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WD_402/ 2007
(  Satoshi Kinoshita )
| Series: | Works on paper: Drawings 5 | | Medium: | oilstick on paper | | Size (inches): | 31.1 x 21.4 | | Size (mm): | 790 x 544 | | Catalog #: | WD_0402 | | Description: | Signed, date and copyright in pencil on the reverse.
LORD GORING: My dear Robert, it's a very awkward business, very awkward indeed. You should have told your wife the whole thing. Secrets from other people's wives are a necessary luxury in modern life. So, at least, I am always told at the club by people who are bald enough to know better. But no man should have a secret from his own wife. She invariably finds it out. Women have a wonderful instinct about things. They can discover everything except the obvious.
From An Ideal Husband (1895) by Oscar Wilde.
-www.literaturepage.com/read/
an-ideal-husband-32.html
Change blindness -
In visual perception, change blindness is the phenomenon where a person viewing a visual scene apparently fails to detect large changes in the scene. For change blindness to occur, the change in the scene typically has to coincide with some visual, disruption such as a saccade (eye movement) or a brief obscuration of the observed scene or image. When looking at still images, change blindness can be achieved by changing a part of the image in 13 seconds or longer.
The first explorations of change blindness appear to have been conducted by George McConkie and his colleagues in the late 1970s, focusing on changes made to words and text during saccadic eye movements. A student of McConkie's, John Grimes, extended this phenomenon to the domain of scene perception (in a conference presentation in 1992, later published in a book chapter in 1996). Grimes showed that people miss large changes to scenes when the changes are introduced during an eye movement. For example, many people failed to notice when two people in a scene exchanged heads. In these saccade-contingent change blindness studies, changes to the scene were synchronized with measured movements of the observer's eyes, so that the changes occurred only when the eyes were moving. Under these conditions, changes are often hard to detect. (For more recent studies of saccade-contingent change blindness, see Henderson & Hollingworth, 1999, and McConkie & Currie, 1996.)
Beginning in the late 1980s, research began to reveal that other forms of visual disruption besides eye movements could also induce relatively poor change detection. Pashler (1988) showed that observers were quite poor at detecting changes introduced into arrays of letters while the display was flickered off and on, even if the offset was as brief as 67 milliseconds (although offsets briefer than that produced better change detection). He concluded by noting that people report having a "clear sense of apprehending the identities and locations of large numbers of objects in a scene" (p. 377), and that given these introspections, it seemed surprising that people's ability to detect changes proved to be so poor.
Later, Rensink et al, popularized the "flicker" technique in which two images of scenes alternate repeatedly with a brief (80 millisecond) blank screen after each image, giving the display a flickering appearance. With the blank screen in place, surprisingly large changes could be made to the scene without the observer reliably noticing them. Rensink et al (1997) also introduced the term "change blindness."
Other studies showed that change detection is also poor when the change is introduced during a cut or pan in a motion picture, even when the change is to the central actor in a scene (Levin & Simons, 1997). People also regularly fail to notice editing errors in commercial movies, despite the intense scrutiny of movies during the production process.
Change blindness can be particularly dramatic when changes occur unexpectedly, with many observers even failing to notice when a person they were talking to was surreptitiously replaced by a different actor (Simons & Levin, 1998). Change blindness has now been shown to occur with a wide variety of visual disruptions (e.g., blinks, transient noise flashed on a display, etc).
Causes and relationship to other phenomena:
Change blindness may be related to other induced failures of awareness, such as inattentional blindness. A crucial difference is that successful change detection in the presence of a visual disruption requires a comparison of one image to another one held in memory. Consequently, change blindness can occur due to a failure to store the information in the first place or to a failure to compare the relevant information from the current scene to the representation (hence models of visual short term memory may be important for understanding the phenomenon). In contrast, inattentional blindness reflects the failure to detect an unexpected stimulus that is fully visible in a single display – it does not require a comparison to memory.
It has been shown that change blindness can even occur immediately after an observer has identified all of the objects in a display. Becker and Pashler (2002) had observers name the highest digit in an array of digits exposed for 2 seconds, at which time the display flickered off and on (with one of the digits changed). Even though observers were almost perfect at naming the highest digit in the initial display, they were still performing at the usual, relatively low, level in spotting the change. When the highest digit itself changed, though, this change was almost always noticed.
