networks (2015, methodology): “…mapped using various techniques, including reconstruction from serially sectioned electron micrographs (White et al. 1986) or the aggregation of data from anatomical tract-tracing experiments (Kötter et al. 2004, Markov et al. 2014, Oh et al. 2014, Scannell et al. 1995, Stephan et al. 2001).”
Sensitive red protein calcium indicators for imaging neural activity (2016, methodology): “, 2013]) and SYN1-GCaMP6s AAV was injected into cortical LM, which sends axons to V1 (Andermann et al., 2011; Oh et al., 2014).”
Parcellations and Connectivity Patterns in Human and Macaque Cerebral Cortex (2016, background): “…have recently been demonstrated in the mouse, based on an inter-areal parcellated connectome using anterograde tracers in ten areas of visual cortex (Wang et al. 2012; Burkhalter 2015) and on a mesoconnectome regional analysis involving nearly 300 bidirectionally analyzed pathways (Oh et al. 2014).”
Predictive Processing: A Canonical Cortical Computation (2018, positive): “Cortical areas receive bottom-up input from the thalamus or other cortical areas, as well as extensive top-down inputs from many nearby and distal cortical areas, and higher-order thalamic nuclei (Felleman and Van Essen, 1991; Markov et al., 2014; Oh et al., 2014; Sherman, 2016; Zingg et al., 2014),”