Emotion Word Processing - Emotions in Language

Chapter 2 Literature Review

2.2 Emotions in Language

2.2.3 Emotion Word Processing

Adopting the two-dimensional structures of emotion, valence and arousal, previous research comprises a great portion of the “emotion effect” on the modulation of word recognition.

Since Kissler’s (2006) study, a series of neuroimaging techniques were applied to explore the temporal and spatial neuronal activities in human brain during emotion word processing.

Several typical early components of emotion effects are specified with mixed results in event-related potential (ERP) studies such as P1, N1, and P2. For instance, Herbert et al.

(2008) using silent reading task with valenced words (60 pleasant, 60 unpleasant and 60 neutral adjectives) of controlled arousal found no P1 and N1 elicitation while Scott et al.

(2009) adopting lexical decision task with arousal-matching words (80 positive, 80 negative, 80 neutral words, half high (HF) and half low (LF) in word frequency) showed greater P1 in positive and neutral stimuli than negative ones and also greater N1 in LF neutral and HF negative stimuli compared with HF neutral and HF positive ones, respectively. On the other hand, with LDT, Kanske and Kotz (2007) presented emotional stimuli (60 positive, 60 negative, 120 neutral nouns, half high and half low in word concreteness) in the right and left

visual field (RVF/LVF), and found greater P2 for positive than neutral stimuli, whereas Carretié et al. (2008) showed no P2 elicitation with 10 insults, 10 compliments, and 10 neutral adjectives. It is thus proposed that the P1 and N1 components in previous studies represent subcortical feed-forward mechanisms (for reviews, see LeDoux, 2003) that link to the acquisition of conditioned responses and the detection of visual emotion stimuli when there are severely limited perceptual resources (e.g. rapid serial visual presentation and subliminal or near-threshold presentation). Also, the emotion effect on P2 amplitude over frontal-central sites (Begleiter & Platz, 1969; Begleiter et al., 1979; Bernat et al., 2001;

Schapkin et al., 2000) can reflect automatic processing of emotion when attention is focused on the emotional connotation in passive viewing (Begleiter and Platz, 1969), with subliminal presentation (Bernat et al., 2001), or in an affective evaluation condition (Begleiter et al., 1979) that does not necessarily associate with emotional word processing. According to Kanske and Kotz (2007), the enhanced P2 amplitude for positive stimuli represented the positive offset since under low levels of arousal input (e.g. word stimuli), people would respond more intensively to positive emotion stimuli compared with negative ones. However, the studies reviewed here often adopted different tasks and manipulation of emotion word stimuli; hence, it could produce artifacts and made most of the inconsistent results hard to interpret.

One of the late commonly seen components is the early posterior negativity (EPN), which peaks between 200 and 300 ms after stimulus onset. It has an occipito-temporal scalp distribution and its amplitude is larger for emotionally valenced words (positive and negative) than neutral words during silent reading (Herbert et al., 2008; Kissler et al., 2009) or lexical decision task (Schacht & Sommer, 2009a; Scott et al., 2009). EPN has been associated with the initial and automatic processing of stimuli with emotional connotations since its effect is not modulated by the emotional nature of the task (Kissler et al., 2006), or the self-referentiality of the emotional stimulus (Herbert et al., 2010). In this time window, source analysis also found that mapping of the visual stimulus with its corresponding lexical representation can occur with higher activities in fusiform gyrus or the visual word form area, which is a part of the ventral visual processing stream in the inferotemporal brain regions (Hinojosa et al., 2001; Schacht & Sommer, 2009a). It is also noted that there is no discrimination between positive and negative valence in this stage, so EPN may be an index of natural selective attention, which signals a general emotion effect without distinguishing relationships between emotional valence and arousal.

Another component evoked by emotion effect and yielding more consistent results in literature is late positivity complex (LPC). LPC has been found in response to emotional stimuli including words, faces, and also pictures. It peaks between 500 and 800 ms and has a centro-parietal scalp distribution. A larger LPC is often seen to emotionally valenced stimuli

than neutral ones (Carretié et al. 2008; Herbert et al., 2008; Kanske & Kotz, 2007; Palazova et al., 2011; Schacht & Sommer, 2009a), representing the valence processing, and may extend several hundred milliseconds, forming a sustained slow positivity (SSP) and peaking from 700 to 1000 ms. However, if comparing LPC on pleasant and unpleasant stimuli directly, different experimental designs again render biased results. For example, it is found that LPC was larger when one experienced unpleasant stimuli (Baumeister et al., 2001;

Schacht & Sommer, 2009b): a common “negative bias” with which people would respond more intensely to negative emotion stimuli compared with arousal-matching positive ones.

