THE INFLUENCE OF NEGATIVE AFFECT ON SELF-REFERENT 
SENTENCE PROCESSING AND MEMORY PERFORMANCE 
BY 
Austin Greg Fitts 
 
 
Submitted to the graduate degree program in Cognitive Psychology 
and the Faculty of the Graduate School of the University of Kansas  
in partial fulfillment of the requirements for the degree of  
Master of Arts 
 
      
      _________________________ 
      Ruth Ann Atchley, Ph.D., Chair 
     
      Committee members: 
      _________________________ 
      Paul Atchley, Ph.D. 
      _________________________ 
      Stephen S. Ilardi, Ph.D. 
      
      Date defended: March 13, 2009 
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The Master?s Committee for Austin Greg Fitts certifies that this is the 
approved version of the following Master?s Thesis: 
 
The Influence of Negative Affect on Self-Referent Sentence 
Processing and Memory Performance 
 
     
       
 
 
 
       
       
      _________________________ 
      Ruth Ann Atchley, Ph.D., Chair 
      
       
 
 
       
 
      Date approved: June 24, 2009 
 
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Specific Aims 
 The current study will investigate how a negative mood state affects 
sentence processing in individuals that have never experienced depression. 
Empirically, the goal of this research is to investigate how an induced negative 
mood state affects the judgment of plausible and implausible sentences that 
contain self-referent material. Past research in the domain of semantic processing 
has found evidence for a distinct attention bias for items that contain emotional 
content (Bradley et al., 2001; Lang, Bradley, & Cuthbert, 1997) and evidence 
supports that this bias is relevant to an individual?s past experience with 
depression (Borod, Bloom, & Haywood, 1998; Atchley, Ilardi, & Enloe, 2003; 
Ilardi et al., 2007; Levin et al., 2007). More generally, there has been significant 
evidence to suggest that items having emotional significance affect cognition in 
the form of enhanced performance (Bradley et al. 2001; Kern et al., 2002; 
Atchley, Ilardi, & Enloe, 2003; Kensinger & Corkin, 2003). For the current study, 
enhanced cognitive performance will include faster lexical access, faster decision-
making abilities, and improved recall accuracy due to the increased salience of 
emotional stimuli. Increased salience facilitates our ability to detect the meaning 
of an emotional stimulus, therefore, improving response time and correct response 
accuracy. More specifically, this study will explore the phenomenon of enhanced 
cognitive performance by measuring the occurrence of faster reading time and 
faster reaction time for making semantic decisions based on sentence content and 
better recall accuracy for emotional words in the sentences presented. 
 4
 Researchers have suggested numerous influences that emotion has on 
memory performance, such as greater recall accuracy for emotionally-valent items 
and increased recall accuracy while in a valenced mood state (see review by 
Blaney, 1986; and also Buchanan, 2007). As this study will be assessing memory 
for emotion-related material and memory performance while in a negative mood 
state, a review of the influence of emotion on recall performance will be provided. 
Regarding recall performance for negatively-valent material, assumptions that 
negative emotional content drives attentional biases (Davidson, 1990; Levin et al., 
2007) and emotion-related items increase physiological arousal (Bradley et al., 
2001; Kensinger & Corkin, 2003) are well accepted explanations for why there is 
increased recall for emotion-related content. For example, research conducted by 
Kensinger and Corkin (2003) showed an advantage for remembering emotionally 
valent words over neutral words and a greater advantage for recalling words with 
high arousal content (eg. anger) over words with low arousal content (eg. shy). A 
study by Schupp et al. (2004) found an attentional bias for negative pictures with 
high arousal content and these researchers proposed that  this effect to due to 
motivated attention.  
 The theory of motivated attention argues that evolutionary significance is 
assigned to stimuli in our environment in the form of increased salience so that 
attention is guided toward information that is critical for survival (Lang, Bradley, 
& Cuthbert, 1997; Bradley et al., 2001). For these researchers, emotional content 
refers to the degree to which an environmental stimulus conveys semantic 
meaning that is relevant to survival. The degree to which a stimulus drives our 
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attention and innervates arousal systems in the brain are determined by the impact 
an emotional stimulus has pertaining to evolutionary significance. The level of 
emotion has been measured by Lang, Bradley, and colleagues according to 
arousal, which reflects the intensity of the stimulus, and valence, reflecting the 
degree to which a stimulus is negative or positive. The degree to which a word 
stimulus can be measured regarding its negative and positive valence is of 
particular interest to the current study as sentences will be presented that include 
positive, negative, and neutral words. The primary research goal of this study is to 
examine how the semantic aspects of emotional valence influence cognitive 
performance and so words rated high in arousal have been excluded from our 
stimulus lists.  
 The current study is concerned with the linguistic aspects of cognitive 
performance while processing emotional items. We will investigate how emotion 
impacts cognitive performance using sentences with emotion-related words, a 
method that has been shown to elicit emotional processing (Landis, 2006; Kissler 
et al., 2007; Herbert, Junghofer, & Kissler; 2008; Silvert et al., 2004; see also 
review by Shanahan, 2008). Attentional biases in decision-making tasks have 
been explored at length, providing evidence for the increased salience of 
