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Cited by 138Neuroscience and Neuropharmacology ResearchVisual perception and processing mechanismsNeural dynamics and brain function

A Laminar Organization for Selective Cortico-Cortical Communication

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D’Souza, Rinaldo D., Burkhalter, Andreas·2017·Frontiers in Neuroanatomy
DOI 10.3389/fnana.2017.00071PMC PMC5572236
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Abstract

The neocortex is central to mammalian cognitive ability, playing critical roles in sensory perception, motor skills and executive function. This thin, layered structure comprises distinct, functionally specialized areas that communicate with each other through the axons of pyramidal neurons. For the hundreds of such cortico-cortical pathways to underlie diverse functions, their cellular and synaptic architectures must differ so that they result in distinct computations at the target projection neurons. In what ways do these pathways differ? By originating and terminating in different laminae, and by selectively targeting specific populations of excitatory and inhibitory neurons, these "interareal" pathways can differentially control the timing and strength of synaptic inputs onto individual neurons, resulting in layer-specific computations. Due to the rapid development in transgenic techniques, the mouse has emerged as a powerful mammalian model for understanding the rules by which cortical circuits organize and function. Here we review our understanding of how cortical lamination constrains long-range communication in the mammalian brain, with an emphasis on the mouse visual cortical network. We discuss the laminar architecture underlying interareal communication, the role of neocortical layers in organizing the balance of excitatory and inhibitory actions, and highlight the structure and function of layer 1 in mouse visual cortex.

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  • Sensory perception is thought to rely on the complex interplay of neural circuits that process information in a cortical layer- and area-mediated manner involving thalamocortical, intracortical, corticocortical, and corticothalamic feedforward/feedback loops.

    “Sensory perception is thought to rely on the complex interplay of neural circuits that process information in a cortical layer- and area-mediated manner involving thalamocortical, intracortical, corticocortical, and corticothalamic feedforward/feedback loops (D’Souza and Burkhalter, 2017).”

    From Perception is associated with the brain’s metabolic response to sensory stimulation (2022) · cites this paper as D’Souza and Burkhalter, 2017

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  1. Alfano C. Studer M. (2013). Neocortical arealization: evolution, mechanisms, and open questions. Dev. Neurobiol. 73, 411– 447. 10.1002/dneu.22067 23239642 · DOI
  2. Amitai Y. Friedman A. Connors B. W. Gutnick M. J. (1993). Regenerative activity in apical dendrites of pyramidal cells in neocortex. Cereb. Cortex 3, 26– 38. 10.1093/cercor/3.1.26 8439739 · DOI
  3. Andermann M. L. Kerlin A. M. Roumis D. K. Glickfeld L. L. Reid R. C. (2011). Functional specialization of mouse higher visual cortical areas. Neuron 72, 1025– 1039. 10.1016/j.neuron.2011.11.013 22196337 PMC3876958 · DOI · Paper page
  4. Antonini A. Fagiolini M. Stryker M. P. (1999). Anatomical correlates of functional plasticity in mouse visual cortex. J. Neurosci. 19, 4388– 4406. 10341241 PMC2452998
  5. Apicella A. J. Wickersham I. R. Seung H. S. Shepherd G. M. (2012). Laminarly orthogonal excitation of fast-spiking and low-threshold-spiking interneurons in mouse motor cortex. J. Neurosci. 32, 7021– 7033. 10.1523/JNEUROSCI.0011-12.2012 22593070 PMC3377057 · DOI
  6. Balaram P. Kaas J. H. (2014). Towards a unified scheme of cortical lamination for primary visual cortex across primates: insights from NeuN and VGLUT2 immunoreactivity. Front. Neuroanat. 8: 81. 10.3389/fnana.2014.00081 25177277 PMC4133926 · DOI
  7. Barone P. Batardiere A. Knoblauch K. Kennedy H. (2000). Laminar distribution of neurons in extrastriate areas projecting to visual areas V1 and V4 correlates with the hierarchical rank and indicates the operation of a distance rule. J. Neurosci. 20, 3263– 3281. 10777791 PMC6773101
  8. Barth A. L. Poulet J. F. (2012). Experimental evidence for sparse firing in the neocortex. Trends Neurosci. 35, 345– 355. 10.1016/j.tins.2012.03.008 22579264 · DOI · Paper page
