ru
Back
УДК: 004.93'12, 004.932, 007.51, 159.93
Image perception in visual-search tasks when dynamic noise is present
Full text «Opticheskii Zhurnal»
Full text on elibrary.ru
Publication in Journal of Optical Technology
Хараузов А.К., Васильев П.П., Соколов А.В., Шелепин Ю.Е., Кувалдина М.Б., Борачук О.В., Фокин В.А., Пронин С.В. Восприятие изображений в задачах зрительного поиска в условиях динамической помехи // Оптический журнал. 2015. Т. 82. № 5. С. 42–55.
Kharauzov A.K., Vasiliev P.P., Sokolov A.V., Shelepin Yu.E., Kuvaldina M.B., Borachuk O.V., Fokin V.A., Pronin S.V. Image perception in visual-search tasks when dynamic noise is present [in Russian] // Opticheskii Zhurnal. 2015. V. 82. № 5. P. 42–55.
A. K. Kharauzov, P. P. Vasil’ev, Yu. E. Shelepin, S. V. Pronin, A. V. Sokolov, V. A. Fokin, M. B. Kuvaldina, and O. V. Borachuk, "Image perception in visual-search tasks when dynamic noise is present," Journal of Optical Technology. 82(5), 298-307 (2015). https://doi.org/10.1364/JOT.82.000298
The methods of neuroiconics and functional magnetic-resonance tomography are used to investigate the factors that limit the possibilities of visual search. The influence of an image of a human face hidden in the background on the activity of the observer’s brain was recorded during the task of tracking a moving ring. It is established that images are unconsciously perceived under threshold-presentation conditions, and this is reflected in the activation of the fusiform gyrus—a region of the brain that participates in face recognition. Under above-threshold presentation conditions, the parietal and frontal regions of the brain were also activated, but activity in this case decreased in the auditory, motor, and certain other regions of the brain not occupied in signal processing. The resulting data reveal the significance of the background semantics under conditions of visual search and explain how the unconsciously perceived optical characteristics of a background image can affect the operator’s functional state.
visual search, image synthesis, inattentional blindness, brain activity patterns, fMRT
Acknowledgements:This work was supported by grants of the Russian Humanitarian Scientific Foundation No. 12-06-00947 (digital synthesis of images, processing of a BOLD signal) and a grant of the Russian Scientific Foundation No. 14-15-00918 (preparation and performance of fMRT measurements).
OCIS codes: 100.4999, 100.6950, 330.5000
References:1. S. E. Zdor and V. B. Shirokov, Optical Search and Recognition (Nauka, Moscow, 1973).
2. N. P. Travnikova, Efficiency of Visual Search (Mashinostroenie, Moscow, 1985).
3. A. Mack and I. Rock, Inattentional Blindness (MIT, Cambridge, Mass, 1998).
4. D. Simons and C. Chabris, “Gorillas in our midst: sustained inattentional blindness for dynamic events,” Perception 28, 1059 (1999).
5. S. Most, D. Simons, B. Steven, B. Scholl, R. Jimenez, E. Clifford, and C. Chabris, “How not to be seen: the contribution of similarity and selective ignoring to sustained inattentional blindness,” Psychol. Sci. 12, No. 1, 9 (2001).
6. S. Most, B. Scholl, E. Clifford, and D. Simons, “What you see is what you set: sustained inattentional blindness and the capture of awareness,” Psychol. Rev. 112, No. 1, 217 (2005).
7. R. O’Reilly, “The what and how of prefrontal cortical organization,” Trends Neurosci. 33, 355 (2010).
8. M. Berman, J. Park, R. Gonzalez, T. Polk, A. Gehrke, S. Knaffla, and J. Jonides, “Evaluating functional localizers: the case of the FFA,” NeuroImage 50, No. 1, 56 (2010).
9. B. Rossion, B. Hanseeuw, and L. Dricot, “Defining face perception areas in the human brain: a large-scale factorial fMRI face localizer analysis,” Brain Cognit. 79, 138 (2012).
