1932
0
  1. Home
  2. A-Z Publications
  3. Annual Review of Neuroscience
  4. Volume 44, 2021
  5. Article

Annual Review of Neuroscience

Volume 44, 2021

How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model

Abstract

The mouse, as a model organism to study the brain, gives us unprecedented experimental access to the mammalian cerebral cortex. By determining the cortex's cellular composition, revealing the interaction between its different components, and systematically perturbing these components, we are obtaining mechanistic insight into some of the most basic properties of cortical function. In this review, we describe recent advances in our understanding of how circuits of cortical neurons implement computations, as revealed by the study of mouse primary visual cortex. Further, we discuss how studying the mouse has broadened our understanding of the range of computations performed by visual cortex. Finally, we address how future approaches will fulfill the promise of the mouse in elucidating fundamental operations of cortex.

Keyword(s): behavioral state, contextual modulation, direction selectivity, orientation selectivity, perception, receptive field
Loading

Article metrics loading...

/content/journals/10.1146/annurev-neuro-102320-085825
2021-07-08
2024-04-24
Loading full text...

Full text loading...

/deliver/fulltext/neuro/44/1/annurev-neuro-102320-085825.html?itemId=/content/journals/10.1146/annurev-neuro-102320-085825&mimeType=html&fmt=ahah

