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The Role of Criticality in Flexible Visual Information Processing

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The Functional Role of Critical Dynamics in Neural Systems

Part of the book series: Springer Series on Bio- and Neurosystems ((SSBN,volume 11))

Abstract

Dynamical systems close to a critical state have the ability to spontaneously engage large numbers of units in collective events called avalanches–but how can this property be actively employed by the brain in order to perform meaningful computations under realistic circumstances? In our study we investigate this question by focusing on the visual system which has to meet a major challenge: to rapidly integrate information from a large number of single channels, and in a flexible manner depending on behavioral and external context. In this framework we are going to discuss two distinct examples, the first a bottom-up figure-ground segregation scenario and the second a top-down enhancement of object discriminability under selective attention. Both scenarios make explicit use of critical states for information processing, while formally extending the concept of criticality to inhomogeneous systems subject to a strong external drive.

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References

  1. Arviv, O., Goldstein, A., Shriki, O.: Near-critical dynamics in stimulus-evoked activity of the human brain and its relation to spontaneous resting-state activity. J. Neurosci.: Off. J. Soc. Neurosci. 35(41), 13,927–42 (2015). https://doi.org/10.1523/JNEUROSCI.0477-15.2015. http://www.ncbi.nlm.nih.gov/pubmed/26468194

    Article  CAS  Google Scholar 

  2. Bak, P., Tang, C., Wiesenfeld, K.: Self-organized criticality: an explanation of the 1/f noise. Phys. Rev. Lett. 59(4), 381–384 (1987). https://doi.org/10.1103/PhysRevLett.59.381

    Article  CAS  Google Scholar 

  3. Bauer, R., Heinze, S.: Contour integration in striate cortex. Classic cell responses or cooperative selection? Exp. Brain Res. 147(2), 145–152 (2002)

    Article  Google Scholar 

  4. Beggs, J.M.: The criticality hypothesis: how local cortical networks might optimize information processing. Philos. Trans. Ser. A, Math., Phys., Eng. Sci. 366(1864), 329–343 (2008). https://doi.org/10.1098/rsta.2007.2092. http://www.ncbi.nlm.nih.gov/pubmed/17673410

    Article  Google Scholar 

  5. Beggs, J.M., Plenz, D.: Neuronal avalanches in neocortical circuits. J. Neurosci.: Off. J. Soc. Neurosci. 23(35), 11,167–77 (2003). https://doi.org/10.1523/JNEUROSCI.23-35-11167.2003. http://www.ncbi.nlm.nih.gov/pubmed/14657176

    Article  CAS  Google Scholar 

  6. Bertschinger, N., Natschläger, T.: Real-time computation at the edge of chaos in recurrent neural networks. Neural Comput. 16(7), 1413–1436 (2004). https://doi.org/10.1162/089976604323057443

    Article  PubMed  Google Scholar 

  7. Carandini, M., Heeger, D.J., Movshon, J.A.: Linearity and normalization in simple cells of the macaque primary visual cortex. J. Neurosci.: Off. J. Soc. Neurosci. 17(21), 8621–8644 (1997). https://doi.org/10.1523/JNEUROSCI.17-21-08621.1997

    Article  CAS  Google Scholar 

  8. Chen, M.G., Yan, Y., Gong, X.J., Gilbert, C.D., Liang, H.L., Li, W.: Incremental integration of global contours through interplay between visual cortical areas. Neuron 82(3), 682–694 (2014)

    Article  CAS  Google Scholar 

  9. Chialvo, D.R.: Emergent complex neural dynamics. Nat. Phys. 6(10), 744–750 (2010). https://doi.org/10.1038/nphys1803

    Article  CAS  Google Scholar 

  10. Dayan, P., Abbott, L.F.: Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems, 1st edn. Massachusetts Institute of Technology Press, Massachusetts (2001)

    Google Scholar 

  11. Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., Reitboeck, H.J.: Coherent oscillations: a mechanism of feature linking in the visual cortex? Biol. Cybern. 60(2), 121–130 (1988). https://doi.org/10.1007/BF00202899

