Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Connectome, General

  • Yoonsuck ChoeEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_277-1


Connectome is the full connection matrix (or the full wiring diagram) of all neurons in the brain (Sporns et al. 2005). Current efforts in connectomics (study of the connectome) can be grouped along two axes, one based on scale (macro [or regional] vs. micro [or cellular] connectome) and the other based on research focus (data acquisition technology vs. theoretical frameworks and analysis). The end goal of connectomics is to understand how the brain works based on its intricate circuitry, i.e., to go from complete structure to detailed function. See Seung (2012) and Sporns (2011, 2012) for a general overview of connectomics.

Detailed Description

The main underlying assumption in connectomics is that the brain’s connective architecture determines in large part its function (Sporns 2012; Seung 2012). This assumption can be put in an evolutionary context, as noted by Swanson (2003): Evolution from simple neuronal networks in primitive animals to complex brains of animals like...


Effective Connectivity Synthetic Circuit Major White Matter Tract Human Connectome Project High Spatial Scale 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Part of the contents of this chapter (section “Analysis and Utilization of Connectome Data”) first appeared in Choe et al. (2011).


  1. Ahrens MB, Orger MB, Robson DN, Li JM, Keller PJ (2013) Whole-brain functional imaging at cellular resolution using light-sheet microscopy. Nat Methods 10:413–420PubMedCrossRefGoogle Scholar
  2. Amunts K, Lepage C, Borgeat L, Mohlberg H, Dickscheid T, Rousseau M-E, Bludau S, Bazin P-L, Lewis LB, Oros-Peusquens A-M, Shah NJ, Lippert T, Zilles K, Evans AC (2013) Bigbrain: an ultrahigh-resolution 3d human brain model. Science 340:1472–1475PubMedCrossRefGoogle Scholar
  3. Anderson JR, Jones BW, Watt CB, Shaw MV, Yang J-H, DeMill D, Lauritzen JS, Lin Y, Rapp KD, Mastronarde D, Koshevoy P, Grimm B, Tasdizen T, Whitaker R, Marc RE (2011) Exploring the retinal connectome. Mol Vis 17:355–379PubMedCentralPubMedCrossRefGoogle Scholar
  4. Ascoli G, Krichmar J, Scorcioni R, Nasuto S, Senft S (2001) Computer generation and quantitative morphometric analysis of virtual neurons. Anat Embryol 204:283–301PubMedCrossRefGoogle Scholar
  5. Axer M, Amunts K, Grassel D, Palm C, Dammers J, Axer H, Pietrzyk U, Zilles K (2011) A novel approach to the human connectome: ultra-high resolution mapping of fiber tracts in the brain. Neuroimage 54:1091–1101PubMedCrossRefGoogle Scholar
  6. Barabasi A-L (2002) Linked: the new science of networks. Perseus Publishing, Cambridge, MAGoogle Scholar
  7. Bebis G, Boyle R, Parvin B, Koracin D, Chung R (Eds.) (2010) Advances in Visual Computing: 6th International Symposium, ISVC 2010, Las Vegas, NV, USA, Nov 29-Dec 1, 2010, Proceedings (Vol. 1). SpringerGoogle Scholar
  8. Bennett MR, Hacker PMS (2003) Philosophical foundations of neuroscience. Blackwell, Malden, MAGoogle Scholar
  9. Bock DD, Kerlin AM, Andermann ML, Hood G, Wetzel AW, Yurgenson S, Soucy ER, Kim HS, Reid RC (2011) Network anatomy and in vivo physiology of visual cortical neurons. Nature 471:177–182PubMedCentralPubMedCrossRefGoogle Scholar
  10. Bower JM, Beeman D (1998) The book of GENESIS: exploring realistic neural models with the GEneral NEural SImulation System. Telos, Santa ClaraCrossRefGoogle Scholar
  11. Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198PubMedCrossRefGoogle Scholar
  12. Chklovskii DB, Vitaladevuni S, Scheffer LK (2010) Semi-automated reconstruction of neural circuits using electron microscopy. Curr Opin Neurobiol 20(5):667–675. Neuronal and glial cell biology – new technologiesGoogle Scholar
