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Structural neurobiology: missing link to a mechanistic understanding of neural computation

Abstract

High-resolution, comprehensive structural information is often the final arbiter between competing mechanistic models of biological processes, and can serve as inspiration for new hypotheses. In molecular biology, definitive structural data at atomic resolution are available for many macromolecules; however, information about the structure of the brain is much less complete, both in scope and resolution. Several technical developments over the past decade, such as serial block-face electron microscopy and trans-synaptic viral tracing, have made the structural biology of neural circuits conceivable: we may be able to obtain the structural information needed to reconstruct the network of cellular connections for large parts of, or even an entire, mouse brain within a decade or so. Given that the brain's algorithms are ultimately encoded by this network, knowing where all of these connections are should, at the very least, provide the data needed to distinguish between models of neural computation.

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Figure 1: Dissecting a computational device.
Figure 2: Cells in the retina manually reconstructed from serial block-face electron microscopy data.

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Acknowledgements

We thank P. Detwiler and A. Karpova for their critical reading of the manuscript.

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SBEM Technology licensed to Gatan results in royalty income to Winfried Denk. Kevin Briggman and Moritz Helmstaedter declare no competing interests.

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Denk, W., Briggman, K. & Helmstaedter, M. Structural neurobiology: missing link to a mechanistic understanding of neural computation. Nat Rev Neurosci 13, 351–358 (2012). https://doi.org/10.1038/nrn3169

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