Skip to main content
Erschienen in: Brain Structure and Function 8/2018

09.07.2018 | Original Article

Cortical networks of the mouse brain elaborate within the gray matter

verfasst von: Akiya Watakabe, Junya Hirokawa

Erschienen in: Brain Structure and Function | Ausgabe 8/2018

Einloggen, um Zugang zu erhalten

Abstract

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.
Anhänge
Nur mit Berechtigung zugänglich
Literatur
Zurück zum Zitat Bassett DS, Bullmore ET (2016) Small-world brain networks revisited. Neuroscientist 23:499–516 Bassett DS, Bullmore ET (2016) Small-world brain networks revisited. Neuroscientist 23:499–516
Zurück zum Zitat Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198CrossRefPubMed Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198CrossRefPubMed
Zurück zum Zitat Bullmore E, Sporns O (2012) The economy of brain network organization. Nat Rev Neurosci 13:336–349CrossRefPubMed Bullmore E, Sporns O (2012) The economy of brain network organization. Nat Rev Neurosci 13:336–349CrossRefPubMed
Zurück zum Zitat 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:e19332CrossRefPubMedPubMedCentral 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:e19332CrossRefPubMedPubMedCentral
Zurück zum Zitat 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 80:184–197CrossRefPubMedPubMedCentral 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 80:184–197CrossRefPubMedPubMedCentral
Zurück zum Zitat Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1:1–47CrossRefPubMed Felleman DJ, Van Essen DC (1991) Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex 1:1–47CrossRefPubMed
Zurück zum Zitat Finlay BL (2016) Principles of network architecture emerging from comparisons of the cerebral cortex in large and small brains. PLoS Biol 14:e1002556CrossRefPubMedPubMedCentral Finlay BL (2016) Principles of network architecture emerging from comparisons of the cerebral cortex in large and small brains. PLoS Biol 14:e1002556CrossRefPubMedPubMedCentral
Zurück zum Zitat 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.e10CrossRefPubMedPubMedCentral 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.e10CrossRefPubMedPubMedCentral
Zurück zum Zitat Goulas A, Uylings HBM, Hilgetag CC (2017) Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse. Brain Struct Funct 222:1281–1295CrossRefPubMed Goulas A, Uylings HBM, Hilgetag CC (2017) Principles of ipsilateral and contralateral cortico-cortical connectivity in the mouse. Brain Struct Funct 222:1281–1295CrossRefPubMed
Zurück zum Zitat Hirokawa J, Bosch M, Sakata S, Sakurai Y, Yamamori T (2008a) Functional role of the secondary visual cortex in multisensory facilitation in rats. Neuroscience 153:1402–1417CrossRefPubMed Hirokawa J, Bosch M, Sakata S, Sakurai Y, Yamamori T (2008a) Functional role of the secondary visual cortex in multisensory facilitation in rats. Neuroscience 153:1402–1417CrossRefPubMed
Zurück zum Zitat 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:e3266CrossRefPubMedPubMedCentral 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:e3266CrossRefPubMedPubMedCentral
Zurück zum Zitat 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:e1002512CrossRefPubMedPubMedCentral 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:e1002512CrossRefPubMedPubMedCentral
Zurück zum Zitat Kaas JH (2000) Why is brain size so important: design problems and solutions as neocortex gets bigger or smaller. Brain Mind 1:7–23CrossRef Kaas JH (2000) Why is brain size so important: design problems and solutions as neocortex gets bigger or smaller. Brain Mind 1:7–23CrossRef
Zurück zum Zitat 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.e5CrossRefPubMed 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.e5CrossRefPubMed
Zurück zum Zitat 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 338:360–376CrossRefPubMed 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 338:360–376CrossRefPubMed
Zurück zum Zitat 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 108:541–557CrossRefPubMedPubMedCentral 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 108:541–557CrossRefPubMedPubMedCentral
Zurück zum Zitat Liska A, Galbusera A, Schwarz AJ, Gozzi A (2015) Functional connectivity hubs of the mouse brain. Neuroimage 115:281–291CrossRefPubMed Liska A, Galbusera A, Schwarz AJ, Gozzi A (2015) Functional connectivity hubs of the mouse brain. Neuroimage 115:281–291CrossRefPubMed
Zurück zum Zitat Lund JS, Yoshioka T, Levitt JB (1993) Comparison of intrinsic connectivity in different areas of macaque monkey cerebral cortex. Cereb Cortex 3:148–162CrossRefPubMed Lund JS, Yoshioka T, Levitt JB (1993) Comparison of intrinsic connectivity in different areas of macaque monkey cerebral cortex. Cereb Cortex 3:148–162CrossRefPubMed
Zurück zum Zitat 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 86:1304–1316CrossRefPubMed 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 86:1304–1316CrossRefPubMed
Zurück zum Zitat 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 21:1254–1272CrossRefPubMed 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 21:1254–1272CrossRefPubMed