  9. Bastos A. M. Vezoli J. Bosman C. A. Schoffelen J. M. Oostenveld R. Dowdall J. R.. (2015). Visual areas exert feedforward and feedback influences through distinct frequency channels. Neuron 85, 390– 401. 10.1016/j.neuron.2014.12.018 25556836 · DOI · Paper page
  10. Belgard T. G. Marques A. C. Oliver P. L. Abaan H. O. Sirey T. M. Hoerder-Suabedissen A.. (2011). A transcriptomic atlas of mouse neocortical layers. Neuron 71, 605– 616. 10.1016/j.neuron.2011.06.039 21867878 PMC3163272 · DOI
  11. Benavides-Piccione R. Hamzei-Sichani F. Ballesteros-Yanez I. DeFelipe J. Yuste R. (2006). Dendritic size of pyramidal neurons differs among mouse cortical regions. Cereb. Cortex 16, 990– 1001. 10.1093/cercor/bhj041 16195469 · DOI
  12. Berezovskii V. K. Nassi J. J. Born R. T. (2011). Segregation of feedforward and feedback projections in mouse visual cortex. J. Comp. Neurol. 519, 3672– 3683. 10.1002/cne.22675 21618232 PMC3219532 · DOI · Paper page
  13. Binzegger T. Douglas R. J. Martin K. A. (2004). A quantitative map of the circuit of cat primary visual cortex. J. Neurosci. 24, 8441– 8453. 10.1523/JNEUROSCI.1400-04.2004 15456817 PMC6729898 · DOI
  14. Bourassa J. Deschênes M. (1995). Corticothalamic projections from the primary visual cortex in rats: a single fiber study using biocytin as an anterograde tracer. Neuroscience 66, 253– 263. 10.1016/0306-4522(95)00009-8 7477870 · DOI
  15. Bourassa J. Pinault D. Deschênes M. (1995). Corticothalamic projections from the cortical barrel field to the somatosensory thalamus in rats: a single-fibre study using biocytin as an anterograde tracer. Eur. J. Neurosci. 7, 19– 30. 10.1111/j.1460-9568.1995.tb01016.x 7711933 · DOI
  16. Bruno R. M. (2011). Synchrony in sensation. Curr. Opin. Neurobiol. 21, 701– 708. 10.1016/j.conb.2011.06.003 21723114 PMC3191231 · DOI
  17. Buffalo E. A. Fries P. Landman R. Buschman T. J. Desimone R. (2011). Laminar differences in γ and α coherence in the ventral stream. Proc. Natl. Acad. Sci. U S A 108, 11262– 11267. 10.1073/pnas.1011284108 21690410 PMC3131344 · DOI · Paper page
  18. Cardin J. A. Carlén M. Meletis K. Knoblich U. Zhang F. Deisseroth K.. (2009). Driving fast-spiking cells induces γ rhythm and controls sensory responses. Nature 459, 663– 667. 10.1038/nature08002 19396156 PMC3655711 · DOI · Paper page
  19. Cauller L. (1995). Layer I of primary sensory neocortex: where top-down converges upon bottom-up. Behav. Brain Res. 71, 163– 170. 10.1016/0166-4328(95)00032-1 8747184 · DOI
  20. Chance F. S. Abbott L. F. Reyes A. D. (2002). Gain modulation from background synaptic input. Neuron 35, 773– 782. 10.1016/s0896-6273(02)00820-6 12194875 · DOI · Paper page
  21. Chattopadhyaya B. Di Cristo G. Higashiyama H. Knott G. W. Kuhlman S. J. Welker E.. (2004). Experience and activity-dependent maturation of perisomatic GABAergic innervation in primary visual cortex during a postnatal critical period. J. Neurosci. 24, 9598– 9611. 10.1523/JNEUROSCI.1851-04.2004 15509747 PMC6730138 · DOI · Paper page
  22. Chaudhuri R. Knoblauch K. Gariel M. A. Kennedy H. Wang X. J. (2015). A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex. Neuron 88, 419– 431. 10.1016/j.neuron.2015.09.008 26439530 PMC4630024 · DOI
  23. Chen M. Yan Y. Gong X. Gilbert C. D. Liang H. Li W. (2014). Incremental integration of global contours through interplay between visual cortical areas. Neuron 82, 682– 694. 10.1016/j.neuron.2014.03.023 24811385 · DOI
  24. Coogan T. A. Burkhalter A. (1990). Conserved patterns of cortico-cortical connections define areal hierarchy in rat visual cortex. Exp. Brain Res. 80, 49– 53. 10.1007/bf00228846 2358036 · DOI
  25. Coogan T. A. Burkhalter A. (1993). Hierarchical organization of areas in rat visual cortex. J. Neurosci. 13, 3749– 3772. 7690066 PMC6576464
  26. Cossell L. Iacaruso M. F. Muir D. R. Houlton R. Sader E. N. Ko H.. (2015). Functional organization of excitatory synaptic strength in primary visual cortex. Nature 518, 399– 403. 10.1038/nature14182 25652823 PMC4843963 · DOI
  27. Covic E. N. Sherman S. M. (2011). Synaptic properties of connections between the primary and secondary auditory cortices in mice. Cereb. Cortex 21, 2425– 2441. 10.1093/cercor/bhr029 21385835 PMC3183423 · DOI · Paper page
  28. Crochet S. Poulet J. F. Kremer Y. Petersen C. C. (2011). Synaptic mechanisms underlying sparse coding of active touch. Neuron 69, 1160– 1175. 10.1016/j.neuron.2011.02.022 21435560 · DOI
  29. Cruikshank S. J. Ahmed O. J. Stevens T. R. Patrick S. L. Gonzalez A. N. Elmaleh M.. (2012). Thalamic control of layer 1 circuits in prefrontal cortex. J. Neurosci. 32, 17813– 17823. 10.1523/JNEUROSCI.3231-12.2012 23223300 PMC3535493 · DOI · Paper page
