Data Acquisition and Analysis - 左右手利者對情緒詞處理之差異

Chapter 3 Methods

3.4 Data Acquisition and Analysis

The E-Prime 2.0 software from Psychology Software Tools, Inc. was used in the Windows 7 environment on a PC to present the stimuli and to record the behavioral data of the participants (i.e., reaction time and response accuracy). The SPSS software version 21 (IBM Corporation) was used to analyze the collected data.

Data with accuracy rate lower than two standard deviations were excluded, and only trials with correct responses were analyzed. The collected RTs and accuracy rates were respectively analyzed with a three-way repeated measures ANOVA with three independent

variables: group (left-handed, FS+, FS-), valence (positive, neutral, negative), and visual field (LVF, RVF). Post-hoc pairwise comparisons were carried out and Bonferroni corrected when needed. In addition, the p-values were adjusted with the Greenhouse-Geisser correction (Greenhouse & Geisser, 1959) when the Mauchly's test of Sphericity was violated.

Importantly, planned comparisons, including paired t-tests on valence under two visual field conditions and paired t-tests on visual field under three valence conditions for each of the subject groups, were carried out to test the body-specificity hypothesis.

Chapter Four

Results

The current study recruited 104 participants. Five subjects’ data were excluded due to technical problems or unexpected health issues of the participants, such as unilateral near-sightedness. Then the data of the remaining 99 participants (33 FS-, 35 FS+, 34 Left-handed) were further subjected to elimination based on the following criteria -- (1) mean accuracy rates lower than 2 SDs, (2) for the left-handed group only, the score (0-10) of the Edinburgh left-handedness inventory lower than five, and (3) the BDI-II depression score equal to or higher than 20 (indicating a moderate depression or above). After the screening, the data of 84 subjects ( 27 FS-, 30 FS+, 27 Left-handed) remained. In order to keep the number consistent across groups, three subjects’ data in the FS+ group were randomly excluded, which left 81 subjects in total, with 27 subjects in each group.

4.1 Accuracy Rates

Table 4 summarizes the mean accuracy rates under the six conditions (3 valence levels x 2 visual field levels) for each group. A three-way repeated measures ANOVA with the factors of group (FS-, FS+, Left-handed), valence (positive, neutral, negative) and visual field (LVF, RVF) was conducted. The results revealed a main effect of valence, F(1.268, 98.934) = 46.940, p<.001. Follow-up pairwise comparisons showed that neutral words had a significantly higher accuracy rate (91.79 ± 6.81%) than the other two categories of words (positive: 85.92 ± 11.04%; negative: 85.86 ± 11.83%), while the other two categories did not

significantly differ from each other (p = 1.00). In addition, there was also a main effect of visual field (F(1, 78)=42.055, p<.001), with higher accuracy in the RVF. The average RVF accuracy rate was 91.33 ± 7.24%, while the LVF accuracy rate was 84.39 ± 12.00% (mean difference: 6.94%). As for the between-subject factor, the test results suggested no significant effect of group. On average, the left-handed group had a slightly higher accuracy (88.21%) than the FS- group (87.73%), and the FS- group performed slightly better than the FS+ group (87.65%), though the difference was not significant, F(2,78)=.097, p=.908.

Table 4. Summary of the accuracy rates (Mean and SD) in each experimental condition across groups

Variables

Valence x Visual field

Negative Words Neutral Words Positive Words

LVF RVF LVF RVF LVF RVF

Group FS- 0.81 observed, F(2,156)=21.342, p<.001. To better understand the simple effects of valence and visual field respectively, six follow-up paired t-tests were conducted to further investigate the pairwise relations, the results of which are illustrated in Table 5. As shown in Table 5, only the pair of positive/neutral stimuli and the pair of neutral/negative words in the LVF showed significant accuracy differences. Finally, except for the valence x visual field interaction, no other interactions reached significance: valence x group, F(4,156)=.140, p=.911; visual field x group, F(2, 78)=.052, p= .949; valence x visual field x group, F(4,156)=.138, p=.968.

Table 5. The summary of the follow-up paired t-tests on accuracy rates after a valence x visual field interaction

Visual Field ^Valence ^t ^p-value

LVF Positive/Neutral t(80)= -6.67 .000**

Positive/Negative t(80)= -0.71 2.89

Neutral/Negative t(80)= 6.26 .000**

RVF Positive/Neutral t(80)= -0.34 4.39

Positive/Negative t(80)= 1.04 1.80

Neutral/Negative t(80)= 0.82 2.49

Note: p-values were Bonferroni-corrected.