Literature Cited

  1. Adesnik H. 2017. Synaptic mechanisms of feature coding in the visual cortex of awake mice. Neuron 95:51147–59.e4
     [Google Scholar]
  2. Adesnik H, Bruns W, Taniguchi H, Huang ZJ, Scanziani M. 2012. A neural circuit for spatial summation in visual cortex. Nature 490:7419226–31
     [Google Scholar]
  3. Ahmadian Y, Rubin DB, Miller KD. 2013. Analysis of the stabilized supralinear network. Neural Comput 25:81994–2037
     [Google Scholar]
  4. Ahmed B, Anderson JC, Douglas RJ, Martin KA, Nelson JC. 1994. Polyneuronal innervation of spiny stellate neurons in cat visual cortex. J. Comp. Neurol. 341:139–49
     [Google Scholar]
  5. Albrecht DG, Geisler WS. 1991. Motion selectivity and the contrast-response function of simple cells in the visual cortex. Vis. Neurosci. 7:6531–46
     [Google Scholar]
  6. Albright TD, Stoner GR. 2002. Contextual influences on visual processing. Annu. Rev. Neurosci. 25:339–79
     [Google Scholar]
  7. Andermann ML, Kerlin AM, Roumis DK, Glickfeld LL, Reid RC. 2011. Functional specialization of mouse higher visual cortical areas. Neuron 72:61025–39
     [Google Scholar]
  8. Atallah BV, Bruns W, Carandini M, Scanziani M. 2012. Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli. Neuron 73:1159–70
     [Google Scholar]
  9. Ayaz A, Saleem AB, Schölvinck ML, Carandini M. 2013. Locomotion controls spatial integration in mouse visual cortex. Curr. Biol. 23:10890–94
     [Google Scholar]
  10. Ayzenshtat I, Karnani MM, Jackson J, Yuste R 2016. Cortical control of spatial resolution by VIP+ interneurons. J. Neurosci. 36:4511498–509
     [Google Scholar]
  11. Barlow HB. 1961. Possible principles underlying the transformations of sensory messages. Sensory Communication WA Rosenblith 217–34 Cambridge, MA: MIT Press
     [Google Scholar]
  12. Bock DD, Lee W-CA, Kerlin AM, Andermann ML, Hood G et al. 2011. Network anatomy and in vivo physiology of visual cortical neurons. Nature 471:7337177–82
     [Google Scholar]
  13. Born G, Schneider FA, Erisken S, Klein A, Lao CL et al. 2021. Corticothalamic feedback sculpts visual spatial integration in mouse thalamus. bioRxiv 104000. https://doi.org/10.1101/2020.05.19.104000
    [Crossref]
  14. Bortone DS, Olsen SR, Scanziani M. 2014. Translaminar inhibitory cells recruited by layer 6 corticothalamic neurons suppress visual cortex. Neuron 82:2474–85
     [Google Scholar]
  15. Bouvier G, Senzai Y, Scanziani M. 2020. Head movements control the activity of primary visual cortex in a luminance-dependent manner. Neuron 108:500–11.e5
     [Google Scholar]
  16. Brunel N. 2000. Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J. Comput. Neurosci. 8:3183–208
     [Google Scholar]
  17. Bruno RM, Sakmann B. 2006. Cortex is driven by weak but synchronously active thalamocortical synapses. Science 312:57801622–27
     [Google Scholar]
  18. Busse L, Cardin JA, Chiappe ME, Halassa MM, McGinley MJ et al. 2017. Sensation during active behaviors. J. Neurosci. 37:4510826–34
     [Google Scholar]
  19. Carandini M, Heeger DJ. 1995. Summation and division in V1 simple cells. The Neurobiology of Computation JM Bower 59–65 Boston, MA: Springer
     [Google Scholar]
  20. Carandini M, Heeger DJ. 2011. Normalization as a canonical neural computation. Nat. Rev. Neurosci. 13:151–62
     [Google Scholar]
  21. Carrillo-Reid L, Han S, Yang W, Akrouh A, Yuste R. 2019. Controlling visually guided behavior by holographic recalling of cortical ensembles. Cell 178:2447–57.e5
     [Google Scholar]
  22. Chapman B, Zahs KR, Stryker MP. 1991. Relation of cortical cell orientation selectivity to alignment of receptive fields of the geniculocortical afferents that arborize within a single orientation column in ferret visual cortex. J. Neurosci. 11:51347–58
     [Google Scholar]
  23. Chen T-W, Wardill TJ, Sun Y, Pulver SR, Renninger SL et al. 2013. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499:7458295–300
     [Google Scholar]
  24. Cossell L, Iacaruso MF, Muir DR, Houlton R, Sader EN et al. 2015. Functional organization of excitatory synaptic strength in primary visual cortex. Nature 518:7539399–403
     [Google Scholar]
  25. Cruz-Martín A, El-Danaf RN, Osakada F, Sriram B, Dhande OS et al. 2014. A dedicated circuit links direction-selective retinal ganglion cells to the primary visual cortex. Nature 507:7492358–61
     [Google Scholar]
  26. de Vries SEJ, Lecoq JA, Buice MA, Groblewski PA, Ocker GK et al. 2020. A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex. Nat. Neurosci. 23:1138–51
     [Google Scholar]
  27. DeAngelis GC, Ohzawa I, Freeman RD. 1993. Spatiotemporal organization of simple-cell receptive fields in the cat's striate cortex. II. Linearity of temporal and spatial summation. J. Neurophysiol. 69:41118–35
     [Google Scholar]