  30. Cruz-Martín A. El-Danaf R. N. Osakada F. Sriram B. Dhande O. S. Nguyen P. L.. (2014). A dedicated circuit links direction-selective retinal ganglion cells to the primary visual cortex. Nature 507, 358– 361. 10.1038/nature12989 24572358 PMC4143386 · DOI
  31. DeFelipe J. Fariñas I. (1992). The pyramidal neuron of the cerebral cortex: morphological and chemical characteristics of the synaptic inputs. Prog. Neurobiol. 39, 563– 607. 10.1016/0301-0082(92)90015-7 1410442 · DOI · Paper page
  32. De Pasquale R. Sherman S. M. (2011). Synaptic properties of corticocortical connections between the primary and secondary visual cortical areas in the mouse. J. Neurosci. 31, 16494– 16506. 10.1523/JNEUROSCI.3664-11.2011 22090476 PMC3233982 · DOI · Paper page
  33. Deschênes M. Bourassa J. Pinault D. (1994). Corticothalamic projections from layer V cells in rat are collaterals of long-range corticofugal axons. Brain Res. 664, 215– 219. 10.1016/0006-8993(94)91974-7 7895031 · DOI
  34. Douglas R. J. Koch C. Mahowald M. Martin K. A. Suarez H. H. (1995). Recurrent excitation in neocortical circuits. Science 269, 981– 985. 10.1126/science.7638624 7638624 · DOI
  35. Douglas R. J. Martin K. A. (1991). A functional microcircuit for cat visual cortex. J. Physiol. 440, 735– 769. 10.1113/jphysiol.1991.sp018733 1666655 PMC1180177 · DOI · Paper page
  36. Douglas R. J. Martin K. A. (2004). Neuronal circuits of the neocortex. Annu. Rev. Neurosci. 27, 419– 451. 10.1146/annurev.neuro.27.070203.144152 15217339 · DOI · Paper page
  37. Douglas R. J. Martin K. A. (2007). Recurrent neuronal circuits in the neocortex. Curr. Biol. 17, R496– R500. 10.1016/j.cub.2007.04.024 17610826 · DOI
  38. Douglas R. J. Martin K. A. (2009). Inhibition in cortical circuits. Curr. Biol. 19, R398– R402. 10.1016/j.cub.2009.03.003 19467204 · DOI
  39. D’Souza R. D. Meier A. M. 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: e19332. 10.7554/eLife.19332 27669144 PMC5074802 · DOI · Paper page
  40. Elston G. N. (2003). Cortex, cognition and the cell: new insights into the pyramidal neuron and prefrontal function. Cereb. Cortex 13, 1124– 1138. 10.1093/cercor/bhg093 14576205 · DOI · Paper page
  41. Elston G. N. Elston A. Aurelio-Freire M. Gomes Leal W. Dias I. A. Pereira A.. (2006). Specialization of pyramidal cell structure in the visual areas V1, V2 and V3 of the South American rodent, Dasyprocta primnolopha. Brain Res. 1106, 99– 110. 10.1016/j.brainres.2006.05.100 16854386 · DOI
  42. Elston G. N. Oga T. Fujita I. (2009). Spinogenesis and pruning scales across functional hierarchies. J. Neurosci. 29, 3271– 3275. 10.1523/JNEUROSCI.5216-08.2009 19279264 PMC6666449 · DOI
  43. Erisken S. Vaiceliunaite A. Jurjut O. Fiorini M. Katzner S. Busse L. (2014). Effects of locomotion extend throughout the mouse early visual system. Curr. Biol. 24, 2899– 2907. 10.1016/j.cub.2014.10.045 25484299 · DOI · Paper page
  44. Feldmeyer D. Qi G. Emmenegger V. Staiger J. F. (2017). Inhibitory interneurons and their circuit motifs in the many layers of the barrel cortex. Neuroscience [Epub ahead of print]. 10.1016/j.neuroscience.2017.05.027 28528964 · DOI
  45. Felleman D. J. Van Essen D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1, 1– 47. 10.1093/cercor/1.1.1 1822724 · DOI · Paper page
  46. Garrett M. E. Nauhaus I. Marshel J. H. Callaway E. M. (2014). Topography and areal organization of mouse visual cortex. J. Neurosci. 34, 12587– 12600. 10.1523/JNEUROSCI.1124-14.2014 25209296 PMC4160785 · DOI
  47. Gentet L. J. Kremer Y. Taniguchi H. Huang Z. J. Staiger J. F. Petersen C. C. (2012). Unique functional properties of somatostatin-expressing GABAergic neurons in mouse barrel cortex. Nat. Neurosci. 15, 607– 612. 10.1038/nn.3051 22366760 · DOI · Paper page
  48. Gilman J. P. Medalla M. Luebke J. I. (2017). Area-specific features of pyramidal neurons-a comparative study in mouse and rhesus monkey. Cereb. Cortex 27, 2078– 2094. 10.1093/cercor/bhw062 26965903 PMC6059164 · DOI
  49. Gonchar Y. Burkhalter A. (1999). Differential subcellular localization of forward and feedback interareal inputs to parvalbumin expressing GABAergic neurons in rat visual cortex. J. Comp. Neurol. 406, 346– 360. 10.1002/(sici)1096-9861(19990412)406:3<346::aid-cne4>3.0.co;2-e 10102500 · DOI
  50. Gonchar Y. Burkhalter A. (2003). Distinct GABAergic targets of feedforward and feedback connections between lower and higher areas of rat visual cortex. J. Neurosci. 23, 10904– 10912. 14645486 PMC6740993