**= <.001

4.2 Reaction Times

Table 6 summarizes the RTs under the six conditions (3 valence levels x 2 visual field levels) for each of the group. A three-way repeated measures ANOVA with the factors of group, valence and visual field was conducted. The results revealed a main effect of valence, F(2,156)=149.019, p<.001. Pairwise comparisons indicated that the three levels of valence all distinguished themselves from one another on a significant level (p’s <.001). To be specific, the RTs of positive words were the shortest while those of neutral words were the longest.

The RTs of positive words (608.35ms) were approximately 50ms shorter than those of negative words (658.00ms), and the RTs of negative words were roughly 120ms shorter than those of the neutral words (772.17ms). Moreover, although there was no significant valence x visual field interaction, planned analyses revealed that different valence levels distinguished from each other in both visual fields (p’s <.001), with positive words soliciting shortest RTs while neutral words longest RTs.

As for the visual field factor, similar to the results of the accuracy rates, a main effect of visual field was observed, F(1,78)=5.667, p<.05. Words appeared in the RVF/LH were

generally processed 12ms faster than words in the LVF/RH.

Table 6. Summary of the mean RTs and SDs (ms) in each experimental condition across groups

Variables

Valence x visual field

Mean RT (SD) Negative Words Neutral Words Positive Words

LVF RVF LVF RVF LVF RVF

group. Although the effect of group did not reach significance, F(2,156)=.902, p=.410, this

“left-handed < FS- < FS+ group” pattern could be observed across valence conditions and also across visual fields, as is shown in Tables 6 and 7. Table 7 shows the RT difference collapsed by valence or visual field. Please note that the arrangement of the groups from top to down is by the longest RTs to the shortest ones, for the ease of observation. Therefore, the FS+ group is placed at the top row and the left-handed group at the bottom row. As can be seen from Tables 6 and 7, the “left-handed < FS- < FS+ group” pattern on RTs held across every condition.

Although valence x visual field interaction was significant with the accuracy data, no such interaction was observed with RTs (F(2,156)=1.226, p= .296). Also, no other interactions reached significance: valence x group, F(4,156)=.204, p= .936; visual field x group, F(2,78)=.743, p= .479; valence x visual field x group, F(4,156)=.484, p= .748.

Table 7. Summary of the mean RTs and SDs(ms) collapsed by valence or visual field

Valence VF

4.3 Analysis of the Headedness of the Materials

It is not clear if the lack of the effect of the body-specificity hypothesis was due to the difference of the headedness distribution of valence in the bisyllabic materials. In the current study, the headedness of the materials was not controlled because the employed bisyllabic words were considered a unit. It is thus not clear if the preference for the dominant side, if any, was obscured by the uncontrolled headedness of valence within the words. Therefore, we analyzed the headedness distribution of the words in the three valence conditions and the results are summarized in Table 8 below.

Table 8. The distribution of headedness among the three valence categories

Valence\Headedness left-headed right-headed double-headed compositional

Positive 10 (樂觀) 15 (中獎) 23 (幸福) 12 (天堂)

Neutral 4 (發呆) 2 (打牌) 51 (填寫) 3 (傻笑)

Negative 24 (吵架) 8 (世仇) 26 (偷竊) 2 (自大)

Note: Examples are provided in the parenthesis.

As can be seen from Table 8, the valence of the word could be derived from the left (e.g. 樂觀) or the right (e.g. 中獎) character of the word, which is termed left- or

right-28

headed in the current study. Moreover, the valence could also come from both characters (e.g.

幸福), termed double-headed here. In addition, it could also be that neither of the two characters carried the word-level valence. Rather, the valence was derived from the composition of the two characters when they formed a word (e.g. 天堂). Although for both positive and negative conditions, valence was contributed by both characters in more than 20 instances, the rest of the instances showed an inconsistent pattern, with more right-headed words in the positive condition and more left-headed words in the negative one. Also, positive words exhibited a greater number of compositionality than neutral or negative words.

As for neutral condition, more than two-thirds of the instances were double-headed (e.g. 巷道).

Chapter Five

Discussion

This study aimed to investigate the hemispheric lateralization of emotion word processing by left-handers, FS+ and FS- right-handers. Specifically, we would like to examine if the body-specificity hypothesis holds for emotion word processing. With the targeted subject recruitment and the experimental manipulations on valenced words and visual fields, we hoped to capture the subtle difference on emotion word processing by the different population of handedness.

Based on the body-specificity hypothesis (Casasanto, 2009), it was expected that participants would prefer and process faster the positive words shown in the visual field ipsilateral to their dominant sides. Our hypotheses were as follows. First, left-handers should respond faster when the positive emotion words appear in the LVF/RH, compared to appearing in the RVF/LH. Second, left-handers should respond faster to the negative words when the words are displayed in the RVF/LH than the LVF/RH. Third, right-handers should react faster to the positive words when they appear in the RVF/LH than in the LVF/RH.

