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Ensemble coding

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Ensemble Coding

Ensemble coding, also known as ensemble perception or summary representation, is the ability to see the average or variance of a group of objects. This is often referred to as taking summary statistical information. Put simply, it is a theory that suggests that people process the general gist of their complex visual surroundings by grouping them together based on their similarities. This process has been demonstrated that individuals have the ability quickly and accurately encode ensembles and gather summary statistical information. [1] [2] People are able to extract the gist of ensembles across various dimensions because the visual world is filled with redundant information. [3] Extant literature has shown that the visual system is particularly sensitive to similarities and organization that occurs naturally in our visual world.[4] Ensemble coding is an adaptive process that lightens cognitive effort in processing and storing visual representations.[5]


Ensemble Coding Defined

David Whitney and Allison Yamanashi Lieb developed an operational and flexible definition stating that, “...ensemble coding should include the following five concepts:

  • Ensemble perception is the ability to discriminate or reproduce a statistical moment.
  • Ensemble perception requires the integration of multiple items.
  • Ensemble information at each level of representation can be precise relative to the processing of single objects at that level.
  • Single-item recognition is not a prerequisite for ensemble coding.
  • Ensemble representations can be extracted with a temporal resolution at or beyond the temporal resolution of individual object recognition.” [3]


Opposing Theories

Some research has found countering evidence to the theory of ensemble coding.

Limited Visual Capacity

Vision science has noted that although humans take in large amounts of visual information, adults are only able to process, attend to, and hold in memory up to roughly four items from the visual environment. [6] [7] Furthermore, scientists have found that this visual upper limit capacity exists across various phenomena including change blindness, [8] [9] object-tracking, [10] and feature representation. [11]

Low Resolution Representations and Limited Capacity

Additional theories in vision science propose that stimuli are represented in the brain individually as small, low resolution, icons stored in templates with limited capacities and are organized through associative links. [12] [13]


Historical Context

Gestalt Theorists

Ensemble coding is a theory that was established by vision scientists, but is now used by various disciplines. Vision Scientists have expressed interest in how people perceive groups of objects for quite some time. This interest has developed from low-level perceptual processes to high-level perceptual processes spanning multiple disciplines.

The Current Era

Seminal findings by Dan Ariely in 2001 were the first data to support theories of ensemble coding. Ariely used novel experimental paradigms he labeled "mean discrimination" and "member identification" to examine how sets of objects are perceived. He conducted three studies involving shape ensembles that varied in size. Across all studies participants were able to accurately encode the mean size of the ensemble, but they were inaccurate when asked if a certain circle was apart of the set. Ariely's findings were the first that found statistical summary information emerge in the visual perception of grouped objects. [14]


Consistent with Ariely's findings,[14] follow up research conducted by Sang Chul Chong and Anne Treisman in 2003, provided evidence that participants are engaging in summary statistical processes. Their research revealed that participant's maintained high accuracy in encoding the mean size of the stimuli even with short stimuli presentations (50ms), memory delays, and circle distribution differences. [15]


Additional work has demonstrated that ensemble coding isn't limited to the mean, [14] but line orientation, [16] spatial ___location, [17] number, [18] and additional statistical summaries like the variances[19] are detected.

"Over all this research pointed to our visual system's profound flexibility in extracting the gist or summary of a group of stimuli, offering a parsimonious explanation to long established cognitive and visual limitations"

Levels of Ensemble Coding

People have the ability to encode summary statistics along various dimensions of ensemble coding. [3]

Low-Level

Low-level ensemble coding has been observed in the perception of size, [15] motion, [20] [21] number, [18] line orientation, [16] and spacial ___location. [17] [3]

High-Level

High-level ensemble coding involves social perception. [3]

