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Size Matters Sara C. Sereno Patrick J. O’Donnell Margaret E. Sereno.

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Presentation on theme: "Size Matters Sara C. Sereno Patrick J. O’Donnell Margaret E. Sereno."— Presentation transcript:

1 Size Matters Sara C. Sereno Patrick J. O’Donnell Margaret E. Sereno

2 Bigger is better Large vs. small visual object –Activation of more neurons –Attract attention more easily –May hold attention for longer

3 Bigger is better Ethology –Mate selection (e.g., alpha males) –Supernormal stimulus (Tinbergen & Perdeck, 1950)

4 Bigger is better Size-value effect (Bruner & Goodman, 1947) 5020 >

5 Bigger is better Size-congruity effects –Pavio (1975) –Rubinsten & Henik (2002) ++ + ZEBRA LAMP+ ZEBRA LAMP

6 Bigger is better Line bisection with numbers (Fischer, 2001) 91 28

7 Bigger is better Linguistic markedness –Unmarked = usual, dominant, basic, default form –Marked = (not the above) –Examples: Gender marking:general/male female lion, actor lioness, actress Size: How tall is X? How big is y? How wide is z?

8 Semantic Size Hypothesis –Words denoting “big” entities are easier to process than those denoting “small” entities. –RTs for semantically “big” words will be faster than those for semantically “small” words.

9 Lexical Decision Experiment Subjects: N=28 –14 female, 14 male –26 years old –right-handed Apparatus –Mac G4 using PsyScope 1.2.5 PPC software –24-pt Courier font (black on white) –3 characters = 1 o vis. angle

10 Lexical Decision Experiment Materials –Big/Small defined in relation to human size N Length Syl FreqImageability Big456.20 2.00 24.40 6.08 Small456.20 2.00 23.74 6.07 FrequencyBNC (occurrences per million) Imageability MRC Psycholinguistic Database (scale 1-7)Bristol Norms (Stadthagen-Gonzalez & Davis, 2006) Cortese & Fugett’s (2004) Imageability Norms –90 length-matched pseudowords (e.g., blimble)

11 Materials BIGSMALL BIGSMALL BIGSMALL bedcup truckthumb buffalo apricot bayfly whalepeach gorilla parsley jetlip camelglove giraffe emerald cowpin cometsnail mountainmagazine parkrose moosetulip motorwaybacteria treeneck planetbutton elephantmolecule bearring jungleneedle wardrobesandwich lakenose galaxyinsect dinosaurparasite tanktape rocketbullet downtownmosquito bullleaf walruspeanut bookcaseteaspoon riverglass monster diamond cathedralcigarette trainphone stadium battery submarinebutterfly horsevideo mansion vitamin skyscraperfingernail oceanapple tractorsausagesupermarkethandkerchief shorerobin volcanoaspirin hippopotamus hummingbird

12 Lexical Decision Experiment Procedure –Instructed that words represent a selection of several different categories of objects. NW W –Response mapping: leftright 1000 ms500 ms200 ms + until response string

13 Results Data exclusion –Overall: RTs 1500 ms –Per subj per cond: RTs +2SD –4.72% data loss

14 Results RT (ms) %Err Big words513 (8.6)1.6 (.3) Small words527 (9.3)2.3 (.5) t 1 (27)=5.22, p.25 t 2 (44)=3.29, p<.01

15 Discussion Potential confound of response mapping: –Spatial markedness Right is for WORD response, Big or Small. Spatially, however, Left is marked and Right is unmarked. Consistency of markedness (Right, Big) confers benefit only to Big words. –SNARC (Daheane et al., 1993) Spatial Numerical Association of Response Codes Faster right-sided responses to larger numbers; faster left-sided responses to smaller numbers. E.g., Which is bigger? vs. 4 · 9 9 · 4

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17 Discussion Test potential confound: W NW –Reverse response mapping: leftright –Subjects: N=14 (7F,7M), 23 years old –Materials: identical –Procedure: identical –Results: 5% data exclusion

18 Discussion Replication: RT (ms) %Err Big words 514 2.4 Small words 527 3.1 t 1 (13)=2.71, p.30 t 2 (44)=2.08, p<.05 Combined data: RT (ms) Big words 513 Small words 527 F 1 (1,40)=28.12, p<.001 F 2 (1,88)=12.72, p<.001

19 Discussion Is size coded in lexical representations? –Yes, for size words and for some like dwarf, giant. Is size a feature of concrete nouns? –Yes, according to size-congruity studies. However, these studies use a size comparison task. –Yes, according to current Lexical Decision results. But, response criteria can still play a role.

20 Possible Explanation –Larger objects contain more Low SF information. –Low SF is transmitted faster thru magno pathway. –1 o vis cortex & LGN are activated during imagery. –If imagery accompanies word recognition, this information may become available earlier for words referring to larger objects. –Thus, while both Big and Small items can be equally highly imageable, the relative speed of accessing a stored visual representation is faster when the object is bigger.

21 Conclusion Need to establish effect in other paradigms: –EM-reading in neutral context. –EM-reading in different contexts (e.g., large ant). –EEG, MEG, fMRI, & WHATNOT. The Bottom Line…………………..

22 FASTER Bigger is FASTER


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