Fourth, when negative words appear in the LVF/RH, right-handers should respond faster than the negative words presented in the RVF/LH.

As it turned out, no three-way interaction of valence x visual field x group and no two-way interactions involving the group factor were found in the accuracy rate and RT analyses. In fact, all subjects responded significantly faster and more accurately with the verbal stimuli presented in the RVF. In other words, both sinistrals and dextrals reacted faster when the bisyllabic words were projected to their LHs. This result, though not supporting the

hypothesis of interest, exhibited RVF advantage, which was in accordance with abundant literature on word recognition (for reviews see Ducrot & Grainger, 2007; Ellis, 2004; Landis, 2006, Walsh et al, 2010). RVF advantage is a well-known perceptual asymmetry and is manifested in numerous studies (Deutsch & Rayner, 1999; Ellis, 2004; Graves et al., 1981;

Kinsbourne, 1972). According to the literature, RVF advantage possibly results from the LH lateralization of language (Kinsbourne, 1972), left-to-right reading habits (Deutsch & Rayner, 1999) or rightward attentional bias (Gazzaniga, 2009, p.791). Although left-handers exhibit a higher occurrence rate of RH linguistic lateralization or bilateral representation, roughly two thirds of the left-handers have their language lateralized to the LH, as reviewed in Chapter 2 (Bryden, Hecaen & DeAgostini, 1983; Knecht et al, 2000; Rasmussen & Milner, 1977). The general phenomenon of left lateralization of language contributes to the RVF advantage on verbal processing, especially word recognition. This robust RVF advantage could be a stronger influence on the RTs and accuracy rates than the preference of one’s dominant side to the other side, as predicted by the body-specificity hypothesis. Finally, it is worth mentioning that the RVF advantage confirmed that our manipulation of visual field was successful and that the lack of the group effect could not be attributed to imprecise stimulus projection to the target visual field.

As for the group effect, the lack of it in our data may be due to the following two reasons. For one, previous studies on the body-specificity hypothesis used pictures as stimuli, while we used words in our experiment. Pictures might probe into emotions more directly than words and thus generated a larger effect. For the other, linguistic conventions might have overpowered the body-specificity preference. As mentioned in Chapter 2, mental metaphors could arise from correlations in linguistic experience. For example, Meier &

Robinson (2004) showed that participants were faster to judge words like polite and rude as having positive or negative valence when positive words were presented at the top and

negative words at the bottom of a computer screen. Since Chinese metaphorical expressions tend to associate positive and negative valence with the top and bottom of a vertical spatial continuum, it is possible that the preference for the left-right dominant side, if any, was overshadowed by the preference for the top-bottom distinction reinforced by the linguistic conventions. Future studies are needed to test if the three subject groups in our experiment show various preference for the top-bottom spatial continuum.

Overall, the data of the current study did not support the body-specificity hypothesis.

Rather, RVF advantage exhibited across every condition. In addition to the observation of RVF advantage, some interesting findings about emotion word processing and the subtle difference of language lateralization among groups were discussed below.

To begin with, it is shown that valence had influence on the accuracy rates only in the LVF/RH, but not in the RVF/LH (see Table 5). As illustrated in Table 5, the comparison between positive and negative words presented in the LVF/RH did not show significant accuracy difference, for both being valenced words. However, the other two pairs (positive/neutral and neutral/negative) both revealed significant accuracy differences. That is to say, the accuracy contrasts only manifested with emotional words vs. non-emotional words in the LVF/RH. This result agreed with the notion that RH is more sensitive to emotional stimuli than the LH, which has been confirmed by studies with verbal stimuli (Atchley et al, 2003; Landis, 2006) as well as nonverbal stimuli such as facial expressions (Alves, Aznar-Casanova & Fukusima, 2009; Landis et al., 1979; Ley & Bryden, 1979) and also with stimuli of another modality (e.g. the listening task in Carmon & Nachshon, 1973).