References:
* Becker, Mark & Pashler, Harold (2002), Volatile visual representations: Failing to detect changes in recently processed information., Psychonomic Bulletin and Review 9: 744-750.
* Grimes, J. (1996), "On the failure to detect changes in scenes across saccades", in Akins, K., Perception (Vancouver Studies in Cognitive Science), vol. 2, New York: Oxford University Press, pp. 89-110.
* Henderson, John M. & Hollingworth, Andrew (1999), The role of fixation position in detecting scene changes across saccades, Psychological Science 10: 438-443.
* Levin, Daniel T. & Simons, Daniel J. (1997), Failure to detect changes to attended objects in motion pictures, Psychonomic Bulletin and Review 4: 501-506.
* McConkie, George W. & Currie, C. B. (1996), Visual stability across saccades while viewing complex pictures, Journal of Experimental Psychology: Human Perception & Performance 22 (3): 563-581.
* Pashler, Harold E. (1988), Familiarity and the detection of change in visual displays, Perception & Psychophysics 44: 369-378.
* Rensink, Ronald A.; O'Regan, J. Kevin & Clark, James J. (1997), To see or not to see: the need for attention to perceive changes in scenes, Psychological Science 8 (5): 368-373.
* Silverman, M. & Mack, A. (2006), Priming by change blindness: When it does and does not occur, Consciousness and Cognition 15: 409-422.
* Simons, Daniel J. & Levin, Daniel T. (1998), Failure to detect changes to people during a real-world interaction, Psychonomic Bulletin and Review 5: 644-649.
-en.wikipedia.org/wiki/Change_blindness
Inattentional blindness -
Inattentional blindness, also known as perceptual blindness which is the phenomenon of not being able to see things that are actually there. This can be a result of having no internal frame of reference to perceive the unseen objects, or it can be the result of the mental focus or attention which cause mental distractions. The phenomenon is due to how our minds see and process information. Closely related to the subject of change blindness, is an observed phenomenon of the inability to perceive features in a visual scene when the observer is not attending to them. That is to say that humans have a limited capacity for attention which thus limits the amount of information processed at any particular time. Any otherwise salient feature within the visual field will not be observed if not processed by attention.
Also related to this is the phenomena of blind people who later in life gain sight. Their processing of the visual stimuli does not allow them to identify objects easily, effectively they can see but are still perceptually blind.
Experiments demonstrating inattentional blindness:
The term inattentional blindness was coined by Arien Mack and Irvin Rock in 1992. It was used as the title of Rock's last text published in 1998 by the MIT Press.
The most well known study demonstrating inattentional blindness was conducted by Daniel Simons of the University of Illinois at Urbana-Champaign and Christopher Chabris of Harvard University. Their study, a contemporized version of earlier studies conducted by Ulric Neisser , asked subjects to watch a short video [1] in which two groups of people (wearing black and white t-shirts) pass a basketball back among themselves. The subjects are told to either count the number of passes made by one of the teams, or to keep count of bounce passes vs. aerial passes. In different versions of the video a woman walks through the scene carrying an umbrella, or wearing a full gorilla suit. In one version the woman in the gorilla suit even stops in the middle, faces the camera, and pounds her chest before walking out of the scene. After watching the video the subjects are asked if they saw anything out of the ordinary take place. In most groups 50% of the subjects did not report seeing the gorilla. Simons interprets this by stating that we are mistaken with regard to how important events will automatically draw our attention away from current tasks or goals. This result indicates that the relationship between what is in our visual field and perception is based much more significantly on attention than was previously thought.
Another experiment was carried out by Steve Most, Chabis and Scholl. They had objects moving randomly on a computer screen. Participants were instructed to attend to the black objects and ignore the white, or vice versa. After several trials, a red cross unexpectedly appeared and traveled across the display, remaining on the computer screen for five seconds. The results of the experiment showed that even though the cross was distinctive from the black and white objects both in color and shape, about a third of participants nonetheless missed it. They had found that people may be attentionally tuned to certain perceptual dimensions, such as brightness or shape.
