Attention and Selection: Part 2. The increasingly important role played by objects in studies of visual attention. Miller’s ‘Magic Number 7’ has continued to haunt us even beyond studies of short-term memory (STM).
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Controls for separability, convexity, area…
When a right neglect patient is shown a dumbbell that rotates,
the patient continues to neglect the object that had been on the
right, even though It is now on the left (Behrmann & Tipper, 1999).
Simultanagnosic patients cannot judge the relative length of two
lines, but they can tell that a figure made by connecting the ends
of the lines is not a rectangle but a trapezoid (Holmes & Horax, 1919).
Picking out objects is an example of the parsing of a scene into things that are likely to be physical objects. But the same must occur in time – temporal parsing entails solving the correspondence problem
Several studies have shown that what counts as an object (as the same object) endures over time and over changes in location;
Certain forms of changes in location as well as disappearances in time preserve objecthood.
This gives what we have been calling a “visual object” a real physical-object character and partly justifies our calling it an “object”.
Short time delays result in “element motion” in which the middle object persists as the “same object” and does not appear to move so the end objects appear to move
Long time delays results in “group motion” in which the middle object does not persist but is perceived as a new object each time it reappears
Object File Theory of Kahneman & Treisman
Letters are faster to read if they appear in the same box where they appeared initially. Priming travels with the object. According to the theory, when an object first appears, a file is created for it and the properties of the object are encoded and subsequently accessed through this object-file.
Object File 1
Object File 2
When items cannot be individuated, predicates over them cannot be evaluated Do these figures contain one or two distinct curves? Individuating these curves requires a “curve tracing” operation, so Number_of_curves (C1, C2, …) takes time proportional to the length of the shortest curve.
Trick, L. M., & Pylyshyn, Z. W. (1994). Why are small and large numbers enumerated differently? A limited capacity preattentive stage in vision. Psychological Review, 101(1), 80-102.
Read the vertical line of digits in the following display
Under these conditions Conjunction Errors are very frequent
Find the following simple figure in the next slide:
This case is easy – and the time is independent of how many nontargets there are – because there is only one red item. This is called a ‘popout’ search
This case is also easy – and the time is independent of how many nontargets there are – because there is only one right-leaning item. This is also a ‘popout’ search.
Find the following simple figure in the next slide:
* This way of putting is simplifies things. Under certain conditions the serial-parallel distinction breaks down
This sort of model of early vision does not work: it does not provide information that would allow the “cognitive demons” to solve the binding problem.
Information about grouping (conjunction) of properties is lost.
But in encoding properties, early vision can’t just bind them together according to their spatial co-occurrence – even their co-occurrence within the same region. That’s because the relevant region depends on the object. So the selection and binding must be according to the objects that have those properties
There is an intersection of two lines…
But which of the two lines you drew are they?
There is no way to indicate which individual things are seen again unless there is a way to refer to individual things
Here is another intersection of two lines…
Is it the same intersection as the one seen earlier?
To be able to tell without a reference to individuals you would have to encode unique properties of the individual lines. Which properties should you encode?
Example of geometrical figure used in solving a problem in plane geometry: Not all of it is seen or noticed at once – coding is incremental
Consider what happens when vertices are encountered while the figure is scanned. When are two such encounters of the very same vertex?
When a new property of a vertex is noticed, which part of the current representation should be updated? When should a new vertex-representation be added? Answering these questions requires keeping track of individual distal objects. We proposed the mechanism of visual indexes (FINSTs) for this function.
A description cannot keep picking out the same individual when the individual is changing its properties unpredictably, even if the description is continually updated
Notice that in the previous example it would not help if you labeled the diagram as you drew it. Why not?