Mesoscale connectomics
Section snippets
Traditional tracers
Historically, inter-areal connections are mapped using a variety of tract tracers. These tract tracers can be made of chemical compounds, glycoproteins, radioactively tagged amino acids or fluorescently conjugated beads that can be transported along axon fibers in either directions (see [19, 20] for a comprehensive overview). Commonly-used tracers that move principally in the anterograde direction, that is, from the soma to the tips of the axons, include biotinylated dextran amine (BDA),
Virus-mediated anterograde and retrograde tracing
Harnessing the power of nature, a plethora of neurotropic viruses have been modified to support a wide range of neuroscience applications including neuroanatomical connectivity mapping. Readers should refer to an excellent recent review [19] that more systematically describes all the major types of recombinant viral vectors for neuroanatomical studies. Here I focus on the most recent technical advances in viral tools for mesoscale connectivity mapping.
In anterograde tracing, cells at the viral
Trans-synaptic tracing
The anterograde and retrograde tracing techniques described thus far enable one to map connections between cell populations and regions. To establish connections between input and recipient cell populations requires trans-synaptic (or trans-neuronal) tracing, in which the viral tracer is transported across synapses in either the anterograde or retrograde direction and label both presynaptic and postsynaptic neurons simultaneously. Monosynaptic trans-synaptic tracing, that is, the viral tracer
Combinatorial and functional circuit mapping
The array of anterograde, retrograde and trans-synaptic viral tools can be combined, and sometimes coupled with transgenic lines, to enable even more sophisticated circuit mapping approaches (for a comprehensive overview see [47]). For example, combining a retrograde tracer (e.g., CAV2-Cre) with an anterograde tracer (e.g., Cre-dependent AAV) can assess target-defined projection specificity [48] (Figure 1d). The ‘tracing the relationship between input and output’ (TRIO) method combines CAV2-Cre
Imaging, image registration and data analysis
To facilitate standardized data generation and comparison, and to enable the creation of brain-wide connectomic maps, it is important to establish standardized imaging platforms. Given that mesoscale connectomes are largely fluorescence-based datasets, high-throughput fluorescence imaging platforms have been deployed, including section-based epifluorescence slide scanners and whole-brain serial two-photon (STP) tomography [52, 53, 54, 55]. To enable more efficient whole-brain imaging, many
Cell type characterization and development of cell type targeting tools
Mesoscale connectomics requires a solid foundation of cell types across all brain regions. However, our understanding of cell types in the brain remains far from complete. Large-scale efforts are underway to systematically characterize brain cell types in the mouse at transcriptomic, morphological and physiological levels [74]. Integrating these multi-dimensional properties of individual cells is essential for deriving a unified cell type taxonomy [75].
Single-cell transcriptomic profiling is
Single cell projectome and barcode connectomics
Connectivity itself is also likely to be an important criterion for definition of a cell type. At the single cell level, the full extent of the dendritic and axonal morphology of a neuron can be considered a partial surrogate for its connectivity, as it contains substantial, though not all, input/output connectional information. In fact, it was the neuronal morphologies that Cajal used to define a ‘neuron’ and the polarity of its information flow, and to discover neuronal diversity [81].
Outlook
Recent technological advances in virus engineering, imaging and genomics are rapidly transforming the landscape of connectomics and enabling us to conduct comprehensive and multi-faceted structure–function studies of brain-wide neuronal networks. I expect that mesoscale connectomics will be dramatically accelerated by our increased understanding of cell types in the brain, and through the mutually synergistic interaction between cell type characterization and connectomics, uncovering underlying
Conflict of interest statement
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
Acknowledgements
I am grateful to Gabe Murphy, Julie Harris, Christof Koch and Liqun Luo for valuable comments on the manuscript. This work was supported by the Allen Institute for Brain Science, and National Institutes of Health grants U01MH105982 and U19MH114830. I thank the Allen Institute founder, Paul G Allen, for his vision, encouragement, and support.
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