Perceptron Example: Computational model for the Stroop Task. Jaeseung Jeong, Ph.D Department of Bio and Brain Engineering, KAIST

Transcription

1 Perceptron Example: Computational model for the Stroop Task Jaeseung Jeong, Ph.D Department of Bio and Brain Engineering, KAIST

2 GREEN YELLOW BLUE BLUE YELLOW GREEN BLUE RED

3 The Stroop Task Can Teach Us About: Attention Automaticity Learning Response Selection Word Reading Color cognition Experimental Methodology

4 GGGGG A A OOO G A A O O GGGG AAAAA O O G A A O O GGGGG A A OOO

5 rabbit

6 below above * * * above

7 LEFT

8 Variations Insufficient evidence to decide whether similar processes are involved in all of the Stroop-like variations.

9 Time (ms) Dalrymple-Alford & Budayr (1966): First to encourage presentation & timing of stimuli individually. This method now dominates Stroop effect 400 BLUE BLUE 300 Congruent Incongruent

10 time (ms) interference 400 facilitation BLUE BLUE 300 Congruent Incongruent Control

11 Control Condition ####### rsmtlae fast ####### rsmtlae fast ####### rsmtlae fast ####### rsmtlae fast

12 Control Condition fast fast fast fast red yellow red green

13 Control Condition fast red fast fast yellow ready fast red mouse fast green fruit

14 Control Condition fast red fast fat fast yellow ready double fast red mouse fat fast green plan fruit

15 Semantic Effects Semantically-related distractor words (e.g. blood, sky) have been used instead of neutral words (e.g. double, fruit): some interference; more so as the semantic association between word & color increases facilitation: small & dependent upon the control condition used Using color words not in the response set (e.g. purple) reduces the Stroop effect

16 Semantic Effects (cont) rabbit Congruent words facilitate responses (compared to unrelated word or nonword) Same category words interfere most Associative word (e.g. cheese on picture of a mouse) is same as an unrelated word. Interference in naming the color of an incongruously colored object (e.g. a blue banana), compared to a neutral object (e.g. a blue book).

17 Acoustic Manipulations Using a manual response rather than vocal reduces interference Tying up the articulatory system (e.g. by saying blah, blah ) and using a manual response to the color reduced interference Interference increases with increasing pronouncability of nonwords, and with increasing similarity between nonwords and incongruent color words

18 Strategy Composition of entire set of trials influences the participants strategy blocked vs. unblocked Cheesman & Merikle (1984): P s could use info regarding proportion of congruent primes if primes were perceived cons ly, but not if perceived uncons ly (but uncons primes still affected responses)

19 Stimulus Onset Asynchrony (SOA) ignored stimulus (e.g. GREEN) complete stimulus (e.g. GREEN) SOA time

20 SOA Dyer (1971): Color naming - interference decreases with increasing SOA (0 500 ms SOA s used) Glaser & Glaser (1982): Color naming - interference maximal at +/- 100 ms SOA Word reading no effect of SOA

21 Hemispheric Differences Larger Stroop effect when the words are presented to the left hemisphere than the right

22 Stroop Effect Age differences Age

23 Language - Bilinguals Stimulus: Response: vert or green red or rouge? Between-language interference ~ 75% of within-language interference Magiste (1984, 1985) studied relative proficiency of the person s languages Whichever language someone was more proficient in caused more interference

24 Explanations Speed of Processing Automaticity Perceptual Encoding Parallel models Parrallel Distributed Processing

25 Speed of Processing Words read faster than colors are named Response from word reaches response stage before response from color Results in interference / facilitation However, if SOA causes color to reach response stage before word, does NOT lead to reversal of Stroop effect. Therefore, theory is inadequate.

26 Automaticity Word reading is automatic & obligatory, color naming is a more controlled process. Automatic processes can interfere with controlled processes, but not vice versa Strategies should not affect automatic processes However, strategies caused by the % of congruent / incongruent trials do affect results Automaticity may be continuous rather than dichotomous: This allows attention to assert some influence, but the theory then looses some specificity and ability to test predictions decreases.

27 Parallel Models Response stage is active from start of trial. Each response option gains support as trial goes on. Once a response reaches a threshold, that response is chosen. Problems: Predicts symmetrical facilitation & interference. But a solution is possible Could have same problems as speed of processing account, but these are also fixable

28 Parallel Models With fine tuning, Logan s model can encompass the existing data. However, parallel models expressed only at the conceptual level tend to have more free parameters than do sequential models, which may be part of why they appear to be more successful. (MacLeod, 1991,p. 192).

29 Negative Priming

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31 Table 1. Comparison of RTs for each NP condition for human behavioral data Mean RTs ± SD (msec) NP NP1 830 ± NP2 708 ± NP3 730 ± non-np Incongruent (NP1) 787 ± Neutral (NP2) 702 ± Congruent (NP3) 659 ± 202.4

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35 Chung et al., Journal of Computational Neuroscience (In press)

36 Table 3. Comparison of RTs for each NP condition between conventional PDP and TDNN models Conventional PDP TDNN (mean RTs ± SD) (mean RTs± SD) NP NP ± ± NP ± ± 31.5 NP ± ± 34.3 non-np Incongruent (NP1) 16.2 ± ± 60.3 Neutral (NP2) 13.5 ± ± 39.1 Congruent (NP3) 12.2 ± ± 32.2

37 Chung et al., Journal of Computational Neuroscience (In press)

38 Chung et al., Journal of Computational Neuroscience (In press)

39 Chung et al., Journal of Computational Neuroscience (In press)

40 Summary Jensen (1965): w/ multiple administrations, the Stroop test is probably more reliable than any other psychometric test. Modifications only affect the magnitude (its quantitative form), not the pattern of the effect (its qualitative form : 700+ articles (~300 applied & ~400 theoretical) MacLeod s review has been cited 365 times ( ). Still not fully understood

41 1935: Stroop s original article 1960 s: Research interest in Stroop paradigm blossoms 1973: Dyer s review of research on Stroop effect 1991: MacLeod s review of research on Stroop effect 2004: Time for another review? I look forward to the progress that will be examined in the subsequent review of the Stroop literature some time early in the next millennium (MacLeod, 1991, p. 193)