Moreover, participants across groups responded significantly faster to positive words than to negative ones, and also distinctly faster to negative than to neutral words, which echoed various studies on emotion word processing (Kanske & Kotz, 2007; Scott et al, 2009;

Walsh et al, 2010), suggesting that our selection of materials was valid. More importantly, the

differences on RTs exhibited emotion word advantage (EWA), which is a facilitation of word recognition when the word has positive or negative valence (Kousta, Vinson & Vigliocco, 2009; Landis, 2006). However, our accuracy data showed an opposite direction of EWA, with the neutral words at the highest accuracy among three groups of words. This could be because neutral words, unlike valenced words, did not solicit one’s emotion, and therefore were of lower arousal level. Therefore, when participants were asked to make valence judgment, they took longer time (though in ms) to ponder on the word and then react, hence the more accurate response. Another explanation could be the difference of the task employment. Emotion word advantage, as shown in previous studies (Kousta, Vinson &

Vigliocco, 2009; Landis, 2006), was observed in a lexical decision task, in which words and nonwords were mixed as the experimental materials. Unlike the task requirement in lexical decision tasks, our experiments required the subjects to make valence judgment. The difference of task requirement could be an explanation why EWA was not manifested in our data.

As for the between-subject factor -- group, it is true that the statistical results on accuracy rates or RTs showed no main effect of group. However, a close observation on the RTs (Tables 6 and 7) indicated that, across conditions, the left-handed group performed slightly better than the FS-, who in turn performed better than the FS+ group. The fact that the left-handed group performed slightly faster could be due to a more bilateral lexical representation in the brain (Basic et al., 2004; Bryden, Hecaen, & DeAgostini, 1983;

Rasmussen & Milner, 1977), so it was possible that the left-handed group had easier access to their lexical representations than the other two groups. However, our results that FS- responded faster than the FS+ group did not agree with findings in previous literature (Bever et al., 1989; Townsend, Carrithers & Bever, 2001), which reported FS+ right-handers, compared with FS- ones, exhibited greater RH involvement during early processing of words.

A possible account of the conflicting outcome might be the inaccuracy of the report of familial handedness by the participants, probably due to the fact that many left-handed people have become corrected right-handers in the Taiwanese society. For example, one of the participants reported no left-handed relatives when registering for the experiment, but in the screening session prior to the experiment, when asked of any left-handed family members, it was found that the father and the brother of the participant were both corrected right-handers.

It could be inferred from this instance that participants might have left-handed relatives without them being aware of it, which might smear the distinction between FS- and FS+

group.

In addition, with a close inspection on the RTs of the visual fields across three groups (as shown in the VF columns, Table 7), we observed an interesting phenomenon. Specifically, the RT difference between LVF and RVF was smaller for the left-handed group (3.82ms), but larger in the other two groups (FS-: 13.56ms, FS+: 17.37ms). Moreover, the SDs in both visual fields of the left-handed group were both close to 110ms, smaller than those of the FS- and FS+ group, which were approximately 140ms. Though the difference among the groups did not reach significance, as indicated by a non-significant group x visual field interaction, the fact that left-handers showed less evidence of lateral asymmetry in performance was in agreement with existent literature (Orbach, 1967; Bryden, 1964). Taken together, the tendency of sinistrals having a more bilateral cerebral linguistic representation might be inferred. This inference corresponds to the literature on handedness and language dominance.

For example, Knecht et al (2000) suggested a higher RH language dominance for left-handers than right-handers, and Kheder et al (2002) reported an observation of bilateral cerebral representation or even RH language dominance in 26.3% of strong left-handers and 57% of mixed handed subjects. In sum, the results, though not statistically significant, could support a more bilateral lexical representation among left-handers.

In the current study the headedness of the bisyllabic experimental materials was not controlled because the words were considered a unit. However, to probe into the character level, the valence of a word could come from (1) both characters (i.e.,double-headed), (2) the left character (i.e., left-headed), (3) the right character (i.e., right-headed), or (4) the composition of the two characters. As indicated in Table 8, the distribution of the headedness was inconsistent across the three valence conditions. For the neutral words, most instances were of neutral valence in both of the two characters, because either character, if carrying positive or negative valence, could lead to a positively or negatively valenced word. For the positive condition, about one third of the words were double-headed. On the other hand, although the negative condition also exhibited one third of double-headed instances, the rest of the words were mostly left-headed. It is not clear whether the lack of the effect of the body-specificity hypothesis in the current study was due to the different distribution of the headedness of the bisyllabic materials. Future studies on body-specificity hypothesis could further take this factor into consideration.

To summarize, the body-specificity hypothesis was not observed in the current data, possibly overshadowed by the RVF advantage of word recognition. In addition, the contrast between LVF and RVF on the accuracy rates supported the LVF/RH advantage in emotion processing. Moreover, the comparisons between visual fields among three groups indicated a somewhat bilateral lexical representation in the left-handed group. Lastly, future research on body-specificity hypothesis could consider the headedness of the words if linguistic materials are utilized in the experiment.

Chapter Six

Conclusion

The present study investigated whether the body-specificity hypothesis, which argued that personal preference of right- or leftward space is influenced by the individual’s

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