Brain Structure and Function

, Volume 223, Issue 8, pp 3633–3652 | Cite as

Cortical networks of the mouse brain elaborate within the gray matter

  • Akiya WatakabeEmail author
  • Junya Hirokawa
Original Article


In primates, proximal cortical areas are interconnected via within-cortex “intrinsic” pathway, whereas distant areas are connected via “extrinsic” white matter pathway. To date, such distinction has not been clearly done for small-brained mammals like rodents. In this study, we systematically analyzed the data of Allen Mouse Brain Connectivity Atlas to answer this question and found that the ipsilateral cortical connections in mice are almost exclusively contained within the gray matter, although we observed exceptions for projections from the retrosplenial area and the medial/orbital frontal areas. By analyzing axonal projections within the gray matter using Cortical Box method, which enabled us to investigate the layer patterns across different cortical areas, we obtained the following results. First, widespread axonal projections were observed in both upper and lower layers in the vicinity of injections, whereas highly specific “point-to-point” projections were observed toward remote areas. Second, such long-range projections were predominantly aligned in the anteromedial–posterolateral direction. Third, in the majority of these projections, the connecting axons traveled through layer 6. Finally, the projections from the primary and higher order areas to distant targets preferentially terminated in the middle and superficial layers, respectively, suggesting hierarchical connections similar to those of primates. Overall, our study demonstrated conspicuous differences in gray/white matter segregation of axonal projections between rodents and primates, despite certain similarities in the hierarchical cortical organization.


AAV Anterograde tracers Cortico-cortical projection Feedforward Feedback White matter 