  51. Grieve K. L. Acuña C. Cudeiro J. (2000). The primate pulvinar nuclei: vision and action. Trends Neurosci. 23, 35– 39. 10.1016/s0166-2236(99)01482-4 10631787 · DOI
  52. Groh A. Meyer H. S. Schmidt E. F. Heintz N. Sakmann B. Krieger P. (2010). Cell-type specific properties of pyramidal neurons in neocortex underlying a layout that is modifiable depending on the cortical area. Cereb. Cortex 20, 826– 836. 10.1093/cercor/bhp152 19643810 · DOI
  53. Haider B. Häusser M. Carandini M. (2013). Inhibition dominates sensory responses in the awake cortex. Nature 493, 97– 100. 10.1038/nature11665 23172139 PMC3537822 · DOI
  54. Harris K. D. Mrsic-Flogel T. D. (2013). Cortical connectivity and sensory coding. Nature 503, 51– 58. 10.1038/nature12654 24201278 · DOI
  55. Harris K. D. Shepherd G. M. (2015). The neocortical circuit: themes and variations. Nat. Neurosci. 18, 170– 181. 10.1038/nn.3917 25622573 PMC4889215 · DOI · Paper page
  56. Hasenstaub A. Shu Y. Haider B. Kraushaar U. Duque A. McCormick D. A. (2005). Inhibitory postsynaptic potentials carry synchronized frequency information in active cortical networks. Neuron 47, 423– 435. 10.1016/j.neuron.2005.06.016 16055065 · DOI
  57. Havekes R. Abel T. (2009). Genetic dissection of neural circuits and behavior in Mus musculus. Adv. Genet. 65, 1– 38. 10.1016/s0065-2660(09)65001-x 19615530 PMC2861997 · DOI
  58. Hestrin S. Armstrong W. E. (1996). Morphology and physiology of cortical neurons in layer I. J. Neurosci. 16, 5290– 5300. 8757242 PMC6578880
  59. Hooks B. M. Mao T. Gutnisky D. A. Yamawaki N. Svoboda K. Shepherd G. M. (2013). Organization of cortical and thalamic input to pyramidal neurons in mouse motor cortex. J. Neurosci. 33, 748– 760. 10.1523/JNEUROSCI.4338-12.2013 23303952 PMC3710148 · DOI
  60. Hubel D. H. Wiesel T. N. (1968). Receptive fields and functional architecture of monkey striate cortex. J. Physiol. 195, 215– 243. 10.1113/jphysiol.1968.sp008455 4966457 PMC1557912 · DOI
  61. Huberman A. D. Niell C. M. (2011). What can mice tell us about how vision works? Trends Neurosci. 34, 464– 473. 10.1016/j.tins.2011.07.002 21840069 PMC3371366 · DOI
  62. Ichinohe N. Fujiyama F. Kaneko T. Rockland K. S. (2003). Honeycomb-like mosaic at the border of layers 1 and 2 in the cerebral cortex. J. Neurosci. 23, 1372– 1382. 12598625 PMC6742255
  63. Ichinohe N. Rockland K. S. (2002). Parvalbumin positive dendrites co-localize with apical dendritic bundles in rat retrosplenial cortex. Neuroreport 13, 757– 761. 10.1097/00001756-200205070-00005 11997682 · DOI
  64. Isaacson J. S. Scanziani M. (2011). How inhibition shapes cortical activity. Neuron 72, 231– 243. 10.1016/j.neuron.2011.09.027 22017986 PMC3236361 · DOI · Paper page
  65. Jackson J. Ayzenshtat I. Karnani M. M. Yuste R. (2016). VIP+ interneurons control neocortical activity across brain states. J. Neurophysiol. 115, 3008– 3017. 10.1152/jn.01124.2015 26961109 PMC4946593 · DOI
  66. Ji W. Gamanut R. Bista P. D’Souza R. D. Wang Q. Burkhalter A. (2015). Modularity in the organization of mouse primary visual cortex. Neuron 87, 632– 643. 10.1016/j.neuron.2015.07.004 26247867 PMC4529541 · DOI
  67. Jiang X. Shen S. Cadwell C. R. Berens P. Sinz F. Ecker A. S.. (2015). Principles of connectivity among morphologically defined cell types in adult neocortex. Science 350: aac9462. 10.1126/science.aac9462 26612957 PMC4809866 · DOI · Paper page
  68. Kaas J. H. (2013). The evolution of brains from early mammals to humans. Wiley Interdiscip. Rev. Cogn. Sci. 4, 33– 45. 10.1002/wcs.1206 23529256 PMC3606080 · DOI
  69. Kapfer C. Glickfeld L. L. Atallah B. V. Scanziani M. (2007). Supralinear increase of recurrent inhibition during sparse activity in the somatosensory cortex. Nat. Neurosci. 10, 743– 753. 10.1038/nn0807-1073b 17515899 PMC3518866 · DOI
  70. Katzner S. Weigelt S. (2013). Visual cortical networks: of mice and men. Curr. Opin. Neurobiol. 23, 202– 206. 10.1016/j.conb.2013.01.019 23415830 · DOI
  71. Kawaguchi Y. Kondo S. (2002). Parvalbumin, somatostatin and cholecystokinin as chemical markers for specific GABAergic interneuron types in the rat frontal cortex. J. Neurocytol. 31, 277– 287. 10.1023/A:1024126110356 12815247 · DOI · Paper page
  72. Kita T. Kita H. (2012). The subthalamic nucleus is one of multiple innervation sites for long-range corticofugal axons: a single-axon tracing study in the rat. J. Neurosci. 32, 5990– 5999. 10.1523/JNEUROSCI.5717-11.2012 22539859 PMC3479642 · DOI