Nevertheless, other studies had null results or even a positive bias (Herbert et al., 2008;

Kissler et al., 2009; Palazova et al., 2011). LPC is considered to be a part of a larger P3 family, related to reallocation of a more domain-general attentional orientation toward an evaluation or processing of the stimulus. Emotional stimuli will thus trigger LPC due to its motivational salience. Also, in contrary to EPN, LPC is task dependent, often occurring in tasks requiring deep processing such as LDT and semantic judgment, and can be modulated by the arousal of the stimuli and the self-relevance in the emotional contexts (Fields &

Kuperberg, 2012).

According to Kissler’s (2006), higher cortical response can be observed through visual word processing if the word is related to or contains affective associations. This higher cortical response occurs in visual word form recognition, the access of the mental

representation, the allocation of attention, contextual integration and memory encoding, which may sustain to 500 ms after the word onset. The variable timing of each component may result from subjects’ different motivational states with different tasks applied, and additional contextual factors. Under LDT, it is important to examine whether the emotion effect precedes or follows the lexical effect (e.g. N400-like negativity) elicited by comparing the emotion words and pseudowords/non-words. This can also be discussed with Coltheart (2001)’s dual-route cascaded (DRC) model to explain skilled reading: visual word recognition can bypass two routes, the lexical and non-lexical one through lexicon/semantic system or grapheme-phoneme rule system respectively. If the time locus of emotion effect can be assured, then it is possible to answer the question whether emotion is encoded as a semantic/lexical feature of the visual words by certain connotation mechanisms or it is just an associative conditioned effect of some mnemonic templates. Only a few studies addressed this issue and there were mixed results. In Scott et al.’s (2009) research, lexical frequency of the emotion words from ANEW was considered an index of lexical processing and the authors found the frequency effect on emotion word stimuli occurs earlier than the lexical effect. On the contrary, Palazova et al. (2011) using the same lexical decision task claimed a reversed pattern. In their research, words were half high and half low in frequency and categorized into nouns, verbs, and adjectives. Nouns and adjectives elicited emotion effect (i.e. EPN) approximately at the same time as the onset of the lexical effect (~270 ms), while

verbs’ emotion effect came much later (~350ms). The inconsistency in the stimuli variables controlled across these studies thus shows the relationship between the linguistic features of the stimuli and emotion effect needs further inspection to explore whether there is linguistic confounds modulating emotion effects or even impacting the positive or negative bias of ERP components, such as P2 or LPC. Recently, Zhuo et al. (2013) used their own Chinese emotion word database to observe ERP response by a valence judgment task for emotion-denoting (e.g. kuai4le4 快樂 “to be happy”) and emotion-inducing (e.g.

zhong4jiang3 中獎 “to win a prize”) words and found these two categories show differences

in a time window of 460~570 ms in the midline positions (FPz, Fz, Cz, Pz, Oz) and the frontal areas (FP1 and FP2). Their emotion word stimuli were rated on not only emotional features such as arousal, valence, continuance (i.e. the duration of the elicited emotion), and controllability (i.e. the degree to which you can control the elicited emotion), but also linguistic features like frequency (i.e. the word’s frequency of occurrence in daily life), and typicality (i.e. the prototypicality of the word) with the 9-point Likert Type scale. However, both the two groups of stimuli in this experiment contained various lexical categories such as stative and event words that were evidenced to cause different processing loads due to its lexical semantic complexity (Gennari and Poeppel, 2003). It is hence necessary that we observe the emotion-related components in an experiment with more detailed temporal resolution and delicate manipulation of emotion word stimuli.

As an index of semantic complexity, lexical category is one of the candidates for showing different semantic information a word can carry. Lexical category has long been one of linguistic universals widely studied in previous literature (for reviews, see Vigliocco et al., 2010) and verbs can assign thematic roles and impose greater processing demands than nouns at the semantic level. Therefore, research using different methods like EEG/fMRI often aimed to investigate whether processing words with different lexical categories, mainly nouns and verbs, would engage different neural systems. Lexical/semantic categorical differences of word stimuli can be observed through ERP differences, with nouns eliciting a left occipitotemporal-distributed negativity as early as 250~280 ms after word onset, but not verbs or numerals, in a semantic category judgment task (Dehaene, 1995). Also, Federmeier et al. (2000) compared the ERP waveforms of unambiguous nouns, verbs, and category ambiguous words (either to be nouns or verbs) embedded in a sentence context. Their materials were picked without the bias in semantic domains so that nouns and verbs were not restricted to objects and actions respectively. The results showed that verbs elicited a left lateralized anterior positivity while nouns generated a more negative wave between 250~450 ms over central-posterior sites. On the contrary, Pulvermüller et al.’s (1999a, b) study compared action verbs, nouns with strong action associations, and nouns with strong visual associations and found no lexical category effect. The authors found that verbs showed a larger P2 at frontal-central sites than nouns but there was no difference between action verbs

and action nouns, suggesting an effect of semantics rather than lexical category during word processing. In addition, Vigliocco et al. (2006) manipulated both the lexical categories (i.e.

