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A Cognitive Model of Saliency, Attention, and Picture Scanning

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Abstract

To view and understand the visual world, we shift our gaze from one location to another about three times per second. These rapid changes in gaze direction result from very fast eye movements called saccades. Visual information is acquired only during fixations, stationary periods between saccades. Active visual search of pictures is the process of active scanning of the visual environment for a particular target among distracters or for the extraction of its meaning. This article discusses a cognitive model of saliency, overt attention, and natural picture scanning that unravels the neurocomputational mechanisms of how human gaze control operates during active real-world scene viewing.

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References

  1. Berman RA, Wurtz RH. Exploring the pulvinar path to visual cortex. Prog Brain Res. 2008;171:467–73.

    Article  PubMed  Google Scholar 

  2. Carpenter GA, Grossberg S. Adaptive resonance theory. In: Arbib MA, editor. The handbook of brain theory and neural networks. 2nd ed. Cambridge: MIT Press; 2003. p. 87–90.

    Google Scholar 

  3. Chelazzi L, Duncan J, Miller EK, Desimone R. Responses of neurons in the inferior temporal cortex during memory guided visual search. J Neurophysiol. 1998;80(6):2918–40.

    CAS  PubMed  Google Scholar 

  4. Coizet V, Comoli E, Westby GW, Redgrave P. Phasic activation of substantia nigra and the ventral tegmental area by chemical stimulation of the superior colliculus: an electrophysiological investigation in the rat. Eur J Neurosci. 2003;17(1):28–40.

    Article  PubMed  Google Scholar 

  5. Comoli E, Coizet V, Boyes J, Bolam JP, Canteras NS, Quirk RH, et al. A direct projection from the superior colliculus to substantia nigra for detecting salient visual events. Nat Neurosci. 2003;6(9):974–80.

    Article  CAS  PubMed  Google Scholar 

  6. Cutsuridis V, Kahramanoglou I, Perantonis S, Evdokimidis I, Smyrnis N. A biophysical model of decision making in an antisaccade task through variable climbing activity. In: Duch W, et al., editors. ICANN 2005. LNCS, vol. 3695. Berlin: Springer; 2005. p. 205–10.

  7. Cutsuridis V, Perantonis S. A neural network model of Parkinson’s disease bradykinesia. Neural Netw. 2006;19(4):354–74.

    Article  PubMed  Google Scholar 

  8. Cutsuridis V. Neural model of dopaminergic control of arm movements in Parkinson’s disease bradykinesia. In: Kollias SD, Stafylopatis A, Duch W, Oja E, editors. ICANN 2006. LNCS, vol. 4131. Heidelberg: Springer; 2006. p. 583–91.

  9. Cutsuridis V. Does reduced spinal reciprocal inhibition lead to co-contraction of antagonist motor units? A modeling study. Int J Neural Syst. 2007;17(4):319–27.

    Article  PubMed  Google Scholar 

  10. Cutsuridis V, Kahramanoglou I, Smyrnis N, Evdokimidis I, Perantonis S. A neural variable integrator model of decision making in an antisaccade task. Neurocomputing. 2007;70(7–9):1390–402.

    Article  Google Scholar 

  11. Cutsuridis V, Smyrnis N, Evdokimidis I, Perantonis S. A neural network model of decision making in an antisaccade task by the superior colliculus. Neural Netw. 2007;20(6):690–704.

    Article  PubMed  Google Scholar 

  12. Cutsuridis V. A bio-inspired system architecture of an active visual search model. In: Kurkova V, Neruda R, Koutnik J, editors. ICANN 2008, LNCS vol. 5164. Berlin: Springer; 2008. p. 248–57.

  13. Cutsuridis V. Neural network modeling of voluntary single joint movement organization. I. Normal conditions. In: Chaovalitwongse WA, Pardalos P, Xanthopoulos P, editors. Computational neuroscience. Berlin: Springer-Verlag; 2010.

