Circuit reconstruction tools today

Current Opinion in Neurobiology

Volumn 17, Issue 5, 2007, Pages 601-608

  Smith, Stephen J ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATION; BRAIN FUNCTION; ELECTRON MICROSCOPY; HUMAN; IMAGE RECONSTRUCTION; IMAGING; MOLECULAR IMAGING; NERVE CELL NETWORK; NONHUMAN; PRIORITY JOURNAL; REVIEW; SYNAPSE; TRANSGENIC MOUSE;

ANIMALS; BRAIN; BRAIN MAPPING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MICROSCOPY, ELECTRON; MODELS, NEUROLOGICAL; NERVE NET; NEURONS;

EID: 37549028828     PISSN: 09594388     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.conb.2007.11.004     Document Type: Review

References (44)

1. Ramon y Cajal S: Histology of the Nervous System of Man and Vertebrates. Oxford Press; (trans. 1995, N. Swanson, L. Swanson). Summarizes the work that first placed the concept of information processing by neural circuit structures on a firm anatomical foundation.
2. McKay R.D., and Hockfield S.J. Monoclonal antibodies distinguish antigenically discrete neuronal types in the vertebrate central nervous system. Proc Natl Acad Sci U S A 79 (1982) 6747-6751
3. Nelson S.B., Hempel C., and Sugino K. Probing the transcriptome of neuronal cell types. Curr Opin Neurobiol 16 5 (2006) 571-576 Epub 2006 Sept. 7
4. Molyneaux B.J., Arlotta P., Menezes J.R., and Macklis J.D. Neuronal subtype specification in the cerebral cortex. Nat Rev Neurosci 6 (2007) 427-437
5. Lein E.S., Hawrylycz M.J., Ao N., Ayres M., Bensinger A., Bernard A., Boe A.F., Boguski M.S., Brockway K.S., Byrnes E.J., et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445 (2007) 168-176
6. Feng G., Mellor R.H., Bernstein M., Keller-Peck C., Nguyen Q.T., Wallace M., Nerbonne J.M., Lichtman J.W., and Sanes J.R. Imaging neuronal subsets in transgenic mice expressing multiple spectral variants of GFP. Neuron 28 (2000) 41-51. This landmark work introduced strategies that have proven very versatile and powerful for making mice with color-coded neuronal subsets.
7. Hatten M.E., and Heintz N. Large-scale genomic approaches to brain development and circuitry. Annu Rev Neurosci 28 (2005) 89-108
8. Xu Q., Cobos I., De La Cruz E., Rubenstein J.L., and Anderson S.A. Origins of cortical interneuron subtypes. J Neurosci 24 (2004) 2612-2622
9. Monro S., and Pelham H.R.B. Use of peptide tagging to detect proteins expressed from cloned genes: deletion mapping functional domains of Drosophila hsp70. EMBO J 3 (1984) 3087-3093
10. Griffin B.A., Adams S.R., Jones J., and Tsien R.Y. Fluorescent labeling of recombinant proteins in living cells with FlAsH. Methods Enzymol 327 (2000) 565-578
11. Giepmans B.N., Adams S.R., Ellisman M.H., and Tsien R.Y. The fluorescent toolbox for assessing protein location and function. Science 312 (2006) 217-224
12. Livet J., Weissman T.A., Kang H., Draft R.W., Lu J., Bennis R., Sanes J.R., and Lichtman J.W. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450 (2007) 56-62. Introduces a powerful new approach to circumventing optical resolution limits that have limited optical imaging of complete neural circuits.
13. Luo L: Fly MARCM and mouse MADM: Genetic methods of labeling and manipulating single neurons. Brain Res Rev 2007, 55:220-227. A very promising new set of schemes for labeling and manipulating circuits.
14. Wickersham I.R., Lyon D.C., Barnard R.J., Mori T., Finke S., Conzelmann K.K., Young J.A., and Callaway E.M. Monosynaptic restriction of transsynaptic tracing from single, genetically targeted neurons. Neuron 53 (2007) 639-647. A new strategy for labeling cells and their monsynaptically partners only.
15. Micheva K.D., and Smith S.J. Array tomography: A new tool for imaging the molecular architecture and ultrastructure of neural circuits. Neuron 55 (2007) 25-36
16. Conchello J.A., and Lichtman J.W. Optical sectioning microscopy. Nat Methods 2 12 (2005) 920-931
17. Rhodes K.J., and Trimmer J.S. Antibodies as valuable neuroscience research tools versus reagents of mass distraction. J Neurosci 26 (2006) 8017-8020. Reviews important recent progress in validating antibody specificity.
18. Hell S.W. Far-field optical nanoscopy. Science 316 (2007) 1153-1158
19. Gustafsson M.G. Nonlinear structured-illumination microscopy: wide-field fluorescence imaging with theoretically unlimited resolution. Proc Natl Acad Sci U S A 102 (2005) 13081-13086
20. Betzig E., Patterson G.H., Sougrat R., Lindwasser O.W., Olenych S., Bonifacino J.S., Davidson M.W., Lippincott-Schwartz J., and Hess H.F. Imaging intracellular fluorescent proteins at nanometer resolution. Science 313 (2006) 1642-1645
21. Hess S.T., Girirajan T.P., and Mason M.D. Ultra-high resolution imaging by fluorescence photoactivation localization microscopy. Biophys J 91 (2006) 4258-4272