  73. Ko H. Hofer S. B. Pichler B. Buchanan K. A. Sjöström P. J. Mrsic-Flogel T. D. (2011). Functional specificity of local synaptic connections in neocortical networks. Nature 473, 87– 91. 10.1038/nature09880 21478872 PMC3089591 · DOI
  74. Kremkow J. Perrinet L. U. Masson G. S. Aertsen A. (2010). Functional consequences of correlated excitatory and inhibitory conductances in cortical networks. J. Comput. Neurosci. 28, 579– 594. 10.1007/s10827-010-0240-9 20490645 · DOI
  75. Kuchibhotla K. V. Gill J. V. Lindsay G. W. Papadoyannis E. S. Field R. E. Sten T. A.. (2017). Parallel processing by cortical inhibition enables context-dependent behavior. Nat. Neurosci. 20, 62– 71. 10.1038/nn.4436 27798631 PMC5191967 · DOI
  76. Laramée M.-E. Boire D. (2014). Visual cortical areas of the mouse: comparison of parcellation and network structure with primates. Front. Neural Circuits 8: 149. 10.3389/fncir.2014.00149 25620914 PMC4286719 · DOI
  77. Larkum M. (2013). A cellular mechanism for cortical associations: an organizing principle for the cerebral cortex. Trends Neurosci. 36, 141– 151. 10.1016/j.tins.2012.11.006 23273272 · DOI · Paper page
  78. Larkum M. E. (2013). The yin and yang of cortical layer 1. Nat. Neurosci. 16, 114– 115. 10.1038/nn.3317 23354381 · DOI
  79. Larkum M. E. Senn W. Lüscher H. R. (2004). Top-down dendritic input increases the gain of layer 5 pyramidal neurons. Cereb. Cortex 14, 1059– 1070. 10.1093/cercor/bhh065 15115747 · DOI · Paper page
  80. Larkum M. E. Zhu J. J. (2002). Signaling of layer 1 and whisker-evoked Ca2+ and Na+ action potentials in distal and terminal dendrites of rat neocortical pyramidal neurons in vitro and in vivo. J. Neurosci. 22, 6991– 7005. 12177197 PMC6757874
  81. Larkum M. E. Zhu J. J. Sakmann B. (2001). Dendritic mechanisms underlying the coupling of the dendritic with the axonal action potential initiation zone of adult rat layer 5 pyramidal neurons. J. Physiol. 533, 447– 466. 10.1111/j.1469-7793.2001.0447a.x 11389204 PMC2278642 · DOI
  82. Lee S. Kruglikov I. Huang Z. J. Fishell G. Rudy B. (2013). A disinhibitory circuit mediates motor integration in the somatosensory cortex. Nat. Neurosci. 16, 1662– 1670. 10.1038/nn.3544 24097044 PMC4100076 · DOI · Paper page
  83. Lee A. J. Wang G. Jiang X. Johnson S. M. Hoang E. T. Lante F.. (2015). Canonical organization of layer 1 neuron-led cortical inhibitory and disinhibitory interneuronal circuits. Cereb. Cortex 25, 2114– 2126. 10.1093/cercor/bhu020 24554728 PMC4494026 · DOI · Paper page
  84. Lien A. D. Scanziani M. (2013). Tuned thalamic excitation is amplified by visual cortical circuits. Nat. Neurosci. 16, 1315– 1323. 10.1038/nn.3488 23933748 PMC3774518 · DOI
  85. Livingstone M. S. Hubel D. H. (1984). Anatomy and physiology of a color system in the primate visual cortex. J. Neurosci. 4, 309– 356. 6198495 PMC6564760
  86. Lui J. H. Hansen D. V. Kriegstein A. R. (2011). Development and evolution of the human neocortex. Cell 146, 18– 36. 10.1016/j.cell.2011.07.005 21729779 PMC3610574 · DOI
  87. Major G. Larkum M. E. Schiller J. (2013). Active properties of neocortical pyramidal neuron dendrites. Annu. Rev. Neurosci. 36, 1– 24. 10.1146/annurev-neuro-062111-150343 23841837 · DOI · Paper page
  88. Markov N. T. Kennedy H. (2013). The importance of being hierarchical. Curr. Opin. Neurobiol. 23, 187– 194. 10.1016/j.conb.2012.12.008 23339864 · DOI · Paper page
  89. Marshel J. H. Garrett M. E. Nauhaus I. Callaway E. M. (2011). Functional specialization of seven mouse visual cortical areas. Neuron 72, 1040– 1054. 10.1016/j.neuron.2011.12.004 22196338 PMC3248795 · DOI
  90. Maunsell J. H. van Essen D. C. (1987). Topographic organization of the middle temporal visual area in the macaque monkey: representational biases and the relationship to callosal connections and myeloarchitectonic boundaries. J. Comp. Neurol. 266, 535– 555. 10.1002/cne.902660407 2449473 · DOI
  91. Michalareas G. Vezoli J. van Pelt S. Schoffelen J. M. Kennedy H. Fries P. (2016). Alpha-beta and gamma rhythms subserve feedback and feedforward influences among human visual cortical areas. Neuron 89, 384– 397. 10.1016/j.neuron.2015.12.018 26777277 PMC4871751 · DOI · Paper page
  92. Muñoz W. Tremblay R. Levenstein D. Rudy B. (2017). Layer-specific modulation of neocortical dendritic inhibition during active wakefulness. Science 355, 954– 959. 10.1126/science.aag2599 28254942 · DOI · Paper page
  93. Muralidhar S. Wang Y. Markram H. (2013). Synaptic and cellular organization of layer 1 of the developing rat somatosensory cortex. Front. Neuroanat. 7: 52. 10.3389/fnana.2013.00052 24474905 PMC3893566 · DOI
