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The averaged waveforms of different valence, including negative, neutral, and positive

stimuli, are displayed in Figure 2. As demonstrated in Figure 2, the brainwaves contain clear

N1 and P2 elicited by all the three valence types of stimuli, followed by a negative-going wave (N400) peaking at around 300350 ms. In addition, the responses to the negative and

positive stimuli are more positive than those to the neutral ones during 500800 ms after the

onset of stimuli, especially over the center and the right hemisphere. To better capture this

pattern, Figure 3 is plotted to demonstrate the difference waves between emotional and

neutral verbs. The more positive responses elicited by emotional verbs reveal that there may

be an LPC effect in the current experiment task.

Figure 2. The grand average waveforms of negative, neutral, and positive stimuli

Figure 3. The topography of ERP differences between Negative stimuli vs. Neutral stimuli (Bin 1: Negative - Neutral) and between Positive stimuli vs. Neutral stimuli (Bin 2: Positive - Neutral) during 400-800ms interval

Figure 4 illustrates the grand average waveforms for stimuli with different polarization:

stimuli co-occurring with highly or low emotion-polarized nominal collocates. The brainwaves contain clear N1, P2, a negative-going wave during 300450 ms, and a following

positive wave peaking at around 500 ms. It also seems that across the two conditions, the

waveforms overlap throughout the whole epoch.

To further verify the patterns observed in Figures 2-4, and to examine the effects of

valence and polarization, repeated measures ANOVAs were carried out on the mean amplitudes in the time windows of 300450 ms (N400) and 500800 ms (LPC) on the lateral

regions (i.e. lateral analysis) and the midline electrodes (i.e. midline analysis) (See Chapter 3

Data analysis for details).

Figure 4. The grand average waveforms of highly and low emotion-polarized nominal collocates of stimuli

4.2.1 N400 (300-450 ms)

For the midline analysis, a 3 x 2 x 3 ANOVAs with the factors of valence (Negative,

Neutral, Positive), polarization (High, Low) and midline electrode (FZ, CZ, PZ) was

conducted. A main effect of valence was found (F(2,40) = 7.101, p < .005), with negative and

neutral stimuli eliciting larger amplitudes than the positive stimuli (Negative vs. Positive:

t(20)= -3.917, p < .005; Neutral vs. Positive: t(20)= -3.437, p < .01), and no significant

contrast between negative and neutral stimuli (Negative vs. Neutral: t(20)= .101, p = 2.762).

There was a marginal main effect of electrode as well (F(2,40) = 4, p < .05), revealing that

interactions were found (Polarization: F(1,20) = .763, p = .393; Valence x Polarization:

F(2,40) = .526, p = .595; Valence x Electrode: F(4,80) = 1.082, p = .371; Polarization x

Electrode: F(2,40) = .788, p = .419; Valence x Polarization x Electrode: F(4,80)= .215, p

= .867).

As for the lateral analysis, a 3 x 2 x 2 ANOVAs was performed with the factors of valence

(Negative, Neutral, Positive), polarization (High, Low) and laterality (Left, Right). No main

effects or interactions involving these three factors were found (Valence: F(2,40) = 3.425, p

= .042; Polarization: F(1,20) = .311, p = .583; Laterality: F(1,20) = .374, p = .548; Valence x

Polarization: F(2,40) = .416, p = 663; Valence x Laterality: F(2,40) = .195, p = .813;

Polarization x Laterality: F(1,20) = 2.638, p = .12; Valence x Polarization x Laterality: F(2,40)

= .693, p = .506).

Taken together, the polarization of stimuli’s habitual nominal collocates did not modulate

the valence in this time window. However, an emotion effect was found along the midline

channels (FZ, CZ, PZ), with the positive stimuli inducing smaller N400 compared with that

of the negative and neutral stimuli.

4.2.2 LPC (500-800 ms)

Similar to the statistical analysis in the N400 time window, two three-way repeated

measure ANOVAs were conducted separately on the midline channels (FZ, CZ, PZ) and the

lateral regions (Left, Right) to examine whether emotion effects within this time window

would be modulated by the polarization of stimuli’s habitual nominal collocates. For the

midline analysis, a 3 x 2 x 3 ANOVAs with the factors of valence (Negative, Neutral,

Positive), polarization (High, Low) and electrode (FZ, CZ, PZ) was performed. There was a

main effect of valence (F(2,40) = 7.857, p < .005), with positive stimuli eliciting larger

amplitude than the neutral ones (Positive vs. Neutral: t(20)= -5.688, p < .001), but no

significant contrasts found between negative and neutral stimuli (Negative vs. Neutral: t(20)=

2.349, p = .087) and between the emotional stimuli (Positive vs. Negative: t(20)= - .993, p

= .996). Apart from this effect of valence, no other main effects or interactions were found

(Polarization: F(1,20) = .424, p = .522; Electrode: F(2,40) = 1.479, p = .242; Valence x

Polarization: F(2,40) = 1.195, p = .313; Valence x Electrode: F(4,80) = .588, p = .619;

Polarization x Electrode: F(2,40) = 1.082, p = .328; Valence x Polarization x Electrode:

F(4,80) = .383, p = 755).