  13. Choe Y, Yang H-F, Eng DC-Y (2007) Autonomous learning of the semantics of internal sensory states based on motor exploration. Int J Hum Robot 4:211–243CrossRefGoogle Scholar
  14. Choe Y, Mayerich D, Kwon J, Miller DE, Chung JR, Sung C, Keyser J, Abbott LC (2011) Knife-edge scanning microscopy for connectomics research. In: Proceedings of the international joint conference on neural networks. IEEE Press, Piscataway, pp 2258–2265Google Scholar
  15. Choe Y, Kwon J, Chung JR (2012) Time, consciousness, and mind uploading. Int J Mach Conscious 4:257–274CrossRefGoogle Scholar
  16. Chung JR, Choe Y (2011) Emergence of memory in reactive agents equipped with environmental markers. IEEE Trans Auton Ment Develop 3:257–271CrossRefGoogle Scholar
  17. Chung K, Diesseroth K (2013) CLARITY for mapping the nervous system. Nat Methods 10:508–513PubMedCrossRefGoogle Scholar
  18. Chung JR, Sung C, Mayerich D, Kwon J, Miller DE, Huffman T, Abbott LC, Keyser J, Choe Y (2011) Multiscale exploration of mouse brain microstructures using the knife-edge scanning microscope brain atlas. Front Neuroinform 5:29PubMedCentralPubMedCrossRefGoogle Scholar
  19. Churchland PM (2005) Cleansing science. Inquiry 5:464–477CrossRefGoogle Scholar
  20. Dayan P, Abbott LF (2001) Theoretical neuroscience. MIT Press, Cambridge, MAGoogle Scholar
  21. de Reus MA, van den Heuvel MP (2013) Rich club organization and intermodule communication in the cat connectome. J Neurosci 33:12929–12939PubMedCrossRefGoogle Scholar
  22. DeFelipe J (2010) From the connectome to the synaptome: an epic love story. Science 330:1198–1201PubMedCrossRefGoogle Scholar
  23. Denk W, Horstmann H (2004) Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biol 19:e329CrossRefGoogle Scholar
  24. Druckmann S, Berger TK, Hill S, Schurmann F, Markram H, Segev I (2008) Evaluating automated parameter constraining procedures of neuron models by experimental and surrogate data. Biol Cybern 99:371–379PubMedCrossRefGoogle Scholar
  25. Eberhard JP, Wanner A, Wittum G (2006) NeuGen: a tool for the generation of realistic morphology of cortical neurons and neural networks. Neurocomputing 70:327–342CrossRefGoogle Scholar
  26. Edwards J, Daniel E, Kinney J, Bartol T, Sejnowski T, Johnston D, Harris K, Bajaj C (2013) Volrovern: enhancing surface and volumetric reconstruction for realistic dynamical simulation of cellular and subcellular function. Neuroinformatics 11:1–13CrossRefGoogle Scholar
  27. Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in primate cerebral cortex. Cereb Cortex 1:1–47PubMedCrossRefGoogle Scholar
  28. Fiala JC (2005) Reconstruct: a free editor for serial section microscopy. J Microsc 218:52–61PubMedCrossRefGoogle Scholar
  29. Friston K (2011) Functional and effective connectivity: a review. Brain Connect 1:13–36PubMedCrossRefGoogle Scholar
  30. Fuster JM (1997) The prefrontal cortex: anatomy, physiology, and the frontal lobe, 3rd edn. Lippencott-Raven, PhiladelphiaGoogle Scholar
  31. Gleeson P, Steuber V, Silver R (2007) NeuroConstruct: a tool for modeling networks of neurons in 3D space. Neuron 54:219–235PubMedCentralPubMedCrossRefGoogle Scholar
  32. Hagmann P, Kurant M, Gigandet X, Thiran P, Wedeen VJ, Meuli R, Thiran J-P (2007) Mapping human whole-brain structural networks with diffusion MRI. PLoS One 2:e597PubMedCentralPubMedCrossRefGoogle Scholar
  33. Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey CJ, Wedeen VJ, Sporns O (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6:e159PubMedCentralPubMedCrossRefGoogle Scholar
  34. Hayworth KJ, Kasthuri N, Schalek R, Lichtman JW (2006) Automating the collection of ultrathin sections for large volume TEM reconstructions. Microsc Microanal 12(Suppl S02):86–87CrossRefGoogle Scholar