  94. Murray J. D. Bernacchia A. Freedman D. J. Romo R. Wallis J. D. Cai X.. (2014). A hierarchy of intrinsic timescales across primate cortex. Nat. Neurosci. 17, 1661– 1663. 10.1038/nn.3862 25383900 PMC4241138 · DOI · Paper page
  95. Nandy A. S. Nassi J. J. Reynolds J. H. (2017). Laminar organization of attentional modulation in macaque visual area V4. Neuron 93, 235– 246. 10.1016/j.neuron.2016.11.029 27989456 PMC5217483 · DOI
  96. Nassi J. J. Callaway E. M. (2009). Parallel processing strategies of the primate visual system. Nat. Rev. Neurosci. 10, 360– 372. 10.1038/nrn2619 19352403 PMC2771435 · DOI · Paper page
  97. Niell C. M. Stryker M. P. (2008). Highly selective receptive fields in mouse visual cortex. J. Neurosci. 28, 7520– 7536. 10.1523/jneurosci.0623-08.2008 18650330 PMC3040721 · DOI · Paper page
  98. O’Connor D. H. Peron S. P. Huber D. Svoboda K. (2010). Neural activity in barrel cortex underlying vibrissa-based object localization in mice. Neuron 67, 1048– 1061. 10.1016/j.neuron.2010.08.026 20869600 · DOI
  99. Oh S. W. Harris J. A. Ng L. Winslow B. Cain N. Mihalas S.. (2014). A mesoscale connectome of the mouse brain. Nature 508, 207– 214. 10.1038/nature13186 24695228 PMC5102064 · DOI · Paper page
  100. Ohki K. Chung S. Ch’ng Y. H. Kara P. Reid R. C. (2005). Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597– 603. 10.1038/nature03274 15660108 · DOI
  101. Okun M. Lampl I. (2008). Instantaneous correlation of excitation and inhibition during ongoing and sensory-evoked activities. Nat. Neurosci. 11, 535– 537. 10.1038/nn.2105 18376400 · DOI
  102. Pafundo D. E. Nicholas M. A. Zhang R. Kuhlman S. J. (2016). Top-down-mediated facilitation in the visual cortex is gated by subcortical neuromodulation. J. Neurosci. 36, 2904– 2914. 10.1523/jneurosci.2909-15.2016 26961946 PMC4783494 · DOI
  103. Palmer L. Murayama M. Larkum M. (2012). Inhibitory regulation of dendritic activity in vivo. Front. Neural Circuits 6: 26. 10.3389/fncir.2012.00026 22654734 PMC3360463 · DOI
  104. Petersen C. C. Crochet S. (2013). Synaptic computation and sensory processing in neocortical layer 2/3. Neuron 78, 28– 48. 10.1016/j.neuron.2013.03.020 23583106 · DOI
  105. Pfeffer C. K. Xue M. He M. Huang Z. J. Scanziani M. (2013). Inhibition of inhibition in visual cortex: the logic of connections between molecularly distinct interneurons. Nat. Neurosci. 16, 1068– 1076. 10.1038/nn.3446 23817549 PMC3729586 · DOI · Paper page
  106. Phillips W. A. (2017). Cognitive functions of intracellular mechanisms for contextual amplification. Brain Cogn. 112, 39– 53. 10.1016/j.bandc.2015.09.005 26428863 · DOI · Paper page
  107. Pi H. J. Hangya B. Kvitsiani D. Sanders J. I. Huang Z. J. Kepecs A. (2013). Cortical interneurons that specialize in disinhibitory control. Nature 503, 521– 524. 10.1038/nature12676 24097352 PMC4017628 · DOI · Paper page
  108. Pinto D. J. Hartings J. A. Brumberg J. C. Simons D. J. (2003). Cortical damping: analysis of thalamocortical response transformations in rodent barrel cortex. Cereb. Cortex 13, 33– 44. 10.1093/cercor/13.1.33 12466213 · DOI · Paper page
  109. Polack P. O. Friedman J. Golshani P. (2013). Cellular mechanisms of brain state-dependent gain modulation in visual cortex. Nat. Neurosci. 16, 1331– 1339. 10.1038/nn.3464 23872595 PMC3786578 · DOI · Paper page
  110. Pouille F. Scanziani M. (2001). Enforcement of temporal fidelity in pyramidal cells by somatic feed-forward inhibition. Science 293, 1159– 1163. 10.1126/science.1060342 11498596 · DOI · Paper page
  111. Price D. J. Zumbroich T. J. (1989). Postnatal development of corticocortical efferents from area 17 in the cat’s visual cortex. J. Neurosci. 9, 600– 613. 2918380 PMC6569794
  112. Ray S. Naumann R. Burgalossi A. Tang Q. Schmidt H. Brecht M. (2014). Grid-layout and theta-modulation of layer 2 pyramidal neurons in medial entorhinal cortex. Science 343, 891– 896. 10.1126/science.1243028 24457213 · DOI
  113. Roberts M. J. Lowet E. Brunet N. M. Ter Wal M. Tiesinga P. Fries P.. (2013). Robust γ coherence between macaque V1 and V2 by dynamic frequency matching. Neuron 78, 523– 536. 10.1016/j.neuron.2013.03.003 23664617 · DOI
  114. Rockland K. S. Pandya D. N. (1979). Laminar origins and terminations of cortical connections of the occipital lobe in the rhesus monkey. Brain Res. 179, 3– 20. 10.1016/0006-8993(79)90485-2 116716 · DOI
  115. Roth M. M. Dahmen J. C. Muir D. R. Imhof F. Martini F. J. Hofer S. B. (2016). Thalamic nuclei convey diverse contextual information to layer 1 of visual cortex. Nat. Neurosci. 19, 299– 307. 10.1038/nn.4197 26691828 PMC5480596 · DOI