  28. Dipoppa M, Ranson A, Krumin M, Pachitariu M, Carandini M, Harris KD 2018. Vision and locomotion shape the interactions between neuron types in mouse visual cortex. Neuron 98:3602–15
     [Google Scholar]
  29. Douglas RJ, Martin KAC, Whitteridge D. 1989. A canonical microcircuit for neocortex. Neural Comput 1:480–88
     [Google Scholar]
  30. 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:e19332
     [Google Scholar]
  31. Edinger L. 1908. The relations of comparative anatomy to comparative psychology. J. Comp. Neurol. Psychol. 18:437–57
     [Google Scholar]
  32. Engel TA, Steinmetz NA. 2019. New perspectives on dimensionality and variability from large-scale cortical dynamics. Curr. Opin. Neurobiol. 58:181–90
     [Google Scholar]
  33. Fairhall A. 2014. The receptive field is dead. Long live the receptive field?. Curr. Opin. Neurobiol. 25:ix–xii
     [Google Scholar]
  34. Felleman DJ, Van Essen DC. 1991. Distributed hierarchical processing in the primate cerebral cortex. Cereb. Cortex 1:11–47
     [Google Scholar]
  35. Ferster D, Chung S, Wheat H 1996. Orientation selectivity of thalamic input to simple cells of cat visual cortex. Nature 380:6571249–52
     [Google Scholar]
  36. Ferster D, Miller KD. 2000. Neural mechanisms of orientation selectivity in the visual cortex. Annu. Rev. Neurosci. 23:441–71
     [Google Scholar]
  37. Fiorani Júnior M, Rosa MG, Gattass R, Rocha-Miranda CE 1992. Dynamic surrounds of receptive fields in primate striate cortex: a physiological basis for perceptual completion?. PNAS 89:188547–51
     [Google Scholar]
  38. Fiser A, Mahringer D, Oyibo HK, Petersen AV, Leinweber M, Keller GB. 2016. Experience-dependent spatial expectations in mouse visual cortex. Nat. Neurosci. 19:121658–64
     [Google Scholar]
  39. Fu Y, Tucciarone JM, Espinosa JS, Sheng N, Darcy DP et al. 2014. A cortical circuit for gain control by behavioral state. Cell 156:61139–52
     [Google Scholar]
  40. Garcia-Marin V, Kelly JG, Hawken MJ. 2019. Major feedforward thalamic input into layer 4C of primary visual cortex in primate. Cereb. Cortex 29:1134–49
     [Google Scholar]
  41. Gilbert CD, Wiesel TN. 1990. The influence of contextual stimuli on the orientation selectivity of cells in primary visual cortex of the cat. Vision Res 30:111689–701
     [Google Scholar]
  42. Glickfeld LL, Andermann ML, Bonin V, Reid RC. 2013a. Cortico-cortical projections in mouse visual cortex are functionally target specific. Nat. Neurosci. 16:2219–26
     [Google Scholar]
  43. Glickfeld LL, Histed MH, Maunsell JHR. 2013b. Mouse primary visual cortex is used to detect both orientation and contrast changes. J. Neurosci. 33:5019416–22
     [Google Scholar]
  44. Glickfeld LL, Olsen SR. 2017. Higher-order areas of the mouse visual cortex. Annu. Rev. Vis. Sci. 3:251–73
     [Google Scholar]
  45. Gouwens NW, Sorensen SA, Berg J, Lee C, Jarsky T et al. 2019. Classification of electrophysiological and morphological neuron types in the mouse visual cortex. Nat. Neurosci. 22:71182–95
     [Google Scholar]
  46. Guillery RW, Sherman SM. 2002. Thalamic relay functions and their role in corticocortical communication: generalizations from the visual system. Neuron 33:2163–75
     [Google Scholar]
  47. Guitchounts G, Masís J, Wolff SBE, Cox D. 2020. Encoding of 3D head orienting movements in the primary visual cortex. Neuron 108:512–25.e4
     [Google Scholar]
  48. Haider B, Häusser M, Carandini M. 2013. Inhibition dominates sensory responses in the awake cortex. Nature 493:743097–100
     [Google Scholar]
  49. Han Y, Kebschull JM, Campbell RAA, Cowan D, Imhof F et al. 2018. The logic of single-cell projections from visual cortex. Nature 556:769951–56
     [Google Scholar]
  50. Harris JA, Mihalas S, Hirokawa KE, Whitesell JD, Choi H et al. 2019. Hierarchical organization of cortical and thalamic connectivity. Nature 575:7781195–202
     [Google Scholar]
  51. Hillier D, Fiscella M, Drinnenberg A, Trenholm S, Rompani SB et al. 2017. Causal evidence for retina-dependent and -independent visual motion computations in mouse cortex. Nat. Neurosci. 20:7960–68
     [Google Scholar]
  52. Hofer SB, Ko H, Pichler B, Vogelstein J, Ros H et al. 2011. Differential connectivity and response dynamics of excitatory and inhibitory neurons in visual cortex. Nat. Neurosci. 14:81045–52
     [Google Scholar]
  53. Hoy JL, Yavorska I, Wehr M, Niell CM. 2016. Vision drives accurate approach behavior during prey capture in laboratory mice. Curr. Biol. 26:223046–52
     [Google Scholar]
  54. Huang C, Ruff DA, Pyle R, Rosenbaum R, Cohen MR, Doiron B. 2019. Circuit models of low-dimensional shared variability in cortical networks. Neuron 101:2337–48.e4
     [Google Scholar]
  55. Hubel DH, Wiesel TN. 1959. Receptive fields of single neurones in the cat's striate cortex. J. Physiol. 148:574–91