    Article  CAS  PubMed  Google Scholar 

  12. Ernst, U.A., Mandon, S., Schinkel Bielefeld, N., Neitzel, S.D., Kreiter, A.K., Pawelzik, K.R.: Optimality of human contour integration. PLoS Comput. Biol. 8(5), e1002,520 (2012). https://doi.org/10.1371/journal.pcbi.1002520. http://dx.plos.org/10.1371/journal.pcbi.1002520

    Article  CAS  Google Scholar 

  13. Eurich, C.W., Herrmann, J.M., Ernst, U.A.: Finite-size effects of avalanche dynamics. Phys. Rev. E 66(6), 066,137 (2002). https://doi.org/10.1103/PhysRevE.66.066137. https://link.aps.org/doi/10.1103/PhysRevE.66.066137

  14. Fagerholm, E.D., Lorenz, R., Scott, G., Dinov, M., Hellyer, P.J., Mirzaei, N., Leeson, C., Carmichael, D.W., Sharp, D.J., Shew, W.L., Leech, R.: Cascades and cognitive state: focused attention incurs subcritical dynamics. J. Neurosci.: Off. J. Soc. Neurosci. 35(11), 4626–4634 (2015). https://doi.org/10.1523/JNEUROSCI.3694-14.2015

    Article  CAS  Google Scholar 

  15. Field, D.J., Hayes, A., Hess, R.F.: Contour integration by the human visual system: evidence for a local association field. Vis. Res. 33(2), 173–193 (1993). https://doi.org/10.1016/0042-6989(93)90156-Q

    Article  CAS  PubMed  Google Scholar 

  16. Finger, H., Knig, P.: Phase synchrony facilitates binding and segmentation of natural images in a coupled neural oscillator network. Front. Comput. Neurosci. 7, 195 (2014). https://doi.org/10.3389/fncom.2013.00195

    Article  PubMed  PubMed Central  Google Scholar 

  17. Friedman, N., Ito, S., Brinkman, B.A.W., Shimono, M., DeVille, R.E.L., Dahmen, K.A., Beggs, J.M., Butler, T.C.: Universal critical dynamics in high resolution neuronal avalanche data. Phys. Rev. Lett. 108(20), 208,102 (2012). https://doi.org/10.1103/PhysRevLett.108.208102. https://link.aps.org/doi/10.1103/PhysRevLett.108.208102

  18. Fries, P.: A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. Trends Cogn. Sci. 9(10), 474–480 (2005). https://doi.org/10.1016/J.TICS.2005.08.011

    Article  PubMed  Google Scholar 

  19. Fries, P., Reynolds, J.H., Rorie, A.E., Desimone, R.: Modulation of oscillatory neuronal synchronization by selective visual attention. Science (New York, N.Y.) 291(5508), 1560–1563 (2001). https://doi.org/10.1126/science.291.5508.1560. http://www.ncbi.nlm.nih.gov/pubmed/11222864

  20. Gautam, S.H., Hoang, T.T., McClanahan, K., Grady, S.K., Shew, W.L.: Maximizing sensory dynamic range by tuning the cortical state to criticality. PLOS Comput. Biol. 11(12), e1004,576 (2015). https://doi.org/10.1371/journal.pcbi.1004576. http://dx.plos.org/10.1371/journal.pcbi.1004576

    Article  Google Scholar 

  21. Gilad, A., Meirovithz, E., Slovin, H.: Population responses to contour integration: early encoding of discrete elements and late perceptual grouping. Neuron 78(2), 389–402 (2013)

    Article  CAS  Google Scholar 

  22. Grothe, I., Neitzel, S.D., Mandon, S., Kreiter, A.K.: Switching neuronal inputs by differential modulations of gamma-band phase-coherence. J. Neurosci.: Off. J. Soc. Neurosci. 32(46), 16,172–80 (2012). https://doi.org/10.1523/JNEUROSCI.0890-12.2012. http://www.ncbi.nlm.nih.gov/pubmed/23152601

    Article  CAS  Google Scholar 

  23. Grothe, I., Rotermund, D., Neitzel, S.D., Mandon, S., Ernst, U.A., Kreiter, A.K., Pawelzik, K.R.: Attention selectively gates afferent signal transmission to area V4. J. Neurosci.: Off. J. Soc. Neurosci. 38(14), 3441–3452 (2018). https://doi.org/10.1523/JNEUROSCI.2221-17.2018