  116. Rubio-Garrido P. Pérez-de-Manzo F. Porrero C. Galazo M. J. Clascá F. (2009). Thalamic input to distal apical dendrites in neocortical layer 1 is massive and highly convergent. Cereb. Cortex 19, 2380– 2395. 10.1093/cercor/bhn259 19188274 · DOI
  117. Rudy B. Fishell G. Lee S. Hjerling-Leffler J. (2011). Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons. Dev. Neurobiol. 71, 45– 61. 10.1002/dneu.20853 21154909 PMC3556905 · DOI · Paper page
  118. Rutishauser U. Slotine J. J. Douglas R. (2015). Computation in dynamically bounded asymmetric systems. PLoS Comput. Biol. 11: e1004039. 10.1371/journal.pcbi.1004039 25617645 PMC4305289 · DOI
  119. Sakata S. Harris K. D. (2009). Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex. Neuron 64, 404– 418. 10.1016/j.neuron.2009.09.020 19914188 PMC2778614 · DOI
  120. Saleem A. B. Ayaz A. Jeffery K. J. Harris K. D. Carandini M. (2013). Integration of visual motion and locomotion in mouse visual cortex. Nat. Neurosci. 16, 1864– 1869. 10.1038/nn.3567 24185423 PMC3926520 · DOI
  121. Saleem A. B. Lien A. D. Krumin M. Haider B. Rosón M. R. Ayaz A.. (2017). Subcortical source and modulation of the narrowband γ oscillation in mouse visual cortex. Neuron 93, 315– 322. 10.1016/j.neuron.2016.12.028 28103479 PMC5263254 · DOI
  122. Sanchez-Vives M. V. McCormick D. A. (2000). Cellular and network mechanisms of rhythmic recurrent activity in neocortex. Nat. Neurosci. 3, 1027– 1034. 10.1038/79848 11017176 · DOI · Paper page
  123. Schiller J. Schiller Y. Stuart G. Sakmann B. (1997). Calcium action potentials restricted to distal apical dendrites of rat neocortical pyramidal neurons. J. Physiol. 505, 605– 616. 10.1111/j.1469-7793.1997.605ba.x 9457639 PMC1160039 · DOI
  124. Shadlen M. N. Newsome W. T. (1998). The variable discharge of cortical neurons: implications for connectivity, computation, and information coding. J. Neurosci. 18, 3870– 3896. 9570816 PMC6793166
  125. Shepherd G. M. (2013). Corticostriatal connectivity and its role in disease. Nat. Rev. Neurosci. 14, 278– 291. 10.1038/nrn3469 23511908 PMC4096337 · DOI · Paper page
  126. Sherman S. M. (2017). Functioning of circuits connecting thalamus and cortex. Compr. Physiol. 7, 713– 739. 10.1002/cphy.c160032 28333385 · DOI
  127. Sherman S. M. Guillery R. W. (1996). Functional organization of thalamocortical relays. J. Neurophysiol. 76, 1367– 1395. 8890259
  128. Sherman S. M. Guillery R. W. (2011). Distinct functions for direct and transthalamic corticocortical connections. J. Neurophysiol. 106, 1068– 1077. 10.1152/jn.00429.2011 21676936 · DOI · Paper page
  129. Shipp S. (2007). Structure and function of the cerebral cortex. Curr. Biol. 17, R443– R449. 10.1016/j.cub.2007.03.044 17580069 · DOI · Paper page
  130. Shipp S. (2016). Neural elements for predictive coding. Front. Psychol. 7: 1792. 10.3389/fpsyg.2016.01792 27917138 PMC5114244 · DOI · Paper page
  131. Silberberg G. Markram H. (2007). Disynaptic inhibition between neocortical pyramidal cells mediated by Martinotti cells. Neuron 53, 735– 746. 10.1016/j.neuron.2007.02.012 17329212 · DOI · Paper page
  132. Sincich L. C. Horton J. C. (2003). Independent projection streams from macaque striate cortex to the second visual area and middle temporal area. J. Neurosci. 23, 5684– 5692. 12843271 PMC6741268
  133. Sorensen S. A. Bernard A. Menon V. Royall J. J. Glattfelder K. J. Desta T.. (2015). Correlated gene expression and target specificity demonstrate excitatory projection neuron diversity. Cereb. Cortex 25, 433– 449. 10.1093/cercor/bht243 24014670 · DOI · Paper page
  134. Spruston N. (2008). Pyramidal neurons: dendritic structure and synaptic integration. Nat. Rev. Neurosci. 9, 206– 221. 10.1038/nrn2286 18270515 · DOI · Paper page
  135. Stuart G. Spruston N. (1998). Determinants of voltage attenuation in neocortical pyramidal neuron dendrites. J. Neurosci. 18, 3501– 3510. 9570781 PMC6793161
  136. Takahashi N. Oertner T. G. Hegemann P. Larkum M. E. (2016). Active cortical dendrites modulate perception. Science 354, 1587– 1590. 10.1126/science.aah6066 28008068 · DOI · Paper page
  137. Thomson A. M. Bannister A. P. (2003). Interlaminar connections in the neocortex. Cereb. Cortex 13, 5– 14. 10.1093/cercor/13.1.5 12466210 · DOI
  138. Timofeev I. Grenier F. Bazhenov M. Sejnowski T. J. Steriade M. (2000). Origin of slow cortical oscillations in deafferented cortical slabs. Cereb. Cortex 10, 1185– 1199. 10.1093/cercor/10.12.1185 11073868 · DOI · Paper page