     [Google Scholar]
  56. Hubel DH, Wiesel TN. 1962. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J. Physiol. 160:1106–54
     [Google Scholar]
  57. Hubel DH, Wiesel TN. 1968. Receptive fields and functional architecture of monkey striate cortex. J. Physiol. 195:1215–43
     [Google Scholar]
  58. Huberman AD, Niell CM. 2011. What can mice tell us about how vision works?. Trends Neurosci 34:9464–73
     [Google Scholar]
  59. Huh CYL, Peach JP, Bennett C, Vega RM, Hestrin S. 2018. Feature-specific organization of feedback pathways in mouse visual cortex. Curr. Biol. 28:1114–20.e5
     [Google Scholar]
  60. Iacaruso MF, Gasler IT, Hofer SB. 2017. Synaptic organization of visual space in primary visual cortex. Nature 547:7664449–52
     [Google Scholar]
  61. Ibrahim LA, Mesik L, Ji X-Y, Fang Q, Li H-F et al. 2016. Cross-modality sharpening of visual cortical processing through layer-1-mediated inhibition and disinhibition. Neuron 89:51031–45
     [Google Scholar]
  62. Isaacson JS, Scanziani M. 2011. How inhibition shapes cortical activity. Neuron 72:2231–43
     [Google Scholar]
  63. Iurilli G, Ghezzi D, Olcese U, Lassi G, Nazzaro C et al. 2012. Sound-driven synaptic inhibition in primary visual cortex. Neuron 73:4814–28
     [Google Scholar]
  64. Ji X-Y, Zingg B, Mesik L, Xiao Z, Zhang LI, Tao HW 2016. Thalamocortical innervation pattern in mouse auditory and visual cortex: laminar and cell-type specificity. Cereb. Cortex 26:62612–25
     [Google Scholar]
  65. Jiang X, Shen S, Cadwell CR, Berens P, Sinz F et al. 2015. Principles of connectivity among morphologically defined cell types in adult neocortex. Science 350:6264aac9462
     [Google Scholar]
  66. Jones HE, Grieve KL, Wang W, Sillito AM 2001. Surround suppression in primate V1. J. Neurophysiol. 86:42011–28
     [Google Scholar]
  67. Juavinett AL, Callaway EM. 2015. Pattern and component motion responses in mouse visual cortical areas. Curr. Biol. 25:131759–64
     [Google Scholar]
  68. Karnani MM, Jackson J, Ayzenshtat I, Tucciarone J, Manoocheri K et al. 2016. Cooperative subnetworks of molecularly similar interneurons in mouse neocortex. Neuron 90:186–100
     [Google Scholar]
  69. Keller AJ, Dipoppa M, Roth MM, Caudill MS, Ingrosso A et al. 2020a. A disinhibitory circuit for contextual modulation in primary visual cortex. Neuron 108:1181–93.e8
     [Google Scholar]
  70. Keller AJ, Roth MM, Scanziani M. 2020b. Feedback generates a second receptive field in neurons of the visual cortex. Nature 582:7813545–49
     [Google Scholar]
  71. Keller GB, Bonhoeffer T, Hübener M. 2012. Sensorimotor mismatch signals in primary visual cortex of the behaving mouse. Neuron 74:5809–15
     [Google Scholar]
  72. Kerlin AM, Andermann ML, Berezovskii VK, Reid RC. 2010. Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex. Neuron 67:5858–71
     [Google Scholar]
  73. Khibnik LA, Tritsch NX, Sabatini BL. 2014. A direct projection from mouse primary visual cortex to dorsomedial striatum. PLoS One 9:8e104501
     [Google Scholar]
  74. Kim EJ, Zhang Z, Huang L, Ito-Cole T, Jacobs MW et al. 2020. Extraction of distinct neuronal cell types from within a genetically continuous population. Neuron 107:2274–82.e6
     [Google Scholar]
  75. Kim M-H, Znamenskiy P, Iacaruso MF, Mrsic-Flogel TD. 2018. Segregated subnetworks of intracortical projection neurons in primary visual cortex. Neuron 100:61313–21.e6
     [Google Scholar]
  76. Ko H, Hofer SB, Pichler B, Buchanan KA, Sjöström PJ, Mrsic-Flogel TD. 2011. Functional specificity of local synaptic connections in neocortical networks. Nature 473:734587–91
     [Google Scholar]
  77. Kohn A, Coen-Cagli R, Kanitscheider I, Pouget A. 2016. Correlations and neuronal population information. Annu. Rev. Neurosci. 39:237–56
     [Google Scholar]
  78. La Chioma A, Bonhoeffer T, Hübener M 2019. Area-specific mapping of binocular disparity across mouse visual cortex. Curr. Biol. 29:172954–60.e5
     [Google Scholar]
  79. Lee AM, Hoy JL, Bonci A, Wilbrecht L, Stryker MP, Niell CM. 2014. Identification of a brainstem circuit regulating visual cortical state in parallel with locomotion. Neuron 83:2455–66
     [Google Scholar]
  80. Lee K-S, Vandemark K, Mezey D, Shultz N, Fitzpatrick D. 2019. Functional synaptic architecture of callosal inputs in mouse primary visual cortex. Neuron 101:3421–28.e5
     [Google Scholar]
  81. Lee S, Hjerling-Leffler J, Zagha E, Fishell G, Rudy B 2010. The largest group of superficial neocortical GABAergic interneurons expresses ionotropic serotonin receptors. J. Neurosci. 30:5016796–808
     [Google Scholar]
  82. Lee S-H, Kwan AC, Zhang S, Phoumthipphavong V, Flannery JG et al. 2012. Activation of specific interneurons improves V1 feature selectivity and visual perception. Nature 488:379–83
     [Google Scholar]