Current research:
A good review is Chun & Marois (2002) The dark side of visual attention. Current Opinion in Neurobiology, Volume 12, Issue 2, 1 April 2002, Pages 184-189
Exploitations:
Inattentional blindness is exploited by illusionists in the presentation of "magic shows" in the performance of some tricks by focusing the audience attention upon some distractive element, away from elements of the scene under manipulation by the performer. This is called misdirection amongst magicians.
-en.wikipedia.org/wiki/Inattentional_blindness
Visual short term memory -
In the study of vision, visual short-term memory (VSTM) is one of three broad memory systems including iconic memory and long-term memory. VSTM is a type of short-term memory, but one limited to information within the visual domain.
The term VSTM refers in a theory-neutral manner to the non-permanent storage of visual information over an extended period of time. The Visuospatial Sketchpad is a VSTM subcomponent within the theoretical model of working memory proposed by Alan Baddeley.
Whereas iconic memories are fragile, decay rapidly, and are unable to be actively maintained, visual short-term memories are robust to subsequent stimuli and last over many seconds.
Overview:
The introduction of stimuli which were hard to verbalize, and unlikely to be held in long-term memory, revolutionized the study of visual short-term memory (VSTM) in the early 1970s (Cermak, 1971; Phillips, 1974; Phillips & Baddeley, 1971). The basic experimental technique used required observers to indicate whether two matrices (Phillips, 1974; Phillips &Baddeley, 1971), or figures (Cermak, 1971), separated by a short temporal interval, were the same. The finding that observers were able to report that a change had occurred, at levels significantly above chance, indicated that they were able to encode some aspect of the first stimulus in a purely visual store, at least for the period until the presentation of the second stimulus. However, as the stimuli used were complex, and the nature of the change relatively uncontrolled, these experiments left open various questions, such as: (1) whether only a subset of the perceptual dimensions comprising a visual stimulus are stored (e.g., spatial frequency, luminance, or contrast); (2) whether some perceptual dimensions are maintained in VSTM with greater fidelity than others; and (3) the nature by which these dimensions are encoded (i.e., are perceptual dimensions encoded within separate, parallel channels, or are all perceptual dimensions stored as a single bound entity within VSTM?).
Set-size effects in VSTM:
In a typical VSTM experiment, observers are presented with two arrays, composed of a number of stimuli. The two arrays are separated by a short temporal interval, and the task of observers is to decide if the first and second arrays are composed of identical stimuli, or whether one item differs across the two displays (e.g., Luck & Vogel, 1997). Increasing the number of stimuli present within the two arrays leads to a monotonic decrease in the sensitivity of observers to differences in stimuli across the two arrays (Luck & Vogel, 1997; Pashler, 1988). This capacity limit has been linked to the posterior parietal cortex, the activity of which increases with the number of stimuli in the arrays, but only up to the capacity limit of about four stimuli (Todd & Marois, 2004). There are a number of frameworks that attempt to explain the effect of increasing set-size on performance in VSTM. These can be broadly grouped under three categories: (1) psychophysical frameworks (e.g., Magnussen & Greenlee, 1997); (2) sample size models (e.g., Palmer, 1990); and (3) urn models (e.g., Pashler, 1988).
Problems with psychophysical explanations:
Psychophysical experiments suggest that information is encoded in VSTM across multiple parallel channels, each channel associated with a particular perceptual attribute (Magnussen, 2000). Within this framework, a decrease in an observer's ability to detect a change with increasing set-size can be attributed to two different processes: (1) if decisions are made across different channels, decreases in performance are typically small, and consistent with decreases expected when making multiple independent decisions (Greenlee & Thomas, 1993; Vincent & Regan, 1995); (2) if multiple decisions are made within the same channel, the decrease in performance is much greater than expected on the basis of increased decision-noise alone, and is attributed to interference caused by multiple decisions within the same perceptual channel (Magnussen & Greenlee, 1997).
However, the Greenlee-Thomas model (Greenlee & Thomas, 1993) suffers from two failings as a model for the effects of set-size in VSTM. First, it has only been empirically tested with displays composed of one or two elements. It has been shown repeatedly in various experimental paradigms that set-size effects differ for displays composed of a relatively small number of elements (i.e., approximately ≤ 4 items), and those associated with larger displays (i.e., approximately > 4 items). The Greenlee-Thomas (1993) model offers no explanation for why this might be so. Second, while Magnussen, Greenlee, and Thomas (1997) are able to use this model to predict that greater interference will be found when dual decisions are made within the same perceptual dimension, rather than across different perceptual dimensions, this prediction lacks quantitative rigor, and is unable to accurately anticipate the size of the threshold increase, or give a detailed explanation of its underlying causes.