    Article  CAS  Google Scholar 

  24. Hahn, G., Ponce-Alvarez, A., Monier, C., Benvenuti, G., Kumar, A., Chavane, F., Deco, G., Frégnac, Y.: Spontaneous cortical activity is transiently poised close to criticality. PLOS Comput. Biol. 13(5), e1005,543 (2017). https://doi.org/10.1371/journal.pcbi.1005543. https://dx.plos.org/10.1371/journal.pcbi.1005543

    Article  Google Scholar 

  25. Haldeman, C., Beggs, J.M.: Critical branching captures activity in living neural networks and maximizes the number of metastable states. Phys. Rev. Lett. 94(5), 058,101 (2005). https://doi.org/10.1103/PhysRevLett.94.058101. https://link.aps.org/doi/10.1103/PhysRevLett.94.058101

  26. Harnack, D., Ernst, U.A., Pawelzik, K.R.: A model for attentional information routing through coherence predicts biased competition and multistable perception. J. Neurophysiol. 114(3), 1593–1605 (2015). https://doi.org/10.1152/jn.01038.2014

    Article  PubMed  PubMed Central  Google Scholar 

  27. Hebb, D.O.: The Organization of Behavior: A Neuropsychological Theory. Wiley, New York (1949)

    Google Scholar 

  28. Hess, R., Hayes, A., Field, D.: Contour integration and cortical processing. J. Physiol.-Paris 97(2–3), 105–119 (2003). https://doi.org/10.1016/J.JPHYSPARIS.2003.09.013

    Article  CAS  Google Scholar 

  29. Hesse, J., Gross, T.: Self-organized criticality as a fundamental property of neural systems. Front. Syst. Neurosci. 8, 166 (2014). https://doi.org/10.3389/fnsys.2014.00166

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hubel, D.H., Wiesel, T.N.: Receptive fields and functional architecture of monkey striate cortex. J. Physiol. 195(1), 215–243 (1968). https://doi.org/10.1113/jphysiol.1968.sp008455

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Jones, H.E., Grieve, K.L., Wang, W., Sillito, A.M.: Surround suppression in primate V1. J. Neurophysiol. 86(4), 2011–2028 (2001). https://doi.org/10.1152/jn.2001.86.4.2011

    Article  CAS  PubMed  Google Scholar 

  32. Kinouchi, O., Copelli, M.: Optimal dynamical range of excitable networks at criticality. Nat. Phys. 2(5), 348–351 (2006). https://doi.org/10.1038/nphys289

    Article  CAS  Google Scholar 

  33. Kovács, I., Julesz, B.: A closed curve is much more than an incomplete one: effect of closure in figure-ground segmentation. Proc. Natl. Acad. Sci. U. S. A. 90(16), 7495–7497 (1993). https://doi.org/10.1073/PNAS.90.16.7495

    Article  PubMed  PubMed Central  Google Scholar 

  34. Kreiter, A.K., Singer, W.: Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey. J. Neurosci.: Off. J. Soc. Neurosci. 16(7), 2381–2396 (1996). https://doi.org/10.1523/JNEUROSCI.16-07-02381.1996

    Article  CAS  Google Scholar 

  35. Langton, C.G.: Computation at the edge of chaos: phase transitions and emergent computation. Phys. D: Nonlinear Phenom. 42(1–3), 12–37 (1990). https://doi.org/10.1016/0167-2789(90)90064-V

    Article  Google Scholar 

  36. Levina, A., Priesemann, V.: Subsampling scaling. Nat. Commun. 8, 15,140 (2017). https://doi.org/10.1038/ncomms15140. http://www.nature.com/doifinder/10.1038/ncomms15140

  37. Levitt, J.B., Lund, J.S.: Contrast dependence of contextual effects in primate visual cortex. Nature 387, 73–76 (1997)

