Abstract

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Abstract
Cognitive control processes reduce the effects of
irrelevant or misleading information on
performance. We report a study suggesting that
effective cognitive control mechanisms are
configured quickly during training. In a
Stroop-like task, participants practiced naming
abstract shapes using color words (with one shape
called red, another called blue, etc.these
are referred to as shape names) In a
subsequent test, naming the actual color of the
shape was impaired when the color name and the
shape name conflicted. Using regression
analysis, we found that both the relative speed
of basic shape and color naming processes and the
amount of training on an individual shape made
independent contributions to the amount of
interference created. ERP recording in the same
task revealed a larger frontal N200 component for
participants who showed more behavioral
interference.
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Slide 1
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Introduction
Human and animal sensory systems are constantly
bombarded with an overload of information, and
environmental demands often require the rapid
integration of many sensory stimuli in order to
choose an appropriate response. This job is
facilitated by selective attention, the
situation-specific control over which stimuli and
responses are fully processed. To the degree
that selective attention fails, irrelevant
information interferes with performance. An
important step in understanding how selective
attention works is developing theories of how
interference is created. One simple model of
how interference is created is a horserace
model based on the processing speeds for relevant
and irrelevant attributes of the stimulus. That
is, the relative speed of basic perceptual/motor
processing of relevant and irrelevant stimulus
attributes predicts how much interference will
be produced. Evidence also exists that the
relationship between relative processing speed
and interference is not linear, but an inverted-U
shaped function (Dyer, 1973). Faster or earlier
processing of irrelevant stimuli does not always
lead to increased interference. For example, if
irrelevant features are processed sufficiently
faster than relevant stimuli, it appears that the
irrelevant response can be primed and then
inhibited before the relevant processing reaches
the critical stage where it is vulnerable to
interference.
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Slide 2
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Another factor contributing to interference is
the automaticity of stimulus processingthe
degree to which the flow of information along a
stimulusresponse pathway is independent of
controlled attention. Automaticity and relative
speed may independently affect cognitive control,
and thus measured interference. Alternately, an
automaticity-based account may replace relative
speed as an explanation for why interference
occurs. MacLeod and Dunbar (1988) used training
in a Stroop-like paradigm in a study designed to
investigate the effects of both relative speed
and stimulus-response automaticity. Participants
practiced naming irregular shapes with color
names (e.g., blue). They were then tested on
both naming the shapes when they appeared in
colors (shape naming) and on naming the colors
in which shapes were presented (color naming).
MacLeod and Dunbar found that the interference
created on each of these two tasks was equal
after five days of practice, but that the
relative speeds of the color naming and shape
naming processes were not equalized until 20 days
of practice. Based on their results, they
suggested that automaticity, created by training,
is a better predictor of interference than
relative speed.
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Slide 3
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Task
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Slide 4
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• Shape Naming
• Participants verbalized an arbitrary color word
  (red, blue, green, or yellow) upon presentation
  of one of four shapes these are the shape
  names.
• The shape names were the same as the four
  non-white stimulus colors red, blue, green, or
  yellow.
• The actual colors of stimuli in the shape-naming
  task were either congruent with the shapes name,
  incongruent with the shapes name, or white
  (neutral condition), with equal proportions of
  each type. The three incongruent colors for each
  shape were presented equally often.
• Color Naming
• Participants verbalized the actual color of one
  of the four random polygons shown above, or of a
  colored circle.
• Stimuli appeared in the four non-white colors of
  the previous task, in equal proportions of each.
  
• For the polygons, colors were either congruent or
  incongruent with the shape name. The circles
  served as a neutral condition. The three
  incongruent shapes for each color were presented
  equally often.

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Slide 5
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Experiment 1 Design
Task sequence
Day 1 2 3 4 5 6 7 A B C
B C B C
Task seq.
Boxed conditions used in ANOVA
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Slide 6
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During shape naming, each of the four shapes
was presented a different number of times, to
allow the effects of number of practice trials
and session to be assessed independently in a
regression analysis. Number of practice
trials naming each shape by the end of Session 7
varied between 0 and 2600. The number of
practice trials on a particular shape varied
between participants.
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Slide 7
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Experiment 1 Results

• The right half of the graph contains the
  results for color naming. The shape naming
  results (left half of the graph) are discussed
  elsewhere, although they are included for
  interest.