  35. Helmstaedter M, Briggman KL, Turaga SC, Jain V, Seung HS, Denk W (2013) Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature 500:168–174PubMedCrossRefGoogle Scholar
  36. Hines ML, Carnevale NT (1997) The NEURON simulation environment. Neural Comput 9:1179–1209PubMedCrossRefGoogle Scholar
  37. Hintiryan H, Gou L, Zingg B, Yamashita S, Lyden HM, Song MY, Grewal AK, Zhang X, Toga AW, Dong H-W (2012) Comprehensive connectivity of the mouse main olfactory bulb: analysis and online digital atlas. Front Neuroanat 6:30PubMedCentralPubMedCrossRefGoogle Scholar
  38. Humphrey N (1992) A history of the mind. HarperCollins, New YorkCrossRefGoogle Scholar
  39. Izhikevich EM, Edelman GM (2008) Large-scale model of mammalian thalamocortical systems. Proc Natl Acad Sci U S A 105:3593–3598PubMedCentralPubMedCrossRefGoogle Scholar
  40. Jain V, Seung HS, Turaga SC (2010) Machines that learn to segment images: a crucial technology for connectomics. Curr Opin Neurobiol 20:653–666PubMedCentralPubMedCrossRefGoogle Scholar
  41. Johansen-Berg H, Rushworth MF (2009) Using diffusion imaging to study human connectional anatomy. Annu Rev Neurosci 32:75–94PubMedCrossRefGoogle Scholar
  42. Kaiser M (2011) A tutorial in connectome analysis: topological and spatial features of brain networks. Neuroimage 57:892–907PubMedCrossRefGoogle Scholar
  43. Kaiser M, Hilgetag CC (2006) Nonoptimal component placement, but short processing paths, due to long-distance projections in neural systems. PLoS Comput Biol 2:805–815CrossRefGoogle Scholar
  44. Kalisman N, Silberberg G, Markram H (2003) Deriving physical connectivity from neuronal morphology. Biol Cybern 88:210–218PubMedCrossRefGoogle Scholar
  45. Keller PJ, Schmidt AD, Wittbrodt J, Stelzer EHK (2008) Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy. Science 322:1065–1069PubMedCrossRefGoogle Scholar
  46. Kleinfeld D, Bharioke A, Blinder P, Bock DD, Briggman KL, Chklovskii DB, Denk W, Helm-Staedter M, Kaufhold JP, Lee W-CA, Meyer HS, Micheva KD, Oberlaender M, Prohaska S, Reid RC, Smith SJ, Takemura S, Tsai PS, Sakmann B (2011) Large-scale automated histology in the pursuit of connectomes. J Neurosci 31:16125–16138PubMedCentralPubMedCrossRefGoogle Scholar
  47. Koene R (2012) Fundamentals of whole brain emulation: state, transition, and update representations. Int J Mach Conscious 4:5–21CrossRefGoogle Scholar
  48. Koene RA (2007) Large scale high resolution network generation: producing known validation sets for serial reconstruction methods that use histological images of neural tissue. In: International conference on complex systems. [Presentation]Google Scholar
  49. Koene RA, Tijms B, van Hees P, Postma F, de Ridder A, Ramakers GJA, van Pelt J, van Ooyen A (2009) NETMORPH: a framework for the stochastic generation of large scale neuronal networks with realistic neuron morphologies. Neuroinformatics 7:1539–2791CrossRefGoogle Scholar
  50. Kreshuk A, Straehle C, Sommer C, Koethe U, Cantoni M, Knott G, Hamprecht FA (2011) Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images. PLoS One 6:e24899PubMedCentralPubMedCrossRefGoogle Scholar
  51. Kwon J, Choe Y (2009) Facilitating neural dynamics for delay compensation: a road to predictive neural dynamics? Neural Netw 22:267–276PubMedCrossRefGoogle Scholar
  52. Lamme VAF, Roelfsema PR (2000) The distinct modes of vision offered by feedforward and recurrent processing. Trends Neurosci 23:571–579PubMedCrossRefGoogle Scholar
  53. Larson-Prior L, Oostenveld R, Penna SD, Michalareas G, Prior F, Babajani-Feremi A, Schoffelen J-M, Marzetti L, de Pasquale F, Pompeo FD, Stout J, Woolrich M, Luo Q, Bucholz R, Fries P, Pizzella V, Romani G, Corbetta M, Snyder A (2013) Adding dynamics to the human connectome project with MEG. Neuroimage 80:190–201PubMedCrossRefGoogle Scholar