verbs and nouns) and the semantic features (i.e. sensory and motion words) of the words and found that nouns and sensory words had a larger N400 effect than verbs and motion words on central-parietal sites. These studies might suggest the effect of lexical category can come from different semantic complexity of words in both the early and late time windows of word recognition; however, few studies focused on this modulation on emotion word processing given that emotion words include both emotion-denoting and emotion-inducing words that may possess different semantic attributes. Besides, previous ERP studies often focused on different onsets of emotion effects on words with different lexical categories. For instance, emotion effects of verbs on EPN (Schacht and Sommer, 2009a, 2009b) started approximately 150 ms later than the effects reported by Kissler et al. (2007) with nouns and by Herbert et al.

(2008) with adjectives. It is thus argued that the emotion contents in verbs and/or adjectives may be elaborated more deeply and for a longer time compared to nouns since nouns are easy to process and acquired early so that they can be processed more superficially without the sustained attention (Palazova et al., 2011). However, to date, no comprehensive comparisons among these word categories were conducted on Chinese emotion words to show whether there are latency, duration, or even scalp differences of the emotion effects.

2.2.4 Trait Theory and Emotion Word Processing

In Eysenck’s (1947) early model of personality, two independent dimensions are specified, namely extraversion and neuroticism. Extraversion is characterized as the sensitivity to positive cues and the tendency to experience positive affects in the environment, whereas neuroticism is associated with emotion instability and the sensitivity to negative emotions, a strong predictor of psychological problems such as depression, anxiety disorder, and schizophrenia. It is further proposed that people with high extraversion (so-called

extroverts) seek excitement and social activity in an effort to heighten their

reticulothalamic–cortical arousal level, while people with low extraversion (so-called

introverts) tend to avoid social situations in an effort to keep such arousal to a minimum.

Neuroticism can be expressed by an increase of reactivity to the limbic system that is sensitive to emotion arousal stimuli and its level can affect the tendency of affective reactivity and emotion regulation. Extraversion and Neuroticism were later also specified in a widely accepted model of personality, the Big Five model (for reviews, see Costa & McCrae, 1992), which included five domains of personality: openness, conscientiousness, extraversion, agreeableness, and neuroticism. Although the neuroanatomical correlates of extraversion and neuroticism were commonly investigated (e.g. Wright et al., 2006; DeYoung et al., 2010)--with extraversion positively correlated with volume of medial orbitofrontal cortex, a brain region involved in processing reward information, and neuroticism negatively

correlated with volume of hippocampus systems, brain regions associated with threat, punishment, and negative emotion--their relationship with emotion word stimuli is still unclear in the normal population. These personal traits affect not only the way people categorize emotion words regarding semantic associates but also the degree of valence and arousal focus during perception. For example, behavioral priming (e.g. deciding if a letter string is an English word is speeded by prior presentation of a semantically related prime) data from Matthews et al. (1995) demonstrated that negative prime-target pairs generally possessed greater priming effects than positive ones and that neutral prime-target pairs were more strongly primed in more neurotic subjects, highlighting the bias on valence processing.

Borkenau et al.’s (2010) study showed extroverts had faster identiﬁcation of pleasant words than of neutral and of unpleasant words under a go/no-go lexical decision task that included pleasant, unpleasant and neutral words. However, whether these traits postulate different arousablities or activate the limbic system to a different degree between neuroticism and extraversion, as suggested by Eysenck’s proposal of arousal variance, is still an issue worthy of careful examining. By using event-related potential technique in the current study, it is expected that a preliminary examination of the interaction between personality traits and (both emotion and linguistic) features of the stimuli can extend previous research and show the time course of the modulation by personality.