Supplementary material

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  1. Bassett DS, Bullmore ET (2016) Small-world brain networks revisited. Neuroscientist 23:499–516Google Scholar
  2. Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198CrossRefGoogle Scholar
  3. Bullmore E, Sporns O (2012) The economy of brain network organization. Nat Rev Neurosci 13:336–349CrossRefGoogle Scholar
  4. Buzsáki G, Logothetis N, Singer W (2013) Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron 80:751–764CrossRefPubMedPubMedCentralGoogle Scholar
  5. Coogan TA, Burkhalter A (1993) Hierarchical organization of areas in rat visual cortex. J Neurosci 13:3749–3772CrossRefPubMedGoogle Scholar
  6. D’Souza RD, Burkhalter A (2017) A laminar organization for selective cortico-cortical communication. Front Neuroanat 11:71CrossRefPubMedPubMedCentralGoogle Scholar
  7. D’Souza RD, Meier AM, Bista P, Wang Q, Burkhalter A (2016) Recruitment of inhibition and excitation across mouse visual cortex depends on the hierarchy of interconnecting areas. Elife 5:e19332CrossRefPubMedPubMedCentralGoogle Scholar
  8. Ercsey-Ravasz M, Markov NT, Lamy C, Van Essen DC, Knoblauch K, Toroczkai Z, Kennedy H (2013) A predictive network model of cerebral cortical connectivity based on a distance rule. Neuron 80:184–197CrossRefPubMedPubMedCentralGoogle Scholar
  9. Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1:1–47CrossRefPubMedPubMedCentralGoogle Scholar
  10. Finlay BL (2016) Principles of network architecture emerging from comparisons of the cerebral cortex in large and small brains. PLoS Biol 14:e1002556CrossRefPubMedPubMedCentralGoogle Scholar
  11. Gămănuţ R, Kennedy H, Toroczkai Z, Ercsey-Ravasz M, Van Essen DC, Knoblauch K, Burkhalter A (2018) The mouse cortical connectome, characterized by an ultra-dense cortical graph, maintains specificity by distinct connectivity profiles. Neuron 97:698–715.e10CrossRefPubMedGoogle Scholar
  12. Goulas A, Uylings HBM, Hilgetag CC (2017) Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse. Brain Struct Funct 222:1281–1295CrossRefPubMedGoogle Scholar
  13. Hirokawa J, Bosch M, Sakata S, Sakurai Y, Yamamori T (2008a) Functional role of the secondary visual cortex in multisensory facilitation in rats. Neuroscience 153:1402–1417CrossRefPubMedGoogle Scholar
  14. Hirokawa J, Watakabe A, Ohsawa S, Yamamori T (2008b) Analysis of area-specific expression patterns of RORbeta, ER81 and Nurr1 mRNAs in rat neocortex by double in situ hybridization and cortical box method. PLoS One 3:e3266CrossRefPubMedPubMedCentralGoogle Scholar
  15. Hofman MA (2014) Evolution of the human brain: when bigger is better. Front Neuroanat 8:15CrossRefPubMedPubMedCentralGoogle Scholar
  16. Horvát S, Gămănuţ R, Ercsey-Ravasz M, Magrou L, GăăuțB, Van Essen DC, Burkhalter A, Knoblauch K, Toroczkai Z, Kennedy H (2016) Spatial embedding and wiring cost constrain the functional layout of the cortical network of rodents and primates. PLoS Biol 14:e1002512CrossRefPubMedPubMedCentralGoogle Scholar
  17. Kaas JH (2000) Why is brain size so important: design problems and solutions as neocortex gets bigger or smaller. Brain Mind 1:7–23CrossRefGoogle Scholar
  18. Leinweber M, Ward DR, Sobczak JM, Attinger A, Keller GB (2017) A sensorimotor circuit in mouse cortex for visual flow predictions. Neuron 95:1420–1432.e5CrossRefPubMedPubMedCentralGoogle Scholar
  19. Levitt JB, Lewis DA, Yoshioka T, Lund JS (1993) Topography of pyramidal neuron intrinsic connections in macaque monkey prefrontal cortex (areas 9 and 46). J Comp Neurol 338:360–376CrossRefPubMedPubMedCentralGoogle Scholar
  20. Liewald D, Miller R, Logothetis N, Wagner H-J, Schüz A (2014) Distribution of axon diameters in cortical white matter: an electron-microscopic study on three human brains and a macaque. Biol Cybern 108:541–557CrossRefPubMedPubMedCentralGoogle Scholar
  21. Liska A, Galbusera A, Schwarz AJ, Gozzi A (2015) Functional connectivity hubs of the mouse brain. Neuroimage 115:281–291CrossRefPubMedGoogle Scholar
  22. Lund JS, Yoshioka T, Levitt JB (1993) Comparison of intrinsic connectivity in different areas of macaque monkey cerebral cortex. Cereb Cortex 3:148–162CrossRefPubMedGoogle Scholar
  23. Manita S, Suzuki T, Homma C, Matsumoto T, Odagawa M, Yamada K, Ota K, Matsubara C, Inutsuka A, Sato M, Ohkura M, Yamanaka A, Yanagawa Y, Nakai J, Hayashi Y, Larkum ME, Murayama M (2015) A top-down cortical circuit for accurate sensory perception. Neuron 86:1304–1316CrossRefPubMedGoogle Scholar
  24. Markov NT, Misery P, Falchier A, Lamy C, Vezoli J, Quilodran R, Gariel MA, Giroud P, Ercsey-Ravasz M, Pilaz LJ, Huissoud C, Barone P, Dehay C, Toroczkai Z, Van Essen DC, Kennedy H, Knoblauch K (2011) Weight consistency specifies regularities of macaque cortical networks. Cereb Cortex 21:1254–1272CrossRefPubMedGoogle Scholar