10. Ya. Kulikovskiı˘ and É. Robson, “Spatial, temporal and chromatic channels: electrophysiological foundations,” Opt. Zh. 66, No. 9, 37 (1999) [J. Opt. Technol. 66, 797 (1999)].
11. M. W. Levine and J. M. Shefner, Fundamentals of Sensation and Perception (Oxford University, Oxford, 2005).
12. L. Ungerleider and M. Mishkin, “Two cortical visual systems,” in The Analysis of Visual Behavior, eds. D. J. Ingle, M. A. Goodale, and R. J. W. Mansfield (MIT, Cambridge, Mass, 1982), pp. 549–586.
13. F. Wilson, S. Scalaidhe, and P. Goldman-Rakic, “Dissociation of object and spatial processing domains in primate prefrontal cortex,” Science 25, No. 5116, 1955 (1993).
14. G. Borst, W. Thompson, and S. Kosslyn, “Understanding the dorsal and ventral systems of the human cerebral cortex: beyond dichotomies,” Am. Psychol. 66, 624 (2011).
15. K. Volz, R. Schubotz, and D. Yves von Cramon, “Variants of uncertainty in decision-making and their neural correlates,” Brain Res. Bull. 67, 403 (2005).
16. E. Koechlin and A. Hyafil, “Anterior prefrontal function and the limits of human-decision making,” Science 318, 594 (2007).
17. R. Buckner, J. Andrews-Hanna, and D. Schacter, “The brain’s default network,” Ann. N. Y. Acad. Sci. 1124, 1 (2008).
18. M. Raichle and A. Snyder, “A default mode of brain function: a brief history of an evolving idea,” NeuroImage 37, 1083 (2007).
19. A. Fornito, B. Harrison, A. Zalesky, and J. Simons, “Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection,” Proc. Nat. Acad. Sci. 109, 12788 (2012).
20. S. Gilbert, G. Bird, C. Frith, and P. Burgess, “Does ‘task difficulty’ explain ‘task-induced deactivation?’” Front. Psychol. 3, No. A125, 1 (2012).
21. C. Preibisch and A. Haase, “Perfusion imaging using spin-labeling methods: contrast-to-noise comparison in functional MRI applications,” Magn. Reson. Med. 46, 172 (2001).
22. E. Rostrup, I. Law, M. Blinkenburg, H. Larsson, A. Born, S. Holm, and O. Paulson, “Regional differences in the CBF and BOLD response to hypercapnia: a combined PET and fMRI study,” NeuroImage 11, 87 (2000).
23. N. Logothetis and B. Wandell, “Interpreting the BOLD signal,” Ann. Rev. Physiol. 66, 735 (2004).
24. P. Matthews, “An introduction to functional magnetic resonance imaging of the brain,” in Functional MRI: an Introduction to Methods, eds. P. Jezzard, P. M. Matthews, and S. M. Smith (Oxford University, Oxford, 2002), pp. 3–34.
25. E. Mazerolle, R. D’Arcy, and D. S. Beyea, “Detecting functional magnetic resonance imaging activation in white matter: interhemispheric transfer across the corpus callosum,” BMC Neurosci. 9, No. 84, 1 (2008).
26. K. Omura, T. Tsukamoto, Y. Kotani, Y. Ohgami, M. Minami, and Y. Inoue, “Different mechanisms involved in interhemispheric transfer of visuomotor information,” NeuroReport 15, 2707 (2004).
27. M. Dieterich, S. Bense, T. Stephan, T. Yousry, and T. Brandt, “fMRI signal increases and decreases in cortical areas during small-field optokinetic stimulation and central fixation,” Exp. Brain Res. 148, No. 1, 117 (2003).
28. V. R. Lutsiv, “Object-independent approach to the structural analysis Fof images,” Opt. Zh. 75, No. 11, 26 (2008) [J. Opt. Technol. 75, 708 (2008)].
29. V. R. Lutsiv and T. A. Novikova, “Modeling attention zones on the basis of an analysis of local features of the image texture,” Opt. Zh. 75, No. 7, 55 (2008) [J. Opt. Technol. 75, 449 (2008)].