    Article  CAS  Google Scholar 

  38. Li, W., Pich, V., Gilbert, C.D.: Contour saliency in primary visual cortex. Neuron 50(6), 951–962 (2006)

    Article  CAS  Google Scholar 

  39. Luck, S., Chelazzi, L., Hillyard, S., Desimone, R.: Neural mechanisms of spatial selective attention in areas v1, v2 and v4 of macaque visual cortex. J. Neurophysiol. 77, 24–42 (1997)

    Article  CAS  Google Scholar 

  40. Mack, A.: Inattentional blindness: looking without seeing. Curr. Dir. Psychol. Sci. (2003). https://doi.org/10.1111/1467-8721.01256

    Article  Google Scholar 

  41. von der Malsburg, C.: The correlation theory of brain function. In: Models of Neural Networks, pp. 95–119. Springer, New York (1994). https://doi.org/10.1007/978-1-4612-4320-5. http://link.springer.com/10.1007/978-1-4612-4320-5_2

    Google Scholar 

  42. Mandon, S., Kreiter, A.K.: Rapid contour integration in macaque monkeys. Vis. Res. 45(3), 291–300 (2005). https://doi.org/10.1016/J.VISRES.2004.08.010

    Article  PubMed  Google Scholar 

  43. Massobrio, P., Pasquale, V., Martinoia, S.: Self-organized criticality in cortical assemblies occurs in concurrent scale-free and small-world networks. Sci. Rep. 5(1), 10,578 (2015). https://doi.org/10.1038/srep10578. http://www.nature.com/articles/srep10578

  44. Meisel, C., Olbrich, E., Shriki, O., Achermann, P.: Fading signatures of critical brain dynamics during sustained wakefulness in humans. J. Neurosci.: Off. J. Soc. Neurosci. 33(44), 17,363–72 (2013). https://doi.org/10.1523/JNEUROSCI.1516-13.2013. http://www.ncbi.nlm.nih.gov/pubmed/24174669. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3858643

    Article  CAS  Google Scholar 

  45. Moran, J., Desimone, R.: Selective attention gates visual processing in the extrastriate cortex. Science 229(4715), 782–784 (1985). https://doi.org/10.1126/science.4023713

    Article  CAS  PubMed  Google Scholar 

  46. Nykter, M., Price, N.D., Larjo, A., Aho, T., Kauffman, S.A., Yli-Harja, O., Shmulevich, I.: Critical networks exhibit maximal information diversity in structure-dynamics relationships. Phys. Rev. Lett. 100(5), 058,702 (2008). https://doi.org/10.1103/PhysRevLett.100.058702. https://link.aps.org/doi/10.1103/PhysRevLett.100.058702

  47. Palva, J.M., Zhigalov, A., Hirvonen, J., Korhonen, O., Linkenkaer-Hansen, K., Palva, S.: Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proc. Natl. Acad. Sci. U. S. A. 110(9), 3585–3590 (2013). https://doi.org/10.1073/pnas.1216855110

    Article  PubMed  PubMed Central  Google Scholar 

  48. Pasquale, V., Massobrio, P., Bologna, L.L., Chiappalone, M., Martinoia, S.: Self-organization and neuronal avalanches in networks of dissociated cortical neurons. Neuroscience 153(4), 1354–1369 (2008). https://doi.org/10.1016/j.neuroscience.2008.03.050

    Article  CAS  PubMed  Google Scholar 

  49. Petermann, T., Thiagarajan, T.C., Lebedev, M.A., Nicolelis, M.A.L., Chialvo, D.R., Plenz, D.: Spontaneous cortical activity in awake monkeys composed of neuronal avalanches. Proc. Natl. Acad. Sci. U. S. A. 106(37), 15,921–6 (2009). https://doi.org/10.1073/pnas.0904089106. http://www.ncbi.nlm.nih.gov/pubmed/19717463. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2732708

    Article  CAS  Google Scholar 

  50. Plenz, D.: Criticality in cortex: neuronal avalanches and coherence potentials. In: Criticality in Neural Systems, pp. 5–42. Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany (2014). https://doi.org/10.1002/9783527651009.ch2. http://doi.wiley.com/10.1002/9783527651009.ch2

    Chapter  Google Scholar 

  51. Polat, U., Sagi, D.: Lateral interactions between spatial channels: suppression and facilitation revealed by lateral masking experiments. Vis. Res. 33(7), 993–999 (1993)