In addition to the Greenlee-Thomas model (Greenlee & Thomas, 1993), there are two other prominent approaches for describing set-size effects in VSTM. These two approaches are can be referred to as sample size models (Palmer, 1990), and urn models (e.g., Pashler, 1988). They differ from the Greenlee-Thomas (1993) model by: (1) ascribing the root cause of set-size effects to a stage prior to decision making; and (2) making no theoretical distinction between decisions made in the same, or across different, perceptual dimensions.
Models of capacity limits in VSTM:
If observers are asked to report on the quality (e.g., color) of an item stored in memory, while performance might be perfect when only a few items are encoded (the number of items that can be perfectly encoded varies depending on the attribute being encoded, but is usually less than five), after which performance invariably declines in a monotonic fashion as more items are added. Different theoretical models have been put forward to explain this decline in performance.
Slot models:
A prominent class of model proposes that observers are limited by the total number of items which can be encoded, either because the capacity of VSTM itself is limited (e.g., Cowan, 2001; Luck & Vogel, 1997; Pashler, 1988), or because of a bottleneck in the number of items which can be attended to prior to encoding. This type of model has obvious similarities to urn models used in probability theory (see, for example, Mendenhall, 1967). In essence, an urn model assumes that VSTM is restricted in storage capacity to only a few items, k (often estimated to lie in the range of three-to-five). The probability that a suprathreshold change will be detected is simply the probability that the change element is encoded in VSTM (i.e., k/N). Although urn models are used commonly to describe performance limitations in VSTM (e.g., Luck & Vogel, 1997; Pashler, 1988; Sperling, 1960), it is only recently that the actual structure of items stored has been considered. Luck and colleagues have reported a series of experiments designed specifically to elucidate the structure of information held in VSTM (Luck & Vogel, 1997). This work provides evidence that items stored in VSTM are coherent objects, and not the more elementary features of which those objects are composed.
Noise models:
A much more controversial framework has more recently been put forward by Wilken and Ma (2004) who suggest that apparent capacity limitations in VSTM are caused by a monotonic decline in the quality of the internal representations stored (i.e., monotonic increase in noise) as a function of set size. In this conception capacity limitations in memory are not caused by a limit on the number of things that can be encoded, but by a decline in the quality of the representation of each thing as more things are added to memory.
In their 2004 experiments, they varied color, spatial frequency, and orientation of objects stored in VSTM using a signal detection theory (SDT) approach. The participants were asked to report difference between the visual stimuli presented to them in consecutive order. The invesigators found that different stimuli were encoded independently and in parallel, and that the major factor limiting discrimination performance was neuronal noise (which is a function of visual set size).
Sample size models:
Sample size models (Palmer, 1990) propose that the monotonic decrease in performance with increasing set-size in VSTM experiments is a direct outcome of a limit in the amount of information observers can extract from a visual display.
In the sample size model, each perceptual attribute of a stimulus is associated with an internal, unidimensional percept, formed by the collection of a finite number of discrete samples. It is assumed that the total number of samples that can be collected across the entire visual scene is fixed. Assuming that equal attention is paid to each stimulus, it follows that the total number of samples taken from each element in an array will be inversely proportional to the number of stimuli present, N. Central limit theorem implies that the mean of the samples taken, and therefore the mean of the internal percept, will have a variance inversely proportional to N. Signal detection theory defines sensitivity (i.e., d′) as being inversely proportional to the standard deviation of the underlying representation to be discriminated (Macmillan & Creelman, 1991). Therefore according to the sample size model, in a VSTM experiment an observer's sensitivity to a stimulus change, d′, will be inversely proportional to square-root of N.
Unfortunately, few studies have directly tested this prediction of the sample size model. Some evidence has been provided by Palmer (1990), who performed a VSTM experiment using arrays composed of lines of varying length, and set-sizes of one, two or four. The task of observers was to determine whether there had been a change in the length of one of the lines. It was found that observers' thresholds increased proportional to square-root of N, in accordance with the predictions of the sample size model.