    Google Scholar 

  14. Cutsuridis V. Neural network modeling of voluntary single joint movement organization. II. Parkinson’s disease. In: Chaovalitwongse WA, Pardalos P, Xanthopoulos P, editors. Computational neuroscience. Berlin: Springer-Verlag; 2010.

    Google Scholar 

  15. Deco G, Schürmann B. A neuro-cognitive visual system for object recognition based on testing of interactive attentional top-down hypotheses. Perception. 2000;29(10):1249–64.

    Article  CAS  PubMed  Google Scholar 

  16. Desimone R, Duncan J. Neural mechanisms of selective visual attention. Ann Rev Neurosci. 1995;18:193–222.

    Article  CAS  PubMed  Google Scholar 

  17. Dommett E, Coizet V, Blaha CD, Martindale J, Lefebre V, Walton N, et al. How visual stimuli activate dopaminergic neurons at short latency. Science. 2005;307(5714):1476–9.

    Article  CAS  PubMed  Google Scholar 

  18. Egner T, Hirsch J. Cognitive control mechanisms resolve conflict through cortical amplification of task relevant information. Nat Neurosci. 2005;8(12):1784–90.

    Article  CAS  PubMed  Google Scholar 

  19. Fazl A, Grossberg S, Mingolla E. View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds. Cogn Psychol. 2009;58(1):1–48.

    Article  PubMed  Google Scholar 

  20. Findlay JM, Gilchrist ID. Active vision: the psychology of looking and seeing. Oxford: Oxford University Press; 2003.

    Google Scholar 

  21. Foxe JJ, Simpson GV. Flow of activation from V1 to frontal cortex in humans. Exp Brain Res. 2002;142:139–50.

    Article  PubMed  Google Scholar 

  22. Hamker FH. The re-entry hypothesis: the putative interaction of the frontal eye field, ventrolateral prefrontal cortex and areas V4, IT of attention and eye movement. Cereb Cortex. 2005;15:431–47.

    Article  PubMed  Google Scholar 

  23. Hanes DP, Wurtz RH. Interaction of frontal eye field and superior colliculus for saccade generation. J Neurophys. 2001;85:804–15.

    CAS  Google Scholar 

  24. Henderson JM, Hollingworth A. The role of fixation position in detecting scene changes across saccades. Psychol Sci. 1999;50:243–71.

    CAS  Google Scholar 

  25. Hikosaka O, Wurtz RH. Visual and oculomotor functions of monkey substantia nigra pars reticulate. J Neurophys. 1983;49:1230–301.

    CAS  Google Scholar 

  26. Hikosaka O, Takikawa Y, Kawagoe R. Role of the basal ganglia in the control of purposive saccadic eye movements. Physiol Rev. 2000;80:954–78.

    Google Scholar 

  27. Itti L, Koch C. Computational modelling of visual attention. Nat Neurosci. 2001;2:194–203.

    Article  CAS  Google Scholar 

  28. Itti L, Koch C. A saliency based search mechanism for overt and covert shifts of visual attention. Vision Res. 2000;40:1489–506.

    Article  CAS  PubMed  Google Scholar 

  29. Klein RM. Inhibition of return. Trends Cogn Sci. 2000;4(4):138–47.

    Article  PubMed  Google Scholar 

  30. Koch C, Ullman S. Shifts in selective visual attention: towards the underlying neural circuitry. Hum Neurobiol. 1995;4:219–27.

    Google Scholar 

  31. Kusunoki M, Gottlieb J, Goldberg ME. The lateral intraparietal area as a salience map: the representation of abrupt onset, stimulus motion and task relevance. Vision Res. 2000;40:1459–68.

    Article  CAS  PubMed  Google Scholar 

  32. Lleras A, Von Mühlenen A. Spatial context and top-down strategies in visual search. Spat Vis. 2004;17(4–5):465–82.

    Article  PubMed  Google Scholar 

  33. McHaffie JG, Jiang H, May PJ, Coizet V, Overton PG, Stein BE, et al. A direct projection from superior colliculus to substantia nigra pars compacta in the cat. Neuroscience. 2006;138(1):221–34.