As for the lateral analysis, a 3 x 2 x 2 ANOVAs was performed with the factors of valence

(Negative, Neutral, Positive), polarization (High, Low) and laterality (Left, Right). A main

effect of valence (F(2,40) = 5.934, p < .01), a main effect of laterality (F(1,20) = 6.346, p

< .05) and an interaction between valence and laterality (F(2,40) = 3.777, p < .05) were found.

Follow-up pair-wise comparisons indicated that, in the left hemisphere, positive stimuli

induced larger amplitude than the neutral ones (Positive vs. Neutral: t(20) = -3.443, p < .01),

while no other significant contrasts were found (Negative vs. Neutral: t(20)= 1.559, p = .404;

Negative vs. Positive: t(20)= - .378, p = 2.128). Whereas in the right hemisphere, both

negative and positive stimuli elicited larger amplitudes than the neutral ones (Negative vs.

Neutral: t(20) = 3.305, p < .05; Positive vs. Neutral: t(20) = -4.563, p < .005), and no

significant difference between the emotional stimuli (Negative vs. Positive: t(20) = - .374, p =

2.136). A significance difference between the left and right hemisphere was found when the

stimuli were negative or positive, with the right hemisphere eliciting larger amplitudes than

the left (Negative stimuli, left region vs. right region: t(20) = -2.681, p < .05; Positive stimuli,

left region vs. right region: t(20) = -3.385, p < .01). Apart from the above, no other main

effects or interactions were found (Polarization: F(1,20) = .013, p = .909; Valence x

Polarization: F(2,40) = .757, p = .476; Polarization x Laterality: F(1,20) = 2.926, p = .103;

Valence x Polarization x Laterality: F(2,40) = .624, p = .541).

To sum up, similar to the midline analysis in the N400 time window, a main emotion

effect was found along the midline channels, although the exact pattern differed. In the N400

time window, both the neutral and negative stimuli elicited larger amplitudes than the positive

stimuli; however, in the LPC time window, the positive stimuli elicited larger amplitude than

the neutral ones, showing no significant contrast between the emotional stimuli. Furthermore,

there was an interaction between valence and laterality of the brain. Both the positive and

negative stimuli (the emotional stimuli) induced larger LPCs than the neutral ones in the right

hemisphere, whereas only the positive stimuli induced larger LPC than the neutral ones in the

left hemisphere. For the emotional stimuli, the LPCs were stronger over the right hemisphere

than the left. Finally, no modulation of collocates’ polarization on the effect of valence was

found.

Chapter 5 Discussions

Words are judged to be associated with positive or negative evaluation as they co-occur

mostly with other words that belong to positive or negative semantic set. “Semantic prosody”

is the term first introduced by Louw (1993) to describe this “consistent aura of meaning with

which a form is imbued by its collocates”. As for Sinclair’s definition (Sinclair 2004a),

semantic prosody speaks for a pragmatic function out of a juxtaposition of co-occurring

words, with its prior purpose to convey speaker/writer’s attitudes. Stewart (2010) further

remarked that shared features existing in the regular collocates (e.g. “undesirable things” for

the verb cause) would be acquired by the verb over time, leading to an epistemic reading

imposed on the verb. The different, but at time same time, similar interpretations on semantic

prosody in addressing “the transfer of pleasant or unpleasant messages from the habitual

collocates to the node verb” made we believe that it may be an informative issue if we can

examine the nature of semantic prosody from the cognitive neuroscience perspective.

The research question of this study was: Do people process the semantic prosody of

Mandarin-Chinese verbs, particularly the negative or positive emotive information induced

by collocational relation with nouns? Our results showed a main emotion effect in 300-450

ms time window (N400), with both the neutral and negative verbs inducing larger N400 than

the positive verbs. Later, in 500-800 ms time window (LPC), we found that both the

emotional verbs had larger amplitudes than the neutral verbs in the right hemisphere, while

only the positive verbs activated larger amplitude than the neutral verbs in the left hemisphere

and in the midline area of the brain (no significant contrast was found between the negative

verbs and neutral verbs). Additionally, specifically for the emotional verbs, we found the right

hemisphere had stronger responses than the left.