Zurück zum Zitat 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 522:225–259CrossRefPubMed 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 522:225–259CrossRefPubMed
Zurück zum Zitat 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):17–36CrossRefPubMed 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):17–36CrossRefPubMed
Zurück zum Zitat 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 508:207–214CrossRefPubMedPubMedCentral 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 508:207–214CrossRefPubMedPubMedCentral
Zurück zum Zitat Pakkenberg B, Gundersen HJ (1997) Neocortical neuron number in humans: effect of sex and age. J Comp Neurol 384:312–320CrossRefPubMed Pakkenberg B, Gundersen HJ (1997) Neocortical neuron number in humans: effect of sex and age. J Comp Neurol 384:312–320CrossRefPubMed
Zurück zum Zitat Paxinos G (2014) The rat nervous system, fourth edition. Academic, New York Paxinos G (2014) The rat nervous system, fourth edition. Academic, New York
Zurück zum Zitat Paxinos G, Franklin KBJ (2004) The mouse brain in stereotaxic coordinates. Elsevier, Amsterdam Paxinos G, Franklin KBJ (2004) The mouse brain in stereotaxic coordinates. Elsevier, Amsterdam
Zurück zum Zitat 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 9:255–258CrossRefPubMedPubMedCentral 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 9:255–258CrossRefPubMedPubMedCentral
Zurück zum Zitat Ringo JL (1991) Neuronal interconnection as a function of brain size. Brain Behav Evol 38:1–6CrossRefPubMed Ringo JL (1991) Neuronal interconnection as a function of brain size. Brain Behav Evol 38:1–6CrossRefPubMed
Zurück zum Zitat Rockland KS, Pandya DN (1979) Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey. Brain Res 179:3–20CrossRefPubMed Rockland KS, Pandya DN (1979) Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey. Brain Res 179:3–20CrossRefPubMed
Zurück zum Zitat Schüz A, Chaimow D, Liewald D, Dortenman M (2006) Quantitative aspects of corticocortical connections: a tracer study in the mouse. Cereb Cortex 16:1474–1486CrossRefPubMed Schüz A, Chaimow D, Liewald D, Dortenman M (2006) Quantitative aspects of corticocortical connections: a tracer study in the mouse. Cereb Cortex 16:1474–1486CrossRefPubMed
Zurück zum Zitat 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):60–79CrossRefPubMed 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):60–79CrossRefPubMed
Zurück zum Zitat 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 37:7513–7533CrossRefPubMedPubMedCentral 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 37:7513–7533CrossRefPubMedPubMedCentral
Zurück zum Zitat 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 28:4047–4056CrossRefPubMedPubMedCentral 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 28:4047–4056CrossRefPubMedPubMedCentral
Zurück zum Zitat Wang Q, Sporns O, Burkhalter A (2012) Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. J Neurosci 32:4386–4399CrossRefPubMedPubMedCentral Wang Q, Sporns O, Burkhalter A (2012) Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex. J Neurosci 32:4386–4399CrossRefPubMedPubMedCentral
Zurück zum Zitat 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 520:3553–3573CrossRefPubMed 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 520:3553–3573CrossRefPubMed
Zurück zum Zitat 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 8:110 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 8:110
Zurück zum Zitat 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 17:6365–6379CrossRefPubMedPubMedCentral 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 17:6365–6379CrossRefPubMedPubMedCentral
Zurück zum Zitat Zhang K, Sejnowski TJ (2000) A universal scaling law between gray matter and white matter of cerebral cortex. Proc Natl Acad Sci USA 97:5621–5626CrossRefPubMedPubMedCentral Zhang K, Sejnowski TJ (2000) A universal scaling law between gray matter and white matter of cerebral cortex. Proc Natl Acad Sci USA 97:5621–5626CrossRefPubMedPubMedCentral
Zurück zum Zitat 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 19:1733–1742CrossRefPubMedPubMedCentral 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 19:1733–1742CrossRefPubMedPubMedCentral
Zurück zum Zitat 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 156:1096–1111CrossRefPubMedPubMedCentral 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 156:1096–1111CrossRefPubMedPubMedCentral
Metadaten
Titel
Cortical networks of the mouse brain elaborate within the gray matter
verfasst von
Akiya Watakabe
Junya Hirokawa
Publikationsdatum
09.07.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Brain Structure and Function / Ausgabe 8/2018
Print ISSN: 1863-2653
Elektronische ISSN: 1863-2661
DOI
https://doi.org/10.1007/s00429-018-1710-5

Weitere Artikel der Ausgabe 8/2018

Brain Structure and Function 8/2018 Zur Ausgabe

Leitlinien kompakt für die Neurologie

Mit medbee Pocketcards sicher entscheiden.

Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag

Update Neurologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.