Searching the visual scene - A2 Flashcards

1
Q

What did original ideas about how we search the visual scene suggest?

A

searches that rely on more than one element of the target (e.g. red crosses) are less efficient than ones that rely on one element (e.g. red)

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2
Q

What factors are usually varied in visual search tasks?

A
  • number of distractors
  • presence or absence of targets (positive or negative)
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3
Q

What are feature searches and conjunction searches?

A
  • feature = target is distinct from distractors by one feature
  • conjunction = target is distinct by a combination of features
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4
Q

What are the findings for visual search tasks for feature searches?

A
  • positive trials = size of the array doesn’t affect RT
  • negative trials = size of array does affect RT (more to search to check it isn’t there)
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5
Q

What are the findings for visual search tasks for conjunction searches?

A
  • the size of the array increasing always increases RT
  • this increase in RT is greater for negative trials
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6
Q

When looking at visual search task results, what does m represent in the equation?

A

the increase in RT for every new item added to the array

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7
Q

What are the 2 processing stages in Feature integration Theory? What are some characteristics of them?

A
  • feature detection - fast, parallel, automatic and efficient - single features pop out
  • feature integration - gluing all the features together (attentional focus is the glue) - slow, inefficient search
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8
Q

What did Wolfe find with regards to the predictions made by feature integration theory?

A

there is no real pattern in the results between feature and conjunction searches

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9
Q

What does Wolfe’s model of guided search suggest?

A
  • there is a top-down part that constrains how you search and a bottom-up part that interact to create a more efficient search
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10
Q

What is an example that supports Wolfe’s model of guided search?

A

When looking for a red item of specific orientation it is easier to find it when some of the shapes are green than them all being red as the top-down process can make you ignore all the green items, reducing the search

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11
Q

What things drive bottom-up search? (2)

A
  • salience (target is more or less different to distractors)
  • attributes (elements that capture attention)
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12
Q

What drives top-down search? (2)

A
  • scene properties
  • values
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13
Q

What does attentional engagement theory suggest?

A

the efficiency of the search is based on aspects of the task
- target/non-target similarity and non-target/non-target similarity

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14
Q

How does target/non-target similarity affect search?

A

more similar = target less likely to pop out so search is less efficient

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15
Q

How does non-target/non-target similarity affect search? What implications does this have?

A
  • if they are heterogeneous (all different) then search is less efficient, even though they still only differ by one dimension from the target
  • doesn’t fit with FIT as that suggests that one dimension different = should always pop out
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16
Q

What are guiding attributes according to Wolfe (2004)?

A

Ways in which an item can differ from the distractors, and these attributes differ in the amounts to which they affect efficiency of the search

17
Q

How does context affect searching for an object?

A

It constrains search to areas that are likely to have that object (e.g. a horse will be on the ground not in the sky)
top-down, guided search

18
Q

What are the 2 pathways in Wolfe’s model?

A
  • selective pathway - recognition of stimuli’s elements
  • non-selective pathway - basic semantic information from the scene (gist)
19
Q

What did Anderson et al (2011) find when they altered the reward value associated with coloured circles that served as distractors in a search task?

A

RT was higher the higher the value of the distractor

20
Q

What other individual factors affect distraction? (2)

A
  • low working memory scores = high distraction
  • higher impulsivity scores = high distraction