  83. Lee W-CA, Bonin V, Reed M, Graham BJ, Hood G et al. 2016. Anatomy and function of an excitatory network in the visual cortex. Nature 532:370–74
     [Google Scholar]
  84. Leinweber M, Ward DR, Sobczak JM, Attinger A, Keller GB. 2017. A sensorimotor circuit in mouse cortex for visual flow predictions. Neuron 95:1420–32.e5
     [Google Scholar]
  85. Leopold DA, Park SH. 2020. Studying the visual brain in its natural rhythm. Neuroimage 216:116790
     [Google Scholar]
  86. Li Y-T, Ibrahim LA, Liu B-H, Zhang LI, Tao HW. 2013. Linear transformation of thalamocortical input by intracortical excitation. Nat. Neurosci. 16:91324–30
     [Google Scholar]
  87. Li Y-T, Liu B-H, Chou X-L, Zhang LI, Tao HW. 2015. Strengthening of direction selectivity by broadly tuned and spatiotemporally slightly offset inhibition in mouse visual cortex. Cereb. Cortex 25:92466–77
     [Google Scholar]
  88. Li Y-T, Ma W-P, Li L-Y, Ibrahim LA, Wang S-Z, Tao HW. 2012. Broadening of inhibitory tuning underlies contrast-dependent sharpening of orientation selectivity in mouse visual cortex. J. Neurosci. 32:4616466–77
     [Google Scholar]
  89. Liang F, Xiong XR, Zingg B, Ji X-Y, Zhang LI, Tao HW 2015. Sensory cortical control of a visually induced arrest behavior via corticotectal projections. Neuron 86:3755–67
     [Google Scholar]
  90. Lien AD, Scanziani M. 2013. Tuned thalamic excitation is amplified by visual cortical circuits. Nat. Neurosci. 16:91315–23
     [Google Scholar]
  91. Lien AD, Scanziani M. 2018. Cortical direction selectivity emerges at convergence of thalamic synapses. Nature 558:770880–86
     [Google Scholar]
  92. Liu B-H, Huberman AD, Scanziani M. 2016. Cortico-fugal output from visual cortex promotes plasticity of innate motor behaviour. Nature 538:7625383–87
     [Google Scholar]
  93. Liu B-H, Li P, Li Y-T, Sun YJ, Yanagawa Y et al. 2009. Visual receptive field structure of cortical inhibitory neurons revealed by two-photon imaging guided recording. J. Neurosci. 29:3410520–32
     [Google Scholar]
  94. Liu B-H, Li Y-T, Ma W-P, Pan C-J, Zhang LI, Tao HW. 2011. Broad inhibition sharpens orientation selectivity by expanding input dynamic range in mouse simple cells. Neuron 71:3542–54
     [Google Scholar]
  95. Livingstone MS. 1998. Mechanisms of direction selectivity in macaque V1. Neuron 20:3509–26
     [Google Scholar]
  96. Longordo F, To M-S, Ikeda K, Stuart GJ. 2013. Sublinear integration underlies binocular processing in primary visual cortex. Nat. Neurosci. 16:6714–23
     [Google Scholar]
  97. Lur G, Vinck MA, Tang L, Cardin JA, Higley MJ. 2016. Projection-specific visual feature encoding by layer 5 cortical subnetworks. Cell Rep 14:112538–45
     [Google Scholar]
  98. Ma W-P, Liu B-H, Li Y-T, Huang ZJ, Zhang LI, Tao HW. 2010. Visual representations by cortical somatostatin inhibitory neurons—selective but with weak and delayed responses. J. Neurosci. 30:4314371–79
     [Google Scholar]
  99. Makino H, Komiyama T. 2015. Learning enhances the relative impact of top-down processing in the visual cortex. Nat. Neurosci. 18:81116–22
     [Google Scholar]
  100. Malpeli JG, Schiller PH, Colby CL. 1981. Response properties of single cells in monkey striate cortex during reversible inactivation of individual lateral geniculate laminae. J. Neurophysiol. 46:51102–19
     [Google Scholar]
  101. Marques T, Summers MT, Fioreze G, Fridman M, Dias RF et al. 2018. A role for mouse primary visual cortex in motion perception. Curr. Biol. 28:111703–13.e6
     [Google Scholar]
  102. Marshel JH, Garrett ME, Nauhaus I, Callaway EM. 2011. Functional specialization of seven mouse visual cortical areas. Neuron 72:61040–54
     [Google Scholar]
  103. Marshel JH, Kaye AP, Nauhaus I, Callaway EM. 2012. Anterior-posterior direction opponency in the superficial mouse lateral geniculate nucleus. Neuron 76:4713–20
     [Google Scholar]
  104. Marshel JH, Kim YS, Machado TA, Quirin S, Benson B et al. 2019. Cortical layer-specific critical dynamics triggering perception. Science 365:6453eaaw5202
     [Google Scholar]
  105. McLean J, Palmer LA. 1989. Contribution of linear spatiotemporal receptive field structure to velocity selectivity of simple cells in area 17 of cat. Vision Res 29:6675–79
     [Google Scholar]
  106. Meinecke DL, Peters A. 1987. GABA immunoreactive neurons in rat visual cortex. J. Comp. Neurol. 261:3388–404
     [Google Scholar]
  107. Meyer AF, Poort J, O'Keefe J, Sahani M, Linden JF 2018. A head-mounted camera system integrates detailed behavioral monitoring with multichannel electrophysiology in freely moving mice. Neuron 100:146–60.e7
     [Google Scholar]
  108. Michaiel AM, Abe ET, Niell CM. 2020. Dynamics of gaze control during prey capture in freely moving mice. eLife 9:e57458
     [Google Scholar]