References:
1. Bennett, P. J., & Cortese, F. (1996). Masking of spatial frequency in visual memory depends on distal, not retinal, frequency. Vision Research, 36(2), 233-238.
2. Blakemore, C., & Campbell, F. W. (1969). On the existence of neurons in the human visual system selectively sensitive to the orientation and size of retinal images. Journal of Physiology, 203, 237-260.
3. Breitmeyer, B. (1984). Visual masking: An integrative approach. Oxford: Oxford University Press.
4. Cermak, G. W. (1971). Short-term recognition memory for complex free-form figures. Psychonomic Science, 25(4), 209-211.
5. Chua, F. K. (1990). The processing of spatial frequency and orientation information. Perception & Psychophysics, 47(1), 79-86.
6. Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral and Brain Sciences, 24(1).
7. DeValois, R. L., & DeValois, K. K. (1990). Spatial vision. Oxford: Oxford University Press.
8. Greenlee, M. W., & Thomas, J. P. (1993). Simultaneous discrimination of the spatial frequency and contrast of periodic stimuli. Journal of the Optical Society of America A, 10(3), 395-404.
9. Lee, B., & Harris, J. (1996). Contrast transfer characteristics of visual short-term memory. Vision Research, 36(14), 2159-2166.
10. Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279-281.
11. Magnussen, S. (2000). Low-level memory processes in vision. Trends in Neurosciences, 23(6), 247-251.
12. Magnussen, S., & Greenlee, M. W. (1992). Retention and disruption of motion information in visual short-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 151-156. 248
13. Magnussen, S., & Greenlee, M. W. (1997). Competition and sharing of processing resources in visual discrimination. Journal of Experimental Psychology: Human Perception and Performance, 23(6), 1603-1616.
14. Magnussen, S., & Greenlee, M. W. (1999). The psychophysics of perceptual memory. Psychological Research, 62(2-3), 81-92.
15. Magnussen, S., Greenlee, M. W., Asplund, R., & Dyrnes, S. (1991). Stimulus-specific mechanisms of visual short-term memory. Vision Research, 31(7-8), 1213-1219.
16. Magnussen, S., Greenlee, M. W., & Thomas, J. P. (1996). Parallel processing in visual short-term memory. Journal of Experimental Psychology: Human Perception and Performance, 22(1), 202-212.
17. Magnussen, S., Idas, E., & Myhre, S. H. (1998). Representation of orientation and spatial frequency in perception and memory: A choice reaction time analysis. Journal of Experimental Psychology: Human Perception and Performance, 24, 707-718.
18. Nilsson, T. H., & Nelson, T. M. (1981). Delayed monochromatic hue matches indicate characteristics of visual memory. Journal of Experimental Psychology: Human Perception and Performance, 7, 141-150.
19. Palmer, J. (1990). Attentional limits on the perception and memory of visual information. Journal of Experimental Psychology: Human Perception and Performance, 16(2), 332-350.
20. Pashler, H. (1988). Familiarity and visual change detection. Perception & Psychophysics, 44(4), 369-378.
21. Phillips, W. A. (1974). On the distinction between sensory storage and short-term visual memory. Perception & Psychophysics, 16(2), 283-290.
22. Phillips, W. A., & Baddeley, A. D. (1971). Reaction time and short-term visual memory. Psychonomic Science, 22(2), 73-74.
23. Regan, D. (1985). Storage of spatial-frequency information and spatial-frequency discrimination. Journal of the Optical Society of America A, 2(4), 619-621.
24. Schiller, P. H. (1995). Effect of lesions in visual cortical area V4 on the recognition of transformed objects. Nature, 376, 342-344.
25. Sperling, G. (1960). The information available in brief visual presentations. Psychological Monographs: General and Applied, 74(11), 1-30.
26. Todd, J. J., & Marois, R. (2004). Capacity limit of visual short-term memory in human posterior parietal cortex. Nature, 428, 751-753.
27. Vincent, A., & Regan, D. (1995). Parallel independent encoding of orientation, spatial frequency, and contrast. Perception, 24(5), 491-499.
28. Wilken P, Ma WJ (2004) A detection theory account of change detection. J Vis, 4, 1120-1135.
-en.wikipedia.org/wiki/Visual_short_term_memory
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