    Article  CAS  Google Scholar 

  52. Priesemann, V., Valderrama, M., Wibral, M., Le Van Quyen, M.: Neuronal avalanches differ from wakefulness to deep sleep evidence from intracranial depth recordings in humans. PLoS Comput. Biol. 9(3), e1002,985 (2013). https://doi.org/10.1371/journal.pcbi.1002985. http://dx.plos.org/10.1371/journal.pcbi.1002985

    Article  CAS  Google Scholar 

  53. Priesemann, V., Wibral, M., Valderrama, M., Pröpper, R., Le Van Quyen, M., Geisel, T., Triesch, J., Nikolić, D., Munk, M.H.J.: Spike avalanches in vivo suggest a driven, slightly subcritical brain state. Front. Syst. Neurosci. 8, 108 (2014). https://doi.org/10.3389/fnsys.2014.00108

    Article  PubMed  PubMed Central  Google Scholar 

  54. Ritz, R., Gerstner, W., Fuentes, U., van Hemmen, J.: A biologically motivated and analytically soluble model of collective oscillations in the cortex. ii. Application to binding and pattern segmentation. Biol Cybern. 71(4), 349–358 (1994)

    Article  CAS  Google Scholar 

  55. Roelfsema, P.R.: Cortical algorithms for perceptual grouping. Annu. Rev. Neurosci. 29, 203–227 (2006)

    Article  CAS  Google Scholar 

  56. Rotermund, D., Taylor, K., Ernst, U.A., Kreiter, A.K., Pawelzik, K.R.: Attention improves object representation in visual cortical field potentials. J. Neurosci. 29(32), 10120–10130 (2009). https://doi.org/10.1523/JNEUROSCI.5508-08.2009

    Article  CAS  PubMed  Google Scholar 

  57. Scarpetta, S., de Candia, A.: Neural avalanches at the critical point between replay and non-replay of spatiotemporal patterns. PLoS ONE 8(6), e64,162 (2013). https://doi.org/10.1371/journal.pone.0064162. http://dx.plos.org/10.1371/journal.pone.0064162

    Article  CAS  Google Scholar 

  58. Schoenholz, S.S., Gilmer, J., Ganguli, S., Sohl-Dickstein, J.: Deep Information Propagation (2016). http://arxiv.org/abs/1611.01232

  59. Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948). https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

    Article  Google Scholar 

  60. Shew, W.L., Clawson, W.P., Pobst, J., Karimipanah, Y., Wright, N.C., Wessel, R.: Adaptation to sensory input tunes visual cortex to criticality. Nat. Phys. 11(8), 659–663 (2015). https://doi.org/10.1038/nphys3370

    Article  CAS  Google Scholar 

  61. Shew, W.L., Plenz, D.: The functional benefits of criticality in the cortex. The Neuroscientist 19(1), 88–100 (2013). https://doi.org/10.1177/1073858412445487

    Article  PubMed  Google Scholar 

  62. Shew, W.L., Yang, H., Petermann, T., Roy, R., Plenz, D.: Neuronal avalanches imply maximum dynamic range in cortical networks at criticality. J. Neurosci.: Off. J. Soc. Neurosci. 29(49), 15,595–600 (2009). https://doi.org/10.1523/JNEUROSCI.3864-09.2009. http://www.ncbi.nlm.nih.gov/pubmed/20007483. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3862241

    Article  CAS  Google Scholar 

  63. Shriki, O., Alstott, J., Carver, F., Holroyd, T., Henson, R.N.A., Smith, M.L., Coppola, R., Bullmore, E., Plenz, D.: Neuronal avalanches in the resting MEG of the human brain. J. Neurosci.: Off. J. Soc. Neurosci. 33(16), 7079–7090 (2013). https://doi.org/10.1523/JNEUROSCI.4286-12.2013

    Article  CAS  Google Scholar 

  64. Sillito, A.M., Grieve, K.L., Jones, H.E., Cudeiro, J., Davls, J.: Visual cortical mechanisms detecting focal orientation discontinuities. Nature 378, 492–496 (1995)

