Transcript Discrimination without awareness: extracting different

Finding Correlations between Subjective and Objective Measures of Awareness Using Masked Words
Anastasia A. Gorbunova and Kenneth I. Forster
University of Arizona
Results
Background
What role does awareness play in priming?
Forster (1987): Form priming yields different results depending on whether the prime is
masked or not
How much information does one receive from unconsciously perceived primes?
•
Participants report being unable to identify the primes for most of the time at 50 ms prime durations
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Group performance was better than chance on both Semantic Discrimination and E-detection
Discussion
Chance performance on Semantic discrimination items rated below 3 suggests
that awareness is required in this task
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Performance on Semantic Discrimination task did not differ significantly from that on E-detection, but the
tasks correlated significantly
•
•
E-detection results suggest that some information is gathered from masked
words even when the participants feel that they are simply guessing
- visual record can persist in the absence of subjective awareness
•
11 participants were better than chance (63%) on e-detection, and 7 on Semantic Discrimination
How does phenomenology correlate with performance on discrimination tasks involving
masked words?
Cheesman and Merikle (1986): Objective measures of awareness show better
performance than subjective measures
Summary of Results
Semantic
Discrimination
E-detection
% Correct
61.9**
67.2**
Paired Samples
Correlation (subjects)
Marcel, A. (1983): Visual record of the prime could be wiped out, but not the semantic
record
Kouider & Dupoux (2004): Unconscious semantic priming is a result of a perceptual
illusion, where a fragment of the stimulus is perceived consciously
r = 0.597*
Semantic Discrimination (items)
E-Detection (items)
100
90
90
80
80
Percent Correct
100
Percent Correct
Finkbeiner et al. (2005): e-detection task and masked priming
70
60
50
r = 0.549**
40
30
20
Purpose
10
1
2
3
4
30
20
5
100
90
80
70
60
50
r = 0.04
40
30
20
10
0
0.0
0
1
2
3
4
5
20.0
40.0
60.0
80.0
100.0
E-detection Percent Correct
Confidence Rating
Semantic Discrimination
100
Method
90
80
r = 0.974***
70
60
50
Participants:
16 University of Arizona students
3
4
5
6
r = 0.921***
Marcel’s (1983) claim was not replicated, but it wasn’t refuted either, since only
performance on Semantic discrimination was statistically indistinguishable from
that on e-detection
•
60
50
30
2
At 50 ms participants are able to discriminate between alternatives semantically
and are able to perform the e-detection task better than chance as a group
•
70
30
Confidence Rating
•
80
40
1
(averaging across all items as
a function of the rating)
90
40
0
Conclusions
E-detection
100
(averaging across all items as a
function of the rating)
Percent Correct
Percent Correct
Look for correlations between semantic discrimination and e-detection
Task:
2-alternative forced choice with masked priming paradigm (Forster & Davis, 1984)
2 conditions (tasks): semantic discrimination and e-detection.
Participants receive no feedback.
Confidence ratings on a scale from 1 to 5; 1 = complete guess, 5 = I saw the word and am
confident of my decision
40
Semantic Discrimination vs E-detection (items)
*p < 0.05; ** p < 0.01; *** p < 0.001
We should expect performance on Semantic Discrimination to be better than chance, but
performance on e-detection to be at chance in the absence of subjective awareness
Materials:
76 items, each consisting of a prime word such as market, and a semantic associate such as
store. The items were matched for frequency of occurrence, length, imageability, and
neighbourhood density. One half of base words and their neighbours contained an e and
the other half didn’t. Additional 12 items were presented for 100 ms and were used as
fillers.
r = 0.365**
50
Confidence Rating
•
Look for correlations between confidence ratings and performance
60
10
•
•
70
0
Test Marcel’s (1983) claim that visual masking only obliterates the visual record, leaving
the semantic record intact.
The absence of an item correlation between tasks suggests that 100% accuracy
on some items in the Semantic Discrimination does not necessarily rely on
visibility of those items
•
Semantic Discrimination
Percent Correct
Can participants perform Semantic Discrimination and e-detection in the absence of
phenomenological awareness?
•
Subject correlation between tasks suggests that participants are assumed to
possess different degrees of an ability (e.g., picking up information from the
prime) that affects their performance on both tasks
•
0
1
2
3
4
5
6
Confidence Rating
On Semantic Discrimination, only performance on items rated 3 and higher is significantly better than chance
On e-detection, performance on items across all ratings is better than chance when ratings of 1 and 2 are taken
together
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Semantic discrimination isn’t better than chance when participants are guessing,
while e-detection is
•
References
Cheesman, J., & Merikle. P. M. (1986). Distinguishing conscious from unconscious
perceptual processes. Canadian Journal of Psychology, 40, 343-367.
Finkbeiner, M., Forster, K.I., Nicol, J. & Nakamura, K. (2004). The role of polysemy in
masked semantic and translation priming. Journal of Memory & Language, 51(1), 1-22.
Forster, K.I. & Davis, C. (1984). Repetition priming and frequency attenuation in lexical
access. Journal of Experimental Psychology: Learning, Memory and Cognition, 10, 680698.
Forster, K.I. & Forster, J. (2003). DMDX: A Windows display program with millisecond
accuracy. Behavioral Research Methods: Instruments and Computers, 35, 116-124.
Kouider, S., & Dupoux, E. (2004). Partial Awareness Creates the 'Illusion' of Subliminal
Semantic Priming. Psychological Science, 15(2), 75-81.
Marcel, A. J. (1983). Conscious and unconscious perception: experiments on visual masking
and word recognition. Cognitive Psychology, 15, 197-237.