  109. Miller KD. 2016. Canonical computations of cerebral cortex. Curr. Opin. Neurobiol. 37:75–84
     [Google Scholar]
  110. Millman DJ, Ocker GK, Caldejon S, Kato I, Larkin JD et al. 2019. VIP interneurons selectively enhance weak but behaviorally-relevant stimuli. bioRxiv 858001. https://doi.org/10.1101/858001
    [Crossref]
  111. Morgenstern NA, Bourg J, Petreanu L. 2016. Multilaminar networks of cortical neurons integrate common inputs from sensory thalamus. Nat. Neurosci. 19:81034–40
     [Google Scholar]
  112. Movshon JA, Thompson ID, Tolhurst DJ. 1978. Spatial summation in the receptive fields of simple cells in the cat's striate cortex. J. Physiol. 283:53–77
     [Google Scholar]
  113. Murgas KA, Wilson AM, Michael V, Glickfeld LL. 2020. Unique spatial integration in mouse primary visual cortex and higher visual areas. J. Neurosci. 40:91862–73
     [Google Scholar]
  114. Murphy BK, Miller KD. 2009. Balanced amplification: a new mechanism of selective amplification of neural activity patterns. Neuron 61:4635–48
     [Google Scholar]
  115. Musall S, Kaufman MT, Juavinett AL, Gluf S, Churchland AK. 2019. Single-trial neural dynamics are dominated by richly varied movements. Nat. Neurosci. 22:101677–86
     [Google Scholar]
  116. Nassi JJ, Callaway EM. 2009. Parallel processing strategies of the primate visual system. Nat. Rev. Neurosci. 10:5360–72
     [Google Scholar]
  117. Niell CM, Stryker MP. 2008. Highly selective receptive fields in mouse visual cortex. J. Neurosci. 28:307520–36
     [Google Scholar]
  118. Niell CM, Stryker MP. 2010. Modulation of visual responses by behavioral state in mouse visual cortex. Neuron 65:4472–79
     [Google Scholar]
  119. Nurminen L, Angelucci A. 2014. Multiple components of surround modulation in primary visual cortex: multiple neural circuits with multiple functions?. Vision Res 104:47–56
     [Google Scholar]
  120. Olsen SR, Bortone DS, Adesnik H, Scanziani M. 2012. Gain control by layer six in cortical circuits of vision. Nature 483:738747–52
     [Google Scholar]
  121. Pakan JMP, Currie SP, Fischer L, Rochefort NL. 2018. The impact of visual cues, reward, and motor feedback on the representation of behaviorally relevant spatial locations in primary visual cortex. Cell Rep 24:102521–28
     [Google Scholar]
  122. Panzeri S, Macke JH, Gross J, Kayser C. 2015. Neural population coding: combining insights from microscopic and mass signals. Trends Cogn. Sci. 19:3162–72
     [Google Scholar]
  123. Parker PRL, Brown MA, Smear MC, Niell CM. 2020. Movement-related signals in sensory areas: roles in natural behavior. Trends Neurosci 43:8581–95
     [Google Scholar]
  124. Peters AJ, Fabre JMJ, Steinmetz NA, Harris KD, Carandini M. 2021. Striatal activity topographically reflects cortical activity. Nature 591:7850420–25
     [Google Scholar]
  125. Pfeffer CK, Xue M, He M, Huang ZJ, Scanziani M. 2013. Inhibition of inhibition in visual cortex: the logic of connections between molecularly distinct interneurons. Nat. Neurosci. 16:81068–76
     [Google Scholar]
  126. Piscopo DM, El-Danaf RN, Huberman AD, Niell CM. 2013. Diverse visual features encoded in mouse lateral geniculate nucleus. J. Neurosci. 33:114642–56
     [Google Scholar]
  127. Poort J, Khan AG, Pachitariu M, Nemri A, Orsolic I et al. 2015. Learning enhances sensory and multiple non-sensory representations in primary visual cortex. Neuron 86:61478–90
     [Google Scholar]
  128. Priebe NJ, Ferster D. 2008. Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. Neuron 57:4482–97
     [Google Scholar]
  129. Prusky GT, Douglas RM. 2004. Characterization of mouse cortical spatial vision. Vision Res 28:3411–18
     [Google Scholar]
  130. Rasmussen R, Matsumoto A, Dahlstrup Sietam M, Yonehara K 2020. A segregated cortical stream for retinal direction selectivity. Nat. Commun. 11:1831
     [Google Scholar]
  131. Reid RC, Alonso JM. 1995. Specificity of monosynaptic connections from thalamus to visual cortex. Nature 378:6554281–84
     [Google Scholar]
  132. Reid RC, Soodak RE, Shapley RM. 1987. Linear mechanisms of directional selectivity in simple cells of cat striate cortex. PNAS 84:238740–44
     [Google Scholar]
  133. Reid RC, Soodak RE, Shapley RM. 1991. Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex. J. Neurophysiol. 66:2505–29
     [Google Scholar]
  134. Reinhold K, Lien AD, Scanziani M. 2015. Distinct recurrent versus afferent dynamics in cortical visual processing. Nat. Neurosci. 18:121789–97
     [Google Scholar]
  135. Resulaj A, Ruediger S, Olsen SR, Scanziani M. 2018. First spikes in visual cortex enable perceptual discrimination. eLife 7:e34044
     [Google Scholar]
  136. Ringach DL. 2021. Sparse thalamocortical convergence. Curr. Biol. In press
    [Google Scholar]