  25. Markov NT, Vezoli J, Chameau P, Falchier A, Quilodran R, Huissoud C, Lamy C, Misery P, Giroud P, Ullman S, Barone P, Dehay C, Knoblauch K, Kennedy H (2014a) Anatomy of hierarchy: feedforward and feedback pathways in macaque visual cortex. J Comp Neurol 522:225–259CrossRefPubMedGoogle Scholar
  26. Markov NT, Ercsey-Ravasz MM, Ribeiro Gomes AR, Lamy C, Magrou L, Vezoli J, Misery P, Falchier A, Quilodran R, Gariel MA, Sallet J, Gamanut R, Huissoud C, Clavagnier S, Giroud P, Sappey-Marinier D, Barone P, Dehay C, Toroczkai Z, Knoblauch K, Van Essen DC, Kennedy H (2014b) A weighted and directed interareal connectivity matrix for macaque cerebral cortex. Cereb Cortex 24(1):17–36CrossRefPubMedGoogle Scholar
  27. Oh SW, Harris JA, Ng L, Winslow B, Cain N, Mihalas S, Wang Q, Lau C, Kuan L, Henry AM, Mortrud MT, Ouellette B, Nguyen TN, Sorensen SA, Slaughterbeck CR, Wakeman W, Li Y, Feng D, Ho A, Nicholas E, Hirokawa KE, Bohn P, Joines KM, Peng H, Hawrylycz MJ, Phillips JW, Hohmann JG, Wohnoutka P, Gerfen CR, Koch C, Bernard A, Dang C, Jones AR, Zeng H (2014) A mesoscale connectome of the mouse brain. Nature 508:207–214CrossRefPubMedPubMedCentralGoogle Scholar
  28. Pakkenberg B, Gundersen HJ (1997) Neocortical neuron number in humans: effect of sex and age. J Comp Neurol 384:312–320CrossRefPubMedGoogle Scholar
  29. Paxinos G (2014) The rat nervous system, fourth edition. Academic, New YorkGoogle Scholar
  30. Paxinos G, Franklin KBJ (2004) The mouse brain in stereotaxic coordinates. Elsevier, AmsterdamGoogle Scholar
  31. Ragan T, Kadiri LR, Venkataraju KU, Bahlmann K, Sutin J, Taranda J, Arganda-Carreras I, Kim Y, Seung HS, Osten P (2012) Serial two-photon tomography for automated ex vivo mouse brain imaging. Nat Methods 9:255–258CrossRefPubMedPubMedCentralGoogle Scholar
  32. Ringo JL (1991) Neuronal interconnection as a function of brain size. Brain Behav Evol 38:1–6CrossRefPubMedGoogle Scholar
  33. Rockland KS, Pandya DN (1979) Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey. Brain Res 179:3–20CrossRefPubMedGoogle Scholar
  34. Schüz A, Chaimow D, Liewald D, Dortenman M (2006) Quantitative aspects of corticocortical connections: a tracer study in the mouse. Cereb Cortex 16:1474–1486CrossRefPubMedGoogle Scholar
  35. Tamamaki N, Yanagawa Y, Tomioka R, Miyazaki J-I, Obata K, Kaneko T (2003) Green fluorescent protein expression and colocalization with calretinin, parvalbumin, and somatostatin in the GAD67-GFP knock-in mouse. J Comp Neurol 467(1):60–79CrossRefGoogle Scholar
  36. Vanni MP, Chan AW, Balbi M, Silasi G, Murphy TH (2017) Mesoscale mapping of mouse cortex reveals frequency-dependent cycling between distinct macroscale functional modules. J Neurosci 37:7513–7533CrossRefPubMedGoogle Scholar
  37. Wang Q, Burkhalter A (2007) Area map of mouse visual cortex. J Comp Neurol 502:339–357CrossRefPubMedGoogle Scholar
  38. Wang SS-H, Shultz JR, Burish MJ, Harrison KH, Hof PR, Towns LC, Wagers MW, Wyatt KD (2008) Functional trade-offs in white matter axonal scaling. J Neurosci 28:4047–4056CrossRefPubMedPubMedCentralGoogle Scholar
  39. Wang Q, Sporns O, Burkhalter A (2012) Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. J Neurosci 32:4386–4399CrossRefPubMedPubMedCentralGoogle Scholar
  40. Watakabe A, Hirokawa J, Ichinohe N, Ohsawa S, Kaneko T, Rockland KS, Yamamori T (2012) Area-specific substratification of deep layer neurons in the rat cortex. J Comp Neurol 520:3553–3573CrossRefPubMedPubMedCentralGoogle Scholar
  41. Watakabe A, Takaji M, Kato S, Kobayashi K, Mizukami H, Ozawa K, Ohsawa S, Matsui R, Watanabe D, Yamamori T (2014) Simultaneous visualization of extrinsic and intrinsic axon collaterals in Golgi-like detail for mouse corticothalamic and corticocortical cells: a double viral infection method. Front Neural Circ 8:110Google Scholar
  42. Zhang ZW, Deschêes M (1997) Intracortical axonal projections of lamina VI cells of the primary somatosensory cortex in the rat: a single-cell labeling study. J Neurosci 17:6365–6379CrossRefPubMedGoogle Scholar
  43. Zhang K, Sejnowski TJ (2000) A universal scaling law between gray matter and white matter of cerebral cortex. Proc Natl Acad Sci USA 97:5621–5626CrossRefPubMedGoogle Scholar
  44. Zhang S, Xu M, Chang W-C, Ma C, Hoang Do JP, Jeong D, Lei T, Fan JL, Dan Y (2016) Organization of long-range inputs and outputs of frontal cortex for top-down control. Nat Neurosci 19:1733–1742CrossRefPubMedPubMedCentralGoogle Scholar
  45. Zingg B, Hintiryan H, Gou L, Song MY, Bay M, Bienkowski MS, Foster NN, Yamashita S, Bowman I, Toga AW, Dong H-W (2014) Neural networks of the mouse neocortex. Cell 156:1096–1111CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Riken, Center for Brain ScienceWakoJapan
  2. 2.Laboratory of Neural InformationDoshisha UniversityKyotanabeJapan

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