    Article  CAS  Google Scholar 

  65. Smirnov, N.: Table for Estimating the Goodness of Fit of Empirical Distributions. Ann. Math. Stat. 19(2), 279–281 (1948). https://doi.org/10.1214/aoms/1177730256

    Article  Google Scholar 

  66. Softky, W., Koch, C.: The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J. Neurosci. 13(1), 334–350 (1993). https://doi.org/10.1523/JNEUROSCI.13-01-00334.1993

    Article  CAS  PubMed  Google Scholar 

  67. Taylor, K., Mandon, S., Freiwald, W., Kreiter, A.: Coherent oscillatory activity in monkey area V4 predicts successful allocation of attention. Cereb. Cortex 15(9), 1424–1437 (2005). https://doi.org/10.1093/cercor/bhi023

    Article  CAS  PubMed  Google Scholar 

  68. Theeuwes, J.: Topdown and bottomup control of visual selection. Acta Psychol. 135(2), 77–99 (2010). https://doi.org/10.1016/J.ACTPSY.2010.02.006

    Article  Google Scholar 

  69. Thorpe, S., Fize, D., Marlot, C.: Speed of processing in the human visual system. Nature 381, 520–522 (1996). https://doi.org/10.1038/381520a0

    Article  CAS  PubMed  Google Scholar 

  70. Tinker, J., Velazquez, J.L.P.: Power law scaling in synchronization of brain signals depends on cognitive load. Front. Syst. Neurosci. 8, 73 (2014). https://doi.org/10.3389/fnsys.2014.00073

    Article  PubMed  PubMed Central  Google Scholar 

  71. Tomen, N., Rotermund, D., Ernst, U.: Marginally subcritical dynamics explain enhanced stimulus discriminability under attention. Front. Syst. Neurosci. 8, (2014). https://doi.org/10.3389/fnsys.2014.00151

  72. Treisman, A.M., Gelade, G.: A feature-integration theory of attention. Cogn. Psychol. 12(1), 97–136 (1980). https://doi.org/10.1016/0010-0285(80)90005-5

    Article  CAS  PubMed  Google Scholar 

  73. Treue, S., Maunsell, J.: Attentional modulation of visual motion processing in cortical areas mt and mst. Nature 382, 539–541 (1996)

    Article  CAS  Google Scholar 

  74. Vogels, T.P., Sprekeler, H., Zenke, F., Clopath, C., Gerstner, W.: Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science (New York, N.Y.) 334(6062), 1569–1573 (2011). https://doi.org/10.1126/science.1211095. http://www.ncbi.nlm.nih.gov/pubmed/22075724

    Article  CAS  Google Scholar 

  75. Wagemans, J., Elder, J.H., Kubovy, M., Palmer, S.E., Peterson, M.A., Singh, M., von der Heydt, R.: A century of Gestalt psychology in visual perception: I. Perceptual grouping and figure-ground organization. Psychol. Bull. 138(6), 1172–1217 (2012). https://doi.org/10.1037/a0029333. http://www.ncbi.nlm.nih.gov/pubmed/22845751 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC3482144

    Article  Google Scholar 

  76. Zapperi, S., Lauritsen, K.B., Stanley, H.E.: Self-organized branching processes: mean-field theory for avalanches. Phys. Rev. Lett. 75(22), 4071–4074 (1995). https://doi.org/10.1103/PhysRevLett.75.4071

    Article  CAS  Google Scholar 

  77. Zhang, X., Zhaoping, L., Zhou, T., Fang, F.: Neural activities in V1 create a bottom-up saliency map. Neuron 73(1), 183–192 (2012). https://doi.org/10.1016/J.NEURON.2011.10.035

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank Dr. Andreas Kreiter and his group for providing the data shown in Fig. 8b. This work has been supported by the Bundesministerium für Bildung und Forschung (BMBF, Bernstein Award Udo Ernst, Grant No. 01GQ1106).

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Tomen, N., Ernst, U. (2019). The Role of Criticality in Flexible Visual Information Processing. In: Tomen, N., Herrmann, J., Ernst, U. (eds) The Functional Role of Critical Dynamics in Neural Systems . Springer Series on Bio- and Neurosystems, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-030-20965-0_12

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