  137. Rossi AF, Desimone R, Ungerleider LG. 2001. Contextual modulation in primary visual cortex of macaques. J. Neurosci. 21:51698–709
     [Google Scholar]
  138. Rossi LF, Harris KD, Carandini M. 2020. Spatial connectivity matches direction selectivity in visual cortex. Nature 588:7839648–52
     [Google Scholar]
  139. Roth MM, Dahmen JC, Muir DR, Imhof F, Martini FJ, Hofer SB. 2016. Thalamic nuclei convey diverse contextual information to layer 1 of visual cortex. Nat. Neurosci. 19:2299–307
     [Google Scholar]
  140. Roth MM, Helmchen F, Kampa BM. 2012. Distinct functional properties of primary and posteromedial visual area of mouse neocortex. J. Neurosci. 32:289716–26
     [Google Scholar]
  141. Roth RH, Cudmore RH, Tan HL, Hong I, Zhang Y, Huganir RL. 2020. Cortical synaptic AMPA receptor plasticity during motor learning. Neuron 105:5895–908.e5
     [Google Scholar]
  142. Ruediger S, Scanziani M. 2020. Learning speed and detection sensitivity controlled by distinct cortico-fugal neurons in visual cortex. eLife 9:e59247
     [Google Scholar]
  143. Rumyantsev OI, Lecoq JA, Hernandez O, Zhang Y, Savall J et al. 2020. Fundamental bounds on the fidelity of sensory cortical coding. Nature 580:7801100–105
     [Google Scholar]
  144. Runyan CA, Schummers J, Van Wart A, Kuhlman SJ, Wilson NR et al. 2010. Response features of parvalbumin-expressing interneurons suggest precise roles for subtypes of inhibition in visual cortex. Neuron 67:5847–57
     [Google Scholar]
  145. Sadeh S, Clopath C. 2021. Inhibitory stabilization and cortical computation. Nat. Rev. Neurosci. 22:121–37
     [Google Scholar]
  146. Saleem AB, Ayaz A, Jeffery KJ, Harris KD, Carandini M. 2013. Integration of visual motion and locomotion in mouse visual cortex. Nat. Neurosci. 16:121864–69
     [Google Scholar]
  147. Saleem AB, Diamanti EM, Fournier J, Harris KD, Carandini M. 2018. Coherent encoding of subjective spatial position in visual cortex and hippocampus. Nature 562:7725124–27
     [Google Scholar]
  148. Sarnaik R, Chen H, Liu X, Cang J. 2014. Genetic disruption of the On visual pathway affects cortical orientation selectivity and contrast sensitivity in mice. J. Neurophysiol. 111:112276–86
     [Google Scholar]
  149. Saul AB, Humphrey AL. 1992. Evidence of input from lagged cells in the lateral geniculate nucleus to simple cells in cortical area 17 of the cat. J. Neurophysiol. 68:41190–208
     [Google Scholar]
  150. Schnabel UH, Bossens C, Lorteije JAM, Self MW, Op de Beeck H, Roelfsema PR. 2018. Figure-ground perception in the awake mouse and neuronal activity elicited by figure-ground stimuli in primary visual cortex. Sci. Rep. 8:117800
     [Google Scholar]
  151. Scholl B, Tan AYY, Corey J, Priebe NJ 2013. Emergence of orientation selectivity in the mammalian visual pathway. J. Neurosci. 33:2610616–24
     [Google Scholar]
  152. Seabrook TA, Burbridge TJ, Crair MC, Huberman AD. 2017. Architecture, function, and assembly of the mouse visual system. Annu. Rev. Neurosci. 40:499–538
     [Google Scholar]
  153. Sedigh-Sarvestani M, Vigeland L, Fernandez-Lamo I, Taylor MM, Palmer LA, Contreras D. 2017. Intracellular, in vivo, dynamics of thalamocortical synapses in visual cortex. J. Neurosci. 37:215250–62
     [Google Scholar]
  154. Seeman SC, Campagnola L, Davoudian PA, Hoggarth A, Hage TA et al. 2018. Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex. eLife 7:e37349
     [Google Scholar]
  155. Self MW, Lorteije JAM, Vangeneugden J, van Beest EH, Grigore ME et al. 2014. Orientation-tuned surround suppression in mouse visual cortex. J. Neurosci. 34:289290–304
     [Google Scholar]
  156. Shuler MG, Bear MF. 2006. Reward timing in the primary visual cortex. Science 311:57671606–9
     [Google Scholar]
  157. Sillito AM. 1975. The contribution of inhibitory mechanisms to the receptive field properties of neurones in the striate cortex of the cat. J. Physiol. 250:2305–29
     [Google Scholar]
  158. Sit KK, Goard MJ. 2020. Distributed and retinotopically asymmetric processing of coherent motion in mouse visual cortex. Nat. Commun. 11:13565
     [Google Scholar]
  159. Smith SL, Smith IT, Branco T, Häusser M. 2013. Dendritic spikes enhance stimulus selectivity in cortical neurons in vivo. Nature 503:7474115–20
     [Google Scholar]
  160. Stringer C, Michaelos M, Pachitariu M. 2019a. High precision coding in visual cortex. bioRxiv 679324. https://doi.org/10.1101/679324
    [Crossref] [Google Scholar]
  161. Stringer C, Pachitariu M, Steinmetz N, Carandini M, Harris KD. 2019b. High-dimensional geometry of population responses in visual cortex. Nature 571:7765361–65
     [Google Scholar]
  162. Stringer C, Pachitariu M, Steinmetz N, Okun M, Bartho P et al. 2016. Inhibitory control of correlated intrinsic variability in cortical networks. eLife 5:e19695
     [Google Scholar]
