Psychology 2135A/B Chapter Notes - Chapter 4: Psych, Mental Rotation, Fusiform Face Area

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Psych 2135
May 21-25, 2018
Chapter 4: Recognizing Objects
Recognition: some early considerations
- The variations in the stimulus input provide out first indication that object recognition
involves some complexity
- Another indication comes from the fact that your recognition of various objects,
whether print or otherwise, is influenced by the context in which the objects are
encountered
- Object recognition is also powerfully influenced by the stimulus itself that is, by the
features that are in view
o Poess that ae dietly shaped y the stiulus ae soeties alled data
die ut ae oe ooly teed bottom up processes
- What we see are also influenced by our knowledge and expectations
o This sort of influence relying on our knowledge is sometimes called concept
driven and processes shaped by knowledge are commonly called top down
processes
The importance of features
- Recognition might begin with the identification of visual features in the input pattern
the vertical lines, curves, diagonals and so on
- With these features properly categorized, you can then start assembling the larger units
- In chapter 3 we saw that specialized cells in the visual system do seem to act as feature
detectors, firing whenever the relevant input is in view
- The importance of features is also evident in the fact that people are remarkably
efficient when searching for a target defined by a simple feature
- People are much slower, in contrast, in searching for a target defined as a combination
of features
Word recognition
- Once detection of simple features has occurred, separate mechanisms are needed to
put the features together, assembling them into complete objects
Factors influencing recognition
- Tachistoscope a device designed to present stimuli for precisely controlled amounts of
time
o Each stimulus is followed by a post stimulus mask often just a random jumble
of letters
- Can people recognize these briefly visible stimuli?
o Depends on how familiar the stimulus is
o Another factor of recognition is recency of view
Repetition priming
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The word superiority effect
- Words that are viewed frequently are, it seems, easier to perceive as are words that
have been viewed recently
- Also, words themselves are easier to perceive than isolated letters
o Word superiority effect
- This effect is usually demonstrated with a two alternative, forced choice procedure
Degree of well-formedness
- The data tells us that its easie to eogize a ‘ if the lette appeas in context, than it
is if the letter appears on its own
- This benefit only emerges however is the context is of the right sort
Making errors
- First, it seems that a latter will be easier to recognize if it appears in a well formed
sequence, but not if it appears in a random sequence
- Second, well-formed strings are, overall, easier to perceive than ill formed strings; this
advantage remains in place even if the well-formed strings are made up ones that
youe ee see efoe
- All of these facts, suggest that you somehow are using your knowledge of spelling
patterns when you look at and recognize the words you encounter
- The influence of spelling patterns also emerges in another way: the mistakes we make
o With brief exposures, word recognition is good but not perfect
o Errors are quite systematic
o There is a strong tendency to misread less common letter sequences as if they
were more common patterns
- Misspelled words, partial words or non-words are read in a way that brings them into
line with normal reading
- In effect, people perceive the input to being more regular than it actually is
Feature nets and word recognition
- The design of a feature net
o The idea is that there could be a network of detectors, organized in layers
o The bottom layer is concerned with features, and that is why networks of this
sort are often referred to as feature nets
o The flow of information would then be bottom up from the lower levels
toward the upper levels
o At any point in time, each detector in the network has a particular activation
level, which reflects the status of the detector at just that moment
How energized it is
o The atiatio leel ill eetually eah the detetos espose theshold, ad
at that point the detector will fire send its signal to the other detectors
o Detectors that have fired frequently in the past will also have a higher activation
level
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