  54. Lee JH, Durand R, Gradinaru V, Zhang F, Goshen I, Kim D-S, Fenno LE, Ramakrishnan C, Deisseroth K (2010) Global and local fMRI signals driven by neurons defined optogenetically by type and wiring. Nature 465:788–792PubMedCentralPubMedCrossRefGoogle Scholar
  55. Lein ES et al (2007) Genome-wide atlas of gene expression in the adult mouse brain. Nature 445:168–176PubMedCrossRefGoogle Scholar
  56. Li A, Gong H, Zhang B, Wang Q, Wan C, Wu J, Liu Q, Zeng S, Luo Q (2010a) Microoptical sectioning tomography to obtain a high-resolution atlas of the mouse brain. Science 330:1404–1408PubMedCrossRefGoogle Scholar
  57. Li L, Tasic B, Micheva KD, Ivanov VM, Spletter ML, Smith SJ, Luo L (2010b) Visualizing the distribution of synapses from individual neurons in the mouse brain. PLoS One 5:e11503PubMedCentralPubMedCrossRefGoogle Scholar
  58. Lichtman JW, Sanes JR (2008) Ome sweet ome: what can the genome tell us about the connectome? Curr Opin Neurobiol 18(3):346–353PubMedCentralPubMedCrossRefGoogle Scholar
  59. Llinás R, Ribary E, Joliot M, Wang G (1994) Content and context in temporal thalamocortical binding. In: Buzsaki G (ed) Temporal coding in the brain. Springer, BerlinGoogle Scholar
  60. Margulies DS, Bttger J, Watanabe A, Gorgolewski KJ (2013) Visualizing the human connectome. Neuroimage 80:445–461PubMedCrossRefGoogle Scholar
  61. Markram H (2006) The blue brain project. Nat Rev Neurosci 7:153–160PubMedCrossRefGoogle Scholar
  62. Mayerich D, Hart J (2007) Volume visualization in serial electron microscopy using local variance. In: IEEE symposium on biological data visualization (BioVis), IEEE, Piscataway, NJ pp 1–6Google Scholar
  63. Mayerich D, Abbott LC, McCormick BH (2008) Knife-edge scanning microscopy for imaging and reconstruction of three-dimensional anatomical structures of the mouse brain. J Microsc 231:134–143PubMedCrossRefGoogle Scholar
  64. Mel BW (1994) Information processing in dendritic trees. Neural Comput 6:1031–1085CrossRefGoogle Scholar
  65. Meyer J, Thomas J, Diehl S, Fisher BD, Keim DA, Laidlaw D, Miksch S, Mueller K, Ribarsky W, Preim B, Ynnerman A (2010) From visualization to visually enabled reasoning. Sci Vis: Adv Concepts 1:227–245Google Scholar
  66. Micheva K, Smith SJ (2007) Array tomography: a new tool for imaging the molecular architecture and ultrastructure of neural circuits. Neuron 55:25–36PubMedCentralPubMedCrossRefGoogle Scholar
  67. Miikkulainen R, Bednar JA, Choe Y, Sirosh J (2005) Computational maps in the visual cortex. Springer, Berlin, p 538. URL: http://www.computationalmaps.org
  68. Mikula S, Trotts I, Stone JM, Jones EG (2007) Internet-enabled high-resolution brain mapping and virtual microscopy. Neuroimage 35:9–15PubMedCentralPubMedCrossRefGoogle Scholar
  69. Mishchenko Y, Hu T, Spacek J, Mendenhall J, Harris KM, Chklovskii DB (2010) Ultrastructural analysis of hippocampal neuropil from the connectomics perspective. Neuron 67:1009–1020PubMedCentralPubMedCrossRefGoogle Scholar
  70. Mitra PP (2012) Technical white paper: mouse brain architecture project. Technical report, Cold Spring Harbor Laboratory. http://brainarchitecture.org
  71. Nowak LG, Bullier J (1997) The timing of information transfer in the visual system. In: Rockland KS, Kass JH, Peters A (eds) Cerebral cortex, vol 12. Plenum Press, New York, pp 205–241Google Scholar
  72. Park H-J, Kim JJ, Lee S-K, Seok JH, Chun J, Kim DI, Lee JD (2008) Corpus callosal connection mapping using cortical gray matter parcellation and dt-mri. Hum Brain Mapp 29:503–516PubMedCrossRefGoogle Scholar
  73. Pearl J (2001) Reasoning with cause and effect. AI Mag 23:95–111Google Scholar
  74. Polsky A, Mel BW, Schiller J (2004) Computational subunits in thin dendrites of pyramidal cells. Nat Neurosci 7:821–827CrossRefGoogle Scholar