  163. Stringer C, Pachitariu M, Steinmetz N, Reddy CB, Carandini M, Harris KD. 2019c. Spontaneous behaviors drive multidimensional, brainwide activity. Science 364:6437eaav7893
     [Google Scholar]
  164. Sun W, Tan Z, Mensh BD, Ji N 2016. Thalamus provides layer 4 of primary visual cortex with orientation- and direction-tuned inputs. Nat. Neurosci. 19:2308–15
     [Google Scholar]
  165. Tang L, Higley MJ. 2020. Layer 5 circuits in V1 differentially control visuomotor behavior. Neuron 105:2346–54.e5
     [Google Scholar]
  166. Tasic B, Menon V, Nguyen TN, Kim TK, Jarsky T et al. 2016. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat. Neurosci. 19:2335–46
     [Google Scholar]
  167. Vale R, Evans DA, Branco T. 2017. Rapid spatial learning controls instinctive defensive behavior in mice. Curr. Biol. 27:91342–49
     [Google Scholar]
  168. Van den Bergh G, Zhang B, Arckens L, Chino YM. 2010. Receptive-field properties of V1 and V2 neurons in mice and macaque monkeys. J. Comp. Neurol. 518:112051–70
     [Google Scholar]
  169. van Vreeswijk C, Sompolinsky H. 1996. Chaos in neuronal networks with balanced excitatory and inhibitory activity. Science 274:52931724–26
     [Google Scholar]
  170. Vangeneugden J, van Beest EH, Cohen MX, Lorteije JAM, Mukherjee S et al. 2019. Activity in lateral visual areas contributes to surround suppression in awake mouse V1. Curr. Biol. 29:244268–75.e7
     [Google Scholar]
  171. Vélez-Fort M, Bracey EF, Keshavarzi S, Rousseau CV, Cossell L et al. 2018. A circuit for integration of head- and visual-motion signals in layer 6 of mouse primary visual cortex. Neuron 98:1179–91.e6
     [Google Scholar]
  172. Vélez-Fort M, Rousseau CV, Niedworok CJ, Wickersham IR, Rancz EA et al. 2014. The stimulus selectivity and connectivity of layer six principal cells reveals cortical microcircuits underlying visual processing. Neuron 83:61431–43
     [Google Scholar]
  173. Vinck M, Batista-Brito R, Knoblich U, Cardin JA. 2015. Arousal and locomotion make distinct contributions to cortical activity patterns and visual encoding. Neuron 86:3740–54
     [Google Scholar]
  174. von der Heydt R, Peterhans E, Baumgartner G. 1984. Illusory contours and cortical neuron responses. Science 224:46541260–62
     [Google Scholar]
  175. Wang Q, Burkhalter A. 2007. Area map of mouse visual cortex. J. Comp. Neurol. 502:3339–57
     [Google Scholar]
  176. Wekselblatt JB, Flister ED, Piscopo DM, Niell CM. 2016. Large-scale imaging of cortical dynamics during sensory perception and behavior. J. Neurophysiol. 115:62852–66
     [Google Scholar]
  177. Wertz A, Trenholm S, Yonehara K, Hillier D, Raics Z et al. 2015. Single-cell-initiated monosynaptic tracing reveals layer-specific cortical network modules. Science 349:624370–74
     [Google Scholar]
  178. Whiteway MR, Butts DA. 2019. The quest for interpretable models of neural population activity. Curr. Opin. Neurobiol. 58:86–93
     [Google Scholar]
  179. Wilson NR, Runyan CA, Wang FL, Sur M. 2012. Division and subtraction by distinct cortical inhibitory networks in vivo. Nature 488:7411343–48
     [Google Scholar]
  180. Xue M, Atallah BV, Scanziani M. 2014. Equalizing excitation-inhibition ratios across visual cortical neurons. Nature 511:7511596–600
     [Google Scholar]
  181. Yoshimura Y, Dantzker JLM, Callaway EM. 2005. Excitatory cortical neurons form fine-scale functional networks. Nature 433:7028868–73
     [Google Scholar]
  182. Young H, Belbut B, Baeta M, Petreanu L. 2021. Laminar-specific cortico-cortical loops in mouse visual cortex. eLife 10:e59551
     [Google Scholar]
  183. Zhang S, Xu M, Kamigaki T, Hoang Do JP, Chang W-C et al. 2014. Selective attention. Long-range and local circuits for top-down modulation of visual cortex processing. Science 345:6197660–65
     [Google Scholar]
  184. Zhao X, Chen H, Liu X, Cang J. 2013. Orientation-selective responses in the mouse lateral geniculate nucleus. J. Neurosci. 33:3112751–63
     [Google Scholar]
  185. Zhao X, Liu M, Cang J. 2014. Visual cortex modulates the magnitude but not the selectivity of looming-evoked responses in the superior colliculus of awake mice. Neuron 84:1202–13
     [Google Scholar]
  186. Zohary E, Shadlen MN, Newsome WT. 1994. Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370:6485140–43
     [Google Scholar]
/content/journals/10.1146/annurev-neuro-102320-085825
Loading
How Cortical Circuits Implement Cortical Computations: Mouse Visual Cortex as a Model
Annual Review of Neuroscience 44, 517 (2021); https://doi.org/10.1146/annurev-neuro-102320-085825
/content/journals/10.1146/annurev-neuro-102320-085825
/content/journals/10.1146/annurev-neuro-102320-085825
Loading

Data & Media loading...

Supplemental Material

Supplementary Data

  • Article Type: Review Article

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error