We first discuss the emotion effects to see if our study replicated previous findings about

emotional words. Previous ERP studies reported that a P2 enhancement was found for

emotional words as compared to neutral words, but the difference was less consistent

between positive and negative words (e.g. adjective materials in Herbert et al. 2006). In the

present study, we found a recognizable P2 effect of emotion as well. However, the brain

responses to the emotional verbs (positive and negative verbs) and the neutral verbs were all

very similar, showing that the emotion effect of verbs was not apparent in the early time

window, 200-300 ms post stimuli.

Despite the lack of the early emotion effect in P2, emotion effects were found in later

time windows: the N400 and LPC. As reviewed in Chapter 2, N400 was proposed as a brain

component modulated by emotional semantics, with decreased amplitude found for emotional

words as opposed to neutral words, because when the content of a word is involved with

emotion, it facilitates the access into long-term memory and hence leads to easier semantic

processing on emotional words (Kanske & Kotz 2007). The current study observed smaller

N400 for the positive verbs compared with the neutral ones, indicating that when verbs were

expressive with positive emotion, they were easier for semantic processing. Interestingly,

different from previous studies, no significant difference was found between the negative and

the neutral verbs. The unique status of positive verbs (i.e. being different from the neutral and

negative verbs) may be due to a general preferred processing towards positivity in humans

(Kissler et al. 2006). According to Ito & Cacioppo (2005), the positive motivational approach

system tends to be activated more strongly than the negative motivational withdrawal system.

The emotion effect was also found in the LPC: the LPC amplitudes were more enhanced for

the emotional (especially the positive) verbs than for neutral ones, replicating previous

findings (Schapkin et al. 2000; Fischler & Bradley 2006; Herbert et al. 2006). Furthermore,

we discovered that the emotion effect appeared in both hemispheres but was stronger over the

right, which was in line with Atchley et al.’s (2003, 2007) argument that the right hemisphere

is particularly involved in processing affective content of emotional words. The fact that there

was larger LPC amplitudes for emotional verbs than neutral ones may reflect more active

cognitive analysis on words with distinctly negative and positive emotion. That is, both

negative and positive verbs might strike more vivid mental images than the neutral ones,

whose emotionality was rather weak or uncertain.

Knowing that emotion effects in the literature were replicated in the current study, we

now turn to the polarization effect of the nominal collocates. Our behavioral results revealed

the polarization effect of the nominal collocates: verbs in the Low conditions were responded

faster than those in the High conditions. It was tempting to believe that this RT disadvantage

in the High conditions might come from the semantic influence of the nominal collocates.

However, our ERP data refuted this speculation and revealed no difference in the

“collocates-to-verbs” semantic influence between the High vs. Low conditions.

To further examine the existence of the polarization effect of collocates in the behavioral

data but its absence in the ERP data, we took a closer look at the two most frequent nominal

collocates (based on corpus’s frequency rating) of the verbs in the High conditions (namely,

conditions NH, PH, and NUH) since we found the accuracy rate for the neutral verbs was

significantly lower than the emotional ones within the High conditions. We found that these

collocates aligned their emotion valence with that of the verbs in the emotional verb (NH and

PH) conditions. This could imply that the negative or positive feature of the high-frequency

collocates might affect ERP participants in their judgement for the verbs being negative or

positive in the NH and PH condition, respectively. That is, semantic prosody might have long

been memorized as an important message of the verbs, and had been acquired through everyday repeated uses of “verb + collocates” constituent. Before pressing the button to

submit response, these ERP participants had already formed a clear picture of the verb’s

affective content in head, and therefore, no clear impact from the invisible collocates (our

manipulation on High vs. Low conditions) can be found on the online processing of verbs.

Interestingly, we discovered that two most frequent collocates in the NUH condition held

salient negative or positive emotion as well, with 13 neutral verbs’ collocates having negative

emotions and 19 neutral verbs’ collocates having positive emotions (; as for the remaining 3

NUH verbs: one with a negative collocate, another one with a positive collocate, the other

one with both a negative and a positive collocates). A question then arises: If the

“collocates-to-verbs” influence were prominent, as in the NH and PH conditions, why were

the neutral verbs, especially those in the NUH condition, evaluated “neutral” by the

population recruited in the pilot test?