  75. Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52:1059–1069PubMedCrossRefGoogle Scholar
  76. Searle JR (1980) Minds, brains and programs. Behav Brain Sci 3:417–424CrossRefGoogle Scholar
  77. Seung HS (2012) Connectome: how the brain’s wiring makes us who we are. Houghton Mifflin Harcourt, Boston, MAGoogle Scholar
  78. Shepherd GM (2004) The synaptic organization of the brain, 5th edn. Oxford University Press, Oxford, UK/New YorkCrossRefGoogle Scholar
  79. Sohn Y, Choi M-K, Ahn Y-Y, Lee J, Jeong J (2011) Topological cluster analysis reveals the systemic organization of the caenorhabditis elegans connectome. PLoS Comput Biol 7:e1001139PubMedCentralPubMedCrossRefGoogle Scholar
  80. Sporns O (2011) Networks of the brain. MIT Press, Cambridge, MAGoogle Scholar
  81. Sporns O (2012) Discovering the human connectome. MIT Press, Cambridge, MAGoogle Scholar
  82. Sporns O, Tononi G, Edelman GM (2000) Connectivity and complexity: the relationship between neuroanatomy and brain dynamics. Neural Netw 13:909–922PubMedCrossRefGoogle Scholar
  83. Sporns O, Tononi G, Kotter R (2005) The human connectome: a structural description of the human brain. PLoS Comput Biol 1:e42PubMedCentralPubMedCrossRefGoogle Scholar
  84. Srinivasan R, Li Q, Zhou X, Lu J, Lichtman J, Wong ST (2010) Reconstruction of the neuromuscular junction connectome. Bioinformatics 26:i64–i70PubMedCentralPubMedCrossRefGoogle Scholar
  85. Swanson LW (2003) Brain architecture: understanding the basic plan. Oxford University Press, OxfordGoogle Scholar
  86. Swanson LW, Bota M (2010) Foundational model of structural connectivity in the nervous system with a schema for wiring diagrams, connectome, and basic plan architecture. Proc Natl Acad Sci 107:20610–20617PubMedCentralPubMedCrossRefGoogle Scholar
  87. Takemura S-Y, Bharioke A, Lu Z, Nern A, Vitaladevuni S, Rivlin PK, Katz WT, Olbris DJ, Plaza SM, Winston P, Zhao T, Horne JA, Fetter RD, Takemura S, Blazek K, Chang L, Ogundeyi O, Saunders MA, Shapiro V, Sigmund C, Rubin GM, Scheffer LK, Meinertzhagen IA, Chklovskii DB (2013) A visual motion detection circuit suggested by drosophila connectomics. Nature 500:175–181PubMedCentralPubMedCrossRefGoogle Scholar
  88. Thiel A, Schwegler H, Eurich CW (2003) Complex dynamics is abolished in delayed recurrent systems with distributed feedback times. Complexity 8:102–108CrossRefGoogle Scholar
  89. Toledo-Rodriguez M, Blumenfeld B, Wu C, Luo J, Attali B, Goodman P, Markram H (2004) Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex. Cereb Cortex 14:1310–1327PubMedCrossRefGoogle Scholar
  90. van den Heuvel MP, Sporns O (2011) Rich-club organization of the human connectome. J Neurosci 31:15775–15786PubMedCrossRefGoogle Scholar
  91. Watts DJ, Strogatz SH (1998) Collective dynamics of small-world networks. Nature 393:440–442PubMedCrossRefGoogle Scholar
  92. Weng J, McClelland JL, Pentland A, Sporns O, Stockman I, Sur M, Thelen E (2001) Autonomous mental development by robots and animals. Science 291(5504):599–600PubMedCrossRefGoogle Scholar
  93. White JG, Southgate E, Thomson JN, Brenner S (1986) The structure of the nervous system of the nematode caenorhabditis elegans. Philos Trans R Soc Lond B 314:1–340CrossRefGoogle Scholar
  94. Xu SWEM, Jarrell TA, Wang Y, Cook SJ, Hall DH (2013) Computer assisted assembly of connectomes from electron micrographs: application to caenorhabditis elegans. PLoS One 8:e54050PubMedCentralPubMedCrossRefGoogle Scholar
  95. Zhou J, Gennatas ED, Kramer JH, Miller BL, Seeley WW (2012) Predicting regional neurodegeneration from the healthy brain functional connectome. Neuron, 73:1216–1227Google Scholar

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© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringTexas A&M UniversityCollege StationUSA