Mean RT (ms)
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Slide 8
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Omnibus ANOVA results showed that congruence
affected color naming latency. Colors with
incongruent shapes were named more slowly than
those with neutral or congruent shapes. There
was no significant main effect of session, F lt 1.
The significant interaction between session and
congruence, F(6,66) 2.61, MSE 854, p lt .05,
demonstrated that interference increased slightly
with practice.   A planned comparison testing
for a linear change in incongruent relative to
neutral across days revealed a significant
increase in interference with practice, F(1,11)
5.96, MSE 324, p lt .05. Few errors were made
on the task. However, an analysis of accuracy
rates yielded similar results, demonstrating that
there was no substatial speed-accuracy tradeoff.
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Slide 9
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Regression Analysis
MacLeod and Dunbar suggested that training
affects performance above and beyond the effects
of relative processing speed. This analysis
investigated whether training and relative speed
independently contribute to interference.
What factors predict amount of interference?
Results

• Significant effect of relative speed of
  processing, F(1,148) 7.95, MSE 84.16, p lt
  .01. Faster shape naming relative to color naming
  produced a linear increase in interference.
• No effect of day of training, p gt .10
• Significant effect of number of training trials,
  F(1,148) 4.94, MSE 84.16, p lt .05. More
  training on a specific shape produced more
  interference.
• Overall, the model accounted for 48 of the
  variance in observed color naming interference.

Relative speed of shape naming and color
naming Days of training Number of training
trials on a particular shape
Effects of subject and shape entered as blocking
factors
Dependent measure
Interference ratio RTI - RTC
RTC
I is incongruent, C is congruent RT reaction
time
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Slide 10
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• Faster shape naming relative to color naming
  produced a linear increase in interference.

More training on a specific shape produced more
interference.
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ERP effects of color naming
ERPs were recorded during the color naming task
in an 8th session, after completion of the seven
practice days. The graphs show a larger overall
frontal negative shift (blue) in the N200 time
window for participants who were successful at
resolving interference.
A
B
C
N200 waveform (235-275 ms)
. Scalp distributions and waveforms for the
color naming task, 235 275 ms after stimulus
presentation. A,B Scalp distributions for
subjects who showed low and high behavioral
interference effects, respectively. C ERP
waveforms during the n200 time window for each
subject group. The thick solid line is neutral
(circles), the dotted line is incongruent, and
the thin solid line represents averages over
congruent trials.
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Slide 11
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Experiment 2

• We hypothesized that practice can affect
  cognitive control in two ways
• Strengthening / speeding an irrelevant
  stimulus-response association
• Weakening a relevant association that has been
  consistently ignored in practice.
• This experiment manipulated the practice stimuli
  to isolate the weakening effect. We predicted
  that the presence of irrelevant colors during
  shape naming practice may create interference
  with color naming. We compared shape naming
  practice on shapes with irrelevant colors to
  practice naming white shapes.
• In addition, based on the previous experiment, we
  reasoned that measures of improvement during
  training might predict interference independent
  of the relative speed of processing relevant and
  irrelevant dimensions at test.

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Slide 12
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Experiment 2 Design
Group 1
Session 1
Session 3
Session 2
Group 2
Boxed conditions used in ANOVA
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Slide 13
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Experiment 2 ANOVA Results

• Hypothesis the presence of irrelevant colors
  during shape naming practice may create
  interference with color naming.

• Subjects were both slower and less accurate to
  name colors when they appeared within incongruent
  shapes
• Interference was created only when subjects saw
  colored shapes during training

Group 1
Group 2
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Slide 14
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Regression Analysis

• To compare practice effects to effects of
  relative speed after practice, we measured
  improvement during training in two ways
• Improvement (decrease in response time) between
  blocks of 20 trials within a session.
• Improvement between the last 3 blocks of one
  session and the first three blocks of the next.
  Participants improved substantially over this
  consolidation period between sessions.
• Relative speed was measured during the final
  color naming block in the same way as in
  Experiment 1, and the regression was conducted
  between subjects (n 34).
• A follow-up Experiment 3 (n 12), similar to
  Experiment 2 except in monetary compensation, was
  analyzed independently using the same regression.

Predictors

• Relative speed
• median shape naming latency for white shapes -
  median color naming latency for new shapes
• Average improvement in training within sessions
• RTblock N - RTblock N1
• Averaged within sessions (19 blocks) and over
  sessions (4)
• Average improvement in training between sessions
• Consider only last 100 trials of session N and
  1st 100 trials of session N 1
• RT session N - RT session N1
• Averaged over sessions (4)

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Slide 15
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Regression Results
Hypothesis Training effects on interference may
not be due to changes in relative speed in
processing alone. Measures of improvement during
training may predict interference independent of
relative speed.
Experiment 2
Experiment 3

• Relative speed both quadratic and linear
  predictors were significant
• Predictors with arrows leading to the DV were
  significant at p lt .05.

• Relative speed quadratic predictor only
  significant
• All predictors shown were of marginal
  significance, p lt .12

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Slide 16