22. Bates M., Huang B., Dempsey G.T., and Zhuang X. Multicolor super-resolution imaging with photo-switchable fluorescent probes. Science 317 (2007) 1749-1753
23. Rust M.J., Bates M., and Zhuang X. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat Methods 3 (2006) 793-795. (Refs. [18-23] introduce new methods for fluorescence imaging at resolutions far higher than formerly respected diffraction limits. Most of these methods have been demonstrated mainly for two-dimensional imaging, but may be very useful to enhance fluorescence lateral resolution in three-dimensional imaging if used in conjunction with array tomography mechanical sectioning procedures).
24. Briggman K.L., and Denk W. Towards neural circuit reconstruction with volume electron microscopy techniques. Curr Opin Neurobiol 16 (2006) 562-570. Reviews the nascent field of high-throughput electron microscopy.
25. Denk W., and Horstmann H. Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biol 11 (2004) e329. Introduces the first fully automated method for the acquisition of volumetric data with resolution and accuracy adequate to allow tracing of neural circuit elements, and inspires a new field of high-throughput electron microscopic neuroanatomy.
26. Hayworth K.J., Kasthuri N., Schalek R., and Lichtman J.W. Automating the collection of ultrathin serial sections for large volume TEM reconstructions. Microscop Microanal 12 (2006) 86-87. Describes exciting an new microtome and an automated section collection scheme that are likely to be very useful for producing very-large-scale tomography arrays.
27. Levoy M. Display of surfaces from volume data. IEEE Comput Graph Appl 8 (1988) 29-37
28. Cai H., Xu X., Lu J., Lichtman J.W., Yung S.P., and Wong S.T. Repulsive force based snake model to segment and track neuronal axons in 3D microscopy image stacks. Neuroimage 32 4 (2006) 1608-1620
29. Fiala J.C., and Harris K. Computer-based alignment and reconstruction of serial sections. Microscop Anal USA Ed 52 (2002) 5-7
30. Fiala J.C. Reconstruct: a free editor for serial section microscopy. J Microscop 218 (2005) 52-61
31. Toni N., Teng E.M., Bushong E.A., Aimone J.B., Zhao C., Consiglio A., van Praag H., Martone M.E., Ellisman M.H., and Gage F.H. Synapse formation on neurons born in the adult hippocampus. Nat Neurosci 10 (2007) 727-734
32. Jain V, Murray JF, Roth F, Turaga S, Zhigulin V, Briggman KL, Helmstaedter MN, Denk W, and Seung HS: Supervised learning of image restoration with convolutional networks. IEEE Int Conf Comput Vis (ICCV), in press.
33. Stepanyants A., and Chklovskii D.B. Neurogeometry and potential synaptic connectivity. Trends Neurosci 28 (2005) 387-394. Introduces a very powerful way to make the most of incomplete information about circuit topologies.
34. Woolsey T.A., Dierker M.L., and Wann D.F. Mouse SmI cortex: qualitative and quantitative classification of golgi-impregnated barrel neurons. Proc Natl Acad Sci U S A 72 (1975) 2165-2169
35. Kleinfeld D., Ahissar E., and Diamond M.E. Active sensation: insights from the rodent vibrissa sensorimotor system. Curr Opin Neurobiol 16 (2006) 435-444
36. Petersen C.C., and Sakmann B. The excitatory neuronal network of rat layer 4 barrel cortex. J Neurosci 20 (2000) 7579-7586
37. Brecht M., Roth A., and Sakmann B. Dynamic receptive fields of reconstructed pyramidal cells in layers 3 and 2 of rat somatosensory barrel cortex. J Physiol 553 (2003) 243-265
38. Sato T.R., Gray N.W., Mainen Z.F., and Svoboda K. The functional microarchitecture of the mouse barrel cortex. PLoS Biol 5 (2007) e189
39. Micheva K.D., and Beaulieu C. Development and plasticity of the inhibitory neocortical circuitry with an emphasis on the rodent barrel field cortex: a review. Can J Physiol Pharmacol 75 (1997) 470-478
40. Knott G.W., Quairiaux C., Genoud C., and Welker E. Formation of dendritic spines with GABAergic synapses induced by whisker stimulation in adult mice. Neuron 34 (2002) 265-273
41. Grant S.G. Toward a molecular catalogue of synapses. Brain Res Rev 55 (2007) 445-449. Clearly articulates the importance of finding ways to measure and classify individual synapses in their native brain tissue contexts.
42. Swindale N.V. Is the cerebral cortex modular?. Trends Neurosci 13 (1990) 487-492
43. Milo R., Shen-Orr S., Itzkovitz S., Kashtan N., Chklovskii D., and Alon U. Network motifs: simple building blocks of complex networks. Science 298 (2002) 824-827
44. Migliore M., Cannia C., Lytton W.W., Markram H., and Hines M.L. Parallel network simulations with NEURON. J Comput Neurosci 21 (2006) 119-129. A strong argument that the computational power for circuit simulation will be ready as soon as the structural and molecular data for the model is available.