This discrepancy about the valence of neutral verbs may be due to different time pressure

in the pilot test vs. the ERP experiment. In the ERP experiment, the participants’ brain

response to the verbs was captured with millisecond resolution under time pressure (i.e.

within 3 sec). Like the emotional verbs, the valence of the neutral verbs also came from the

valence of the high-frequency collocates; hence, the judgment of the neutral verbs did not

differ from that to the emotional verbs. In contrast, in the pilot test of valence-rating,

participants were totally free from time limitation, leading to a possible change in their

judgment because not only high-, but also low-frequency collocates were activated and

contributed to how participants rated the verbs. So, even if the participants did have some initial “emotional feeling” about the neutral verbs, it might have been cancelled out by other

co-activated, lower-frequency, collocates.

Therefore, the existence of the polarization effect in the behavioral data but its absence in

the ERP data might actually come from the same reason. That is, the judgment of the

positivity/negativity of the verbs is based on the valence of the high-frequency collocates, not

on how diverse/consistent the valence of the collocates are. The “frequency effect” of the

valence of the high-frequency collocates may result from years of language use by the

speakers themselves. Therefore, the Valence x Polarization interaction in the accuracy data

might simply reflect the possibility that the neutral verbs in the ERP experiment were

perceived with emotion carried by their high-frequency collocates, and such “misperception”

was even stronger when the collocates were highly emotional (i.e. mostly positive or

negative), as demonstrated by the 38.1% accuracy rate in the NUH condition.

In sum, despite the observation about semantic prosody of the “verb + collocate”

constituents in the linguistics literature, our experiment failed to find an online computation

of semantic prosody, as indicated by the existence of the emotion effect of the verbs and the

lack of the polarization effect of the invisible collocates. However, we did observe that the

valence of the verbs may come from the valence of the high-frequency collocates. We argue

that the semantic prosody might have been gradually formed during the process when a

speaker learns and uses the combination of the verb and its collocates, and later be

strengthened by the most frequent collocations between the verb and the following noun.

Once the semantic prosody is consolidated, it is directly associated with the verb and cannot

be easily altered by the valence of other collocates in online processing.

Chapter 6 Conclusion

In the linguistics literature, semantic prosody is collocational influence exerted on a target

word by its habitual or close surrounds. This study attempted to capture the online

computation of semantic prosody. Focusing on the emotion aspect of the target verbs

(Mandarin Chinese two-character transitive verbs), we further manipulated the verbs with

high or low emotion-arousing degree of their invisible nominal collocates. The experimental

design employed in our study was a 3 x 2 design, based on the interaction between two main

factors: Valence (Negative verbs, Neutral verbs, Positive verbs), and Polarization (Highly

emotion-polarized invisible nominal collocates, Low emotion-polarized invisible nominal

collocates). The results showed emotion effects for the emotional verbs and the neutral verbs

in the N400 and the LPC time windows. The smaller N400 for the positive verbs compared to

that of the neutral ones demonstrated easier semantic processing of words expressive with

positive emotions. Since no such contrast was found for the negative verbs (as well as a

distinct contrast between positive and negative verbs), we suggested this uniqueness of

positive verbs may due to human’s general bias towards positivity. The enhanced LPC for the

emotional (especially the positive) verbs may suggest the vivid mental images activated by

the verbs and reflect more active cognitive analysis on words with distinctly negative and

positive emotion. Furthermore, stronger LPC responses in the right hemisphere may indicate

right-hemisphere involvement in processing the affective content of words.

The current experiment failed to find an online computation of semantic prosody, as

indicated by the existence of the emotion effect of the verbs and the lack of the polarization

effect of the invisible collocates. However, we did observe that the valence of the verbs may

come from the valence of the high-frequency collocates. Thus, we argue that the semantic

prosody might have been gradually formed during the process when a speaker learns and uses

the combination of the verb and its collocates. And once the semantic prosody is consolidated,

it is directly associated with the verb and may have well become an epistemic or pragmatic

reading imposed on the verb.

This study may be improved for its future directions. The discrepancy in the emotion

judgment was found between the ERP participants and the valence-rating participants

recruited in the pilot test. Since the so-called “correct answers” were based on the result from

the pilot test in this study, we may reanalyze the ERP data according to the valence answers

made by the ERP participants. This way, different patterns of brain responses may be

revealed and provide a new window into the study of sematic prosody. In addition, the

perfectivity of verbs may considered further controlled in future study since

Mandarin-Chinese verbs may address differently in the perfectivity of the action it denotes:

some include the viewing of the beginning and end of the situation, while others focus on the

middle phase of the action, leaving the end of the situation unspecified.

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