    Article  CAS  PubMed  Google Scholar 

  34. Mohler CW, Wurtz RH. Role of striate cortex and superior colliculus in visual guidance of saccadic eye movements in monkeys. J Neurophyiol. 1977;40:74–94.

    CAS  Google Scholar 

  35. Olshausen BA, Anderson CH, van Essen DC. A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information. J Neurosci. 1993;13(11):4700–19.

    CAS  PubMed  Google Scholar 

  36. Reynolds JH, Desimone R. The role of neural mechanisms of attention in solving the binding problem. Neuron. 1999;24(1):19–29.

    Article  CAS  PubMed  Google Scholar 

  37. Redgrave P, Gurney K. The short latency dopamine signal: a role in discovering novel actions. Nat Neurosci. 2006;7:967–75.

    Article  CAS  Google Scholar 

  38. Redgrave P, Gurney K, Reinolds J. What is reinforced by the phasic dopamine signals? Brain Res Rev. 2008;58(2):322–39.

    Article  CAS  PubMed  Google Scholar 

  39. Rybak IA, Gusakova VI, Golovan AV, Podladchikova LN, Shevtsova NA. A model of attention-guided visual perception and recognition. Vision Res. 1998;38(15–16):2387–400.

    Article  CAS  PubMed  Google Scholar 

  40. Schall JD, Hanes DP, Thompson KG, King DJ. Saccade target selection in frontal eye field of macaque. I. Visual and premovement activation. J Neurosci. 1995;15:6905–18.

    CAS  PubMed  Google Scholar 

  41. Schiller PH, True SD, Conway JL. Deficits in eye movements following frontal eye field and superior colliculus ablations. J Neurophys. 1980;44:1175–89.

    CAS  Google Scholar 

  42. Schultz W. Predictive reward signal of dopamine neurons. J Neurophys. 1998;80:1–27.

    CAS  Google Scholar 

  43. Sommer MA, Wurtz RH. Frontal eye field neurons orthodromically activated from the superior colliculus. J Neurophys. 1998;80:3331–3.

    CAS  Google Scholar 

  44. Tavassoli A, Linde I, Bovik AC, Cormack LK. Eye movements selective for spatial frequency and orientation during active visual search. Vision Res. 2009;49(2):173–81.

    Article  CAS  PubMed  Google Scholar 

  45. Taylor JG, Hartley M, Taylor N, Panchev C, Kasderidis S. A hierarchical attention-based neural network architecture, based on human brain guidance, for perception, conceptualisation, action and reasoning. Image Vis Comput. 2009;27:1641–57.

    Article  Google Scholar 

  46. Thompson KG, Bichot NP. A visual saliency map in the primate frontal eye field. Prog Brain Res. 2005;147:251–62.

    PubMed  Google Scholar 

  47. Thorpe S, Fize D, Marlot C. Speed of processing in the human visual system. Nature. 1996;381(6582):520–2.

    Article  CAS  PubMed  Google Scholar 

  48. Tsotsos JK, Culhane S, Wai W, Lai Y, Davis N, Nuflo F. Modeling visual attention via selective tuning. Artif Intell. 1995;78(1–2):507–47.

    Article  Google Scholar 

  49. Viviani P. Eye movements in visual search. Cognitive, perceptual and motor control aspects. In: Kowler E, editor. Eye movements and their role in visual and cognitive processes. Amsterdam: Elsevier; 1990. p. 353–93.

    Google Scholar 

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Acknowledgment

V.C. was supported by the EPSRC Project Grant EP/D04281X/1.

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Correspondence to Vassilis Cutsuridis.

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Cutsuridis, V. A Cognitive Model of Saliency, Attention, and Picture Scanning. Cogn Comput 1, 292–299 (2009). https://doi.org/10.1007/s12559-009-9024-9

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