  139. Tohmi M. Meguro R. Tsukano H. Hishida R. Shibuki K. (2014). The extrageniculate visual pathway generates distinct response properties in the higher visual areas of mice. Curr. Biol. 24, 587– 597. 10.1016/j.cub.2014.01.061 24583013 · DOI
  140. Treisman A. (1996). The binding problem. Curr. Opin. Neurobiol. 6, 171– 178. 10.1016/S0959-4388(96)80070-5 8725958 · DOI
  141. Vaiceliunaite A. Erisken S. Franzen F. Katzner S. Busse L. (2013). Spatial integration in mouse primary visual cortex. J. Neurophysiol. 110, 964– 972. 10.1152/jn.00138.2013 23719206 PMC3742980 · DOI
  142. Wang Q. Burkhalter A. (2007). Area map of mouse visual cortex. J. Comp. Neurol. 502, 339– 357. 10.1002/cne.21286 17366604 · DOI
  143. Wehr M. Zador A. M. (2003). Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature 426, 442– 446. 10.1038/nature02116 14647382 · DOI
  144. Whitmire C. J. Stanley G. B. (2016). Rapid sensory adaptation redux: a circuit perspective. Neuron 92, 298– 315. 10.1016/j.neuron.2016.09.046 27764664 PMC5076890 · DOI
  145. Williams S. R. Stuart G. J. (2002). Dependence of EPSP efficacy on synapse location in neocortical pyramidal neurons. Science 295, 1907– 1910. 10.1126/science.1067903 11884759 · DOI
  146. Wilson N. R. Runyan C. A. Wang F. L. Sur M. (2012). Division and subtraction by distinct cortical inhibitory networks in vivo. Nature 488, 343– 348. 10.1038/nature11347 22878717 PMC3653570 · DOI · Paper page
  147. Wurtz R. H. McAlonan K. Cavanaugh J. Berman R. A. (2011). Thalamic pathways for active vision. Trends Cogn. Sci. 15, 177– 184. 10.1016/j.tics.2011.02.004 21414835 PMC3070860 · DOI · Paper page
  148. Xu X. Olivas N. D. Ikrar T. Peng T. Holmes T. C. Nie Q.. (2016). Primary visual cortex shows laminar-specific and balanced circuit organization of excitatory and inhibitory synaptic connectivity. J. Physiol. 594, 1891– 1910. 10.1113/jp271891 26844927 PMC4818606 · DOI · Paper page
  149. Xue M. Atallah B. V. Scanziani M. (2014). Equalizing excitation-inhibition ratios across visual cortical neurons. Nature 511, 596– 600. 10.1038/nature13321 25043046 PMC4117808 · DOI · Paper page
  150. Yang W. Carrasquillo Y. Hooks B. M. Nerbonne J. M. Burkhalter A. (2013). Distinct balance of excitation and inhibition in an interareal feedforward and feedback circuit of mouse visual cortex. J. Neurosci. 33, 17373– 17384. 10.1523/jneurosci.2515-13.2013 24174670 PMC3812505 · DOI
  151. Yoshimura Y. Callaway E. M. (2005). Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity. Nat. Neurosci. 8, 1552– 1559. 10.1038/nn1565 16222228 · DOI · Paper page
  152. Yuste R. Gutnick M. J. Saar D. Delaney K. R. Tank D. W. (1994). Ca2+ accumulations in dendrites of neocortical pyramidal neurons: an apical band and evidence for two functional compartments. Neuron 13, 23– 43. 10.1016/0896-6273(94)90457-x 8043278 · DOI
  153. Zeisel A. Muñoz-Manchado A. B. Codeluppi S. Lönnerberg P. La Manno G. Juréus A.. (2015). Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138– 1142. 10.1126/science.aaa1934 25700174 · DOI · Paper page
  154. Zhang S. Xu M. Kamigaki T. Hoang Do J. P. Chang W. C. Jenvay S.. (2014). Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing. Science 345, 660– 665. 10.1126/science.1254126 25104383 PMC5776147 · DOI · Paper page
  155. Zhou M. Liang F. Xiong X. R. Li L. Li H. Xiao Z.. (2014). Scaling down of balanced excitation and inhibition by active behavioral states in auditory cortex. Nat. Neurosci. 17, 841– 850. 10.1038/nn.3701 24747575 PMC4108079 · DOI
  156. Zhuang J. Ng L. Williams D. Valley M. Li Y. Garrett M.. (2017). An extended retinotopic map of mouse cortex. Elife 6: e18372. 10.7554/eLife.18372 28059700 PMC5218535 · DOI

Authors
D’Souza, R. D., & Burkhalter, A.
Affiliations
Washington University in St. Louis (US)
Corresponding author
D’Souza, Rinaldo D.
ORCID
Venue
Frontiers in Neuroanatomy
Publisher
Frontiers Media SA
Published
2017-08-22
Volume
11
Pages
71-71
ISSN
1662-5129 (ISSN-L)
DOI
10.3389/fnana.2017.00071
PMC
PMC5572236
OpenAlex
W2748086290
Cited by
138
References
188
Citations by year
2026: 7 · 2025: 9 · 2024: 25 · 2023: 13 · 2022: 12 · 2021: 37 · 2020: 15 · 2019: 9 · 2018: 10 · 2017: 1
FWCI
1.18
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Frontiers in Neuroanatomy (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Institutes of Health (R01 EY016184, R01 EY022090)
Topics
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
cortico-cortical pathways, cortical lamination, visual cortex, layer 1, excitation-inhibition balance, pyramidal neurons, long-range connectivity, mouse visual cortex, synaptic structure

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