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Cognitive Processes
PSY 334
Chapter 2 – Perception
April 11, 2003
Categorical Perception
 For speech, perception does not change
continuously but abruptly at a category
boundary.
 Categorical perception – failure to
perceive gradations among stimuli within
a category.

Pairs of [b]’s or [p]’s sound alike despite
differing in voice-onset times.
Two Views of Categorical
Perception
 Weak view – stimuli are grouped into
recognizable categories.
 Strong view – we cannot discriminate
among items within such a category.
 Massaro – people can discriminate
within category but have a bias to same
items are the same despite differences.
 Category boundaries can be shifted by
fatiguing the feature detectors.
Top Down Processing
 General knowledge (context, high-level
thinking) combines with interpretation of
low-level perceptual units (features).
 Context limits the possibilities so fewer
features must be processed:

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Word superiority effect – D or K vs WORD
or WORK – words do 10% better.
To xllxstxatx, I cxn rxplxce xvexy txirx
lextex of x sextexce xitx an x, anx yox stxll
xan xanxge xo rxad xt wixh sxme xifxicxltx.
Context and Speech
 Phoneme restoration effect:

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It was found that the *eel was on the axle.
It was found that the *eel was on the shoe.
It was found that the *eel was on the
orange.
It was found that the *eel was on the table.
 The identification of the missing word
depends on what happens after it.
Faces and Scenes
 When parts are presented in isolation,
more feature information is needed to
recognize them.


Face parts are recognized with less detail
when in the context of a face.
Subjects are better able to identify objects
when they are part of coherent novel
scenes rather than jumbled scenes.
Models of Object Perception
 Two competing models explain how
context and feature information are
combined:


Massaro’s FLMP (fuzzy logic model of
perception) -- Context and detail are two
independent sources of information.
McClelland & Rumelhart’s PDP model –
connectionist model in which both sources
of information interact.
Testing the FLMP Model
 Four kinds of stimuli:



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Only an e can make a real word.
Only a c can make a real word.
Both letters can make a word.
Neither letter can make a word.
 Within each group, stimuli go from e to c.
 Subjects saw each stimulus word briefly
and had to identify the letter, e or c.
FLMP Results
 Observed frequencies for naming a letter
e increase as it has more e features, but
also as the context demands an e.
 Baye’s theorem gives a formula for
combining the independent contributions
of two sources of information.
 Massaro’s results conform to predictions
of Baye’s theorem, suggesting that the
information sources must be
independent of each other.
Testing the PDP Model
 Activation spreads from features to
excite letters and from letters to excite
words (bottom up processing).
 Activation also spreads from words to
the component letters (top-down
processing).
 The more activation, the more likely the
correct letter will be identified:

TRAP vs TRIP
Comparing the Two Models
 Subjects heard a phoneme that varied
from r to an l in two contexts:


A syllable beginning with t – tr or tl.
A syllable beginning with s – sl or sr.
 Both the FLMP and PDP models were
compared to actual subject data.

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FLMP was close to what subjects did.
PDP was too strongly affected by context.
PDP Model Describes More
 The PDP model suggests that
information is not separately processed
but each letter affects each other letter.

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Recognition of “a” in MAVE is almost as
good as recognizing it in MADE.
This occurs because MAVE is similar to
many other words with an A in that
position.
 We do not have a context but four letters
that each influence the others.
Marr
 Depth cues (texture gradient, stereopsis)
– where are edges in space?
 How are visual cues combined to form
an image with depth?

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Primal sketch – extracts features.
2-1/2 D sketch – identifies where visual
features are in relation to observer (depth).
3-D model – refers to the representation of
the objects in a scene, combines context.
Putting it All Together
 The output of these stages (see Fig
2.31) is a representation of an object and
its location.
 This output is used as input to higherlevel cognitive processes.
 Conscious awareness (a higher-level
process) involves the recognition stage,
but lots of processing occurs first.