Several recent studies used functional magnetic resonance imaging (fMRI) to investigate emotion word processing in people with minor or major mood-related disorders, such as subliminal depression, anxiety, or even schizophrenia (Laeger et al., 2012; Pankow et al., 2013). In Laeger et al.’s (2012) research, subclinical measures of anxiety or depression were found to modulate the neural processing of emotional words: emotion valenced words activated the amygdala and there was a positive correlation between the activation of the amygdala and the scores on trait anxiety and subclinical depression during negative word processing. Subjects with high trait anxiety also showed greater functional correlations between left amygdala and left dorsolateral prefrontal cortex (DLPFC) activation. The amygdala’s role in the emotion word processing could thus be more general, regardless of the valence nature of the emotion words. Pankow et al.’s 2013 study, on the other hand, revealed that with affective pictures, schizophrenic patients showed stronger activation of the right amygdala while viewing negative compared to positive stimuli. Among these patients, medication status further influences the degree of activation in ventral anterior cingulate cortex, a region involved in emotion processing and conflict monitoring. Other studies discussing the personality modulation such as extraversion and neuroticism on the emotion effect in human brain were mainly conducted by pictorial stimuli (Kehoe et al., 2011) in passive viewing which cannot truly reflect the reading models, but it is informative to make an analogical comparison between word and pictorial stimuli and clarify the relationship

between emotion valence and arousal. For example, individuals with high neuroticism showed reduced activation in the orbitofrontal cortex and valence processing in the right temporal lobe, but an increased response to emotional arousal in the right medial prefrontal cortex (mPFC) was observed (Kehoe et al., 2011). Canli et al.’s (2001) study showed that extraversion is correlated with the amygdala, caudate nucleus, and putamen response to positive stimuli. The left middle frontal gyrus and temporal gyrus were all observed to be associated with extraversion and neuroticism in emotion processing. However, since the valence difference is only reflected in the LPC or SSP activities during individualized emotion word processing in previous ERP studies and BOLD signals are not able to differentiate different aspects of emotion, using fMRI might not provide sufficient temporal resolution on the time window of interest we want to focus on. Indeed, ERP studies have showed the correlation of the characteristics in late components that reflect motivational significance of stimulus meanings or salience with peculiarities of the personality (for reviews, see Kovalenko & Pavlenko, 2009). For instance, the amplitude and latency of the LPC (mainly P3) in the central/parietal/occipital regions demonstrated a negative correlation with the indices based on the extraversion scale, and this was argued to be related to the level of voluntary attention and the intensity of habituation to stimulation in introverts. Also, in the right hemisphere, the neuroticism level was shown to be positively correlated with the amplitude of all the ERP components, along with the latency of late ERP components.

However, these ERP studies often adopted visual/auditory oddball or attention spatial orienting tasks that focused on individual differences in attention allocation with mostly pictorial stimuli; there was little proof of this modulation by a better temporal description under word recognition paradigm. Even though Laeger et al.’s (2012) fMRI study used linguistic stimuli, it only incorporated German nouns that could cause emotion connotations and left other lexical categories of emotion stimuli untested, such as the emotion-denoting words. No work has been done on the modulation of individual differences in healthy population on the emotion effect during visual word processing with the consideration of semantic complexity of the stimuli. With EEG, we hope our study can fill in the gap in the modulation of emotion effect on early and later components with comparison of individual differences and thus can shed more light on the impact of lexical differences on emotion word perception.

Chapter 3 Methodology

3.1 Subjects

Thirty-five native Chinese speakers (19 males), aged between 20 and 40 year (M=26, SD=4.46), took part in the experiment. They were all right-handed, had normal or corrected-to-normal vision, had no neurological disorders and psychological/mental illness and took no medication for mood disorders. They completed the Eysenck personality questionnaire revised (EPQ-R, revised short-scale edition in Chinese, see Appendix A) (Eysenck et al., 1995) before EEG recording. EPQ-R is a self-report questionnaire which measures levels of extraversion, neuroticism and psychoticism on scales ranging from 0 to 12, with 0 indicating the lowest and 12 the highest level of the trait, and it shows good reliability and validity in the male sample (N=408, Age=38.44±17.67). The coefficient of internal consistency (Cronbach’s α ) for the scale of extraversion is 0.88, and for the scale of neuroticism, 0.84 (Eysenck et al., 1995). We focused on extraversion and neuroticism in this study. The participants were then divided into two groups (high scores, low scores) based on the median scores of extraversion and neuroticism levels in EPQ-R. Accordingly, each participant was categorized as a member of extroverts or introverts (i.e. low extraversion) with high or low neuroticism at the same time. Besides, to ensure participants’ moods are in relative stability before the experiment, participants also filled out the Beck Depression Inventory-second edition in Chinese (BDI-II, see Appendix B). BDI-II is a self-report

questionnaire using 4-point Likert scale which measures levels of depression originally based on Beck et al. (1961). It also shows good reliability and validity in both the college student and patient samples. The internal reliability (Cronbach’s α ) for clinical patients is 0.92, while for college students, 0.93, with the test-retest reliability being 0.93 (Beck et al., 1961).

The score ranges from 0 to 63 with the cut-off score for mild depression being 14. The participants’ scores indicated that they were not going through moderate or severe depression

在文檔中個人特質差異對不同中文詞類情緒詞處理之影響：事件相關腦電位研究 (頁 27-0)