Social Ensemble Coding

History

Social Vision of groups and social categorization



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  1. ^ Alt, Nicholas P.; Goodale, Brianna; Lick, David J.; Johnson, Kerri L. (2019-03). "Threat in the Company of Men: Ensemble Perception and Threat Evaluations of Groups Varying in Sex Ratio". Social Psychological and Personality Science. 10 (2): 152–159. doi:10.1177/1948550617731498. ISSN 1948-5506. {{cite journal}}: Check date values in: |date= (help)
  2. ^ Alvarez, George (2011-03). "Representing Multiple Objects as an Ensemble Enhances Visual Cognition". Trends in Cognitive Sciences. doi:10.1016/j.tics.2011.01.003. ISSN 1364-6613. {{cite journal}}: Check date values in: |date= (help)
  3. ^ a b c d e Whitney, David; Yamanashi Leib, Allison (2018). "Ensemble Perception". Annual Review of Psychology. 69 (1): 105–129. doi:10.1146/annurev-psych-010416-044232. PMID 28892638.
  4. ^ Whitney D, Haberman J, Sweeny T. 2014. From textures to crowds: multiple levels of summary statistical perception. In The New Visual Neuroscience, ed. JS Werner, LM Chalupa, pp. 695–710. Cambridge, MA: MIT Press
  5. ^ Haberman, Jason; Whitney, David (2009-6). "Seeing the mean: Ensemble coding for sets of faces". Journal of experimental psychology. Human perception and performance. 35 (3): 718–734. doi:10.1037/a0013899. ISSN 0096-1523. PMC 2696629. PMID 19485687. {{cite journal}}: Check date values in: |date= (help)
  6. ^ Alvarez, G.A.; Cavanagh, P. (2004-02). "The Capacity of Visual Short-Term Memory is Set Both by Visual Information Load and by Number of Objects". Psychological Science. 15 (2): 106–111. doi:10.1111/j.0963-7214.2004.01502006.x. ISSN 0956-7976. {{cite journal}}: Check date values in: |date= (help)
  7. ^ Luck, Steven J.; Vogel, Edward K. (1997-11). "The capacity of visual working memory for features and conjunctions". Nature. 390 (6657): 279–281. doi:10.1038/36846. ISSN 1476-4687. {{cite journal}}: Check date values in: |date= (help)
  8. ^ O'Regan, J. Kevin; Deubel, Heiner; Clark, James J.; Rensink, Ronald A. (2000-01-01). "Picture Changes During Blinks: Looking Without Seeing and Seeing Without Looking". Visual Cognition. 7 (1–3): 191–211. doi:10.1080/135062800394766. ISSN 1350-6285.
  9. ^ Simons, Daniel J.; Chabris, Christopher F. (1999-09-01). "Gorillas in Our Midst: Sustained Inattentional Blindness for Dynamic Events:". Perception. doi:10.1068/p281059.
  10. ^ Scholl, Scholl, B. J., Pylyshyn, B. J. (1999). Tracking Multiple Items Through Occlusion: Clues to Visual Objecthood. Cognitive psychology, 38(2), 259-290.
  11. ^ Luck, Steven J.; Vogel, Edward K. (1997-11). "The capacity of visual working memory for features and conjunctions". Nature. 390 (6657): 279–281. doi:10.1038/36846. ISSN 1476-4687. {{cite journal}}: Check date values in: |date= (help)
  12. ^ Adler, K.; Pointon, M. (1993-05-13). Vision: Coding and Efficiency. Cambridge University Press. ISBN 978-0-521-44769-0.
  13. ^ Neisser, U. (1967). Cognitive psychology. New York: Appleton-Cent
  14. ^ a b c Ariely, Dan (2001). "Seeing Sets: Representation by Statistical Properties". Psychological Science. 12 (2): 157–162. ISSN 0956-7976.
  15. ^ a b Chong, Sang Chul; Treisman, Anne (2003-02-01). "Representation of statistical properties". Vision Research. 43 (4): 393–404. doi:10.1016/S0042-6989(02)00596-5. ISSN 0042-6989.
  16. ^ a b Dakin, S. C.; Watt, R. J. (1997-11-01). "The computation of orientation statistics from visual texture". Vision Research. 37 (22): 3181–3192. doi:10.1016/S0042-6989(97)00133-8. ISSN 0042-6989.
  17. ^ a b Alvarez, George A.; Oliva, Aude (2008-04-01). "The Representation of Simple Ensemble Visual Features Outside the Focus of Attention". Psychological Science. 19 (4): 392–398. doi:10.1111/j.1467-9280.2008.02098.x. ISSN 0956-7976. PMC 2587223. PMID 18399893.{{cite journal}}: CS1 maint: PMC format (link)
  18. ^ a b Halberda, Justin; Sires, Sean F.; Feigenson, Lisa (2006-07-01). "Multiple Spatially Overlapping Sets Can Be Enumerated in Parallel". Psychological Science. 17 (7): 572–576. doi:10.1111/j.1467-9280.2006.01746.x. ISSN 0956-7976.
  19. ^ Solomon, Joshua A.; Morgan, Michael; Chubb, Charles (2011-10-01). "Efficiencies for the statistics of size discrimination". Journal of Vision. 11 (12): 13–13. doi:10.1167/11.12.13. ISSN 1534-7362. PMC 4135075. PMID 22011381.{{cite journal}}: CS1 maint: PMC format (link)
  20. ^ Watamaniuk, Scott N. J.; Sekuler, Robert; Williams, Douglas W. (1989-01-01). "Direction perception in complex dynamic displays: The integration of direction information". Vision Research. 29 (1): 47–59. doi:10.1016/0042-6989(89)90173-9. ISSN 0042-6989.
  21. ^ Watamaniuk, Scott N. J.; McKee, Suzanne P. (1998-01-01). "Simultaneous encoding of direction at a local and global scale". Perception & Psychophysics. 60 (2): 191–200. doi:10.3758/BF03206028. ISSN 1532-5962.
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