emotional items and also evidence for increased performance when making a 
decision about words that convey emotional meaning (Borod et al., 1998; Atchley 
et al., 2003; Ilardi et al., 2007; Levin et al., 2007). Emotion researchers consider 
attentional biases toward emotion-related content a survival mechanism that 
produces an advantage when performing a cognitive task and several researchers 
 6
have linked this phenomenon to increased levels physiological arousal driven by 
emotion stimuli (Tucker, 1981; Derryberry & Tucker, 1992; Bradley et al., 2001; 
Schupp et al., 2004). Schupp et al. (2004) suggests that levels of physiological 
arousal can be modulated by the level of emotional-arousal present in a stimulus 
and that emotion content, particularly content rated high in arousal, requires more 
mental resources. Considering that physiological arousal can be modulated by 
emotional content, neuroimaging evidence demonstrates that both cortical and 
subcortical areas play a large role in emotion processing (Damasio et al., 2000) 
and that processing at both the cortical and subcortical level can play a large role 
in determining emotional significance. In the following review, a discussion of 
the substantial amount of evidence supporting the role of specific subcortical 
structures in processing emotional information (Derryberry and Tucker, 1992) 
will be considered.   
 Within the literature pertinent to particular anatomical structures being 
involved in emotion processing, there is evidence for activation in the left and 
right hemispheres being influenced by whether this information is aversive or 
appetitive (Tucker, 1981; Davidson, 1990; Davidson, 2000; Landis; 2006). Other 
researcher, such as recent work done by Atchley, Ilardi, and Enloe (2003), 
suggests that the right hemisphere plays a highly specific role in emotional 
language processing. Using depressed and remitted-depressed patients, this 
research provides behavioral aspects of semantic processing that are not mood-
state specific, but rather trait-specific. In thinking of how mood dependent 
cognition is related to more enduring trait-like aspects of personality, research 
 7
presented by Levin et al. (2007) suggests that depression can result from a 
prolonged negative mood state. The current study has implications for 
investigating the mechanisms that underlie transient mood and how this can 
influence semantic access for emotional words. Currently, theories related to the 
processing of emotion require more evidence to differentiate between the effect of 
a transient mood state and the experience of prolonged negative affect, as 
suggested by researchers such as Levine and Burgess (1997). The current research 
intends to provide evidence for how valenced emotional states influence the 
processing of emotional stimuli in never-depressed individuals.  
 This research also will explore the effects of word valence on recall for 
emotional and neutral sentences with a particular interest in how a self-referent 
context can affect emotion processing (see review by Ingram, 1990). Emotion and 
memory researchers such as Kern et al. (2002; 2005) have found that a negative 
mood state aids the availability of negative memories and that negative mood 
results in enhanced memory performance. Somewhat incompatible findings are 
presented by Davidson (2003), who suggests overall poor memory performance 
while in a negative mood state. The current research intends to provide further 
evidence of the influence of a negative mood on memory performance and 
sentence processing.  
 How the judgment of valenced sentences changes after the induction of a 
negative mood is the primary aim of the current research and this will provide 
insight into how never-depressed individuals process emotion. This research 
could also influence our understanding of emotion processing in clinically 
 8
depressed populations regarding semantic organization in a negative mood. 
Positive, negative, and neutral sentences that include self-referent material will be 
used to test whether an induced negative mood state affects reading time, aspects 
of judging of sentence plausibility, and memory performance. To help us interpret 
the current research, an outline of past research related to our current goals from 
the perspective of emotion research in cognitive neuroscience and how emotion is 
related to language comprehension and memory processing is provided. We also 
will provide background considerations relevant to an investigation of how 
emotion is processed while in a valenced mood state.  
 In summary, the primary theoretical goal of this research is to study the 
impact of emotion on higher order cognition. Numerous models of emotion that 
have been developed are applicable to this research. Thus, many of the 
researchers who have developed these models will be discussed, with a particular 
focus on the domains of language comprehension, memory, and emotion in 
cognitive neuroscience. The following review provides a targeted discussion of 
the research theories related to emotional cognition that have led to the current 
research goals. We will begin with a general outline of the dominant models of 
emotion processing in the domain of cognitive neuroscience.  
 
Emotion in Cognitive Neuroscience 
 Before the turn of the 20th century, emotion was considered a brain 
mechanism activated after the emergence of an exciting stimulus (James, 1884), 
although the emotion model established by William James and later developed by 
Carl Lange specified that emotion was not the cause of physiological change 
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(Lange, 1922). These researchers suggested that the emotional response is a brain 
reaction to the physiological changes that take place in the body. Emotion did not 
occur after the presentation of an arousing stimulus, but only after physiological 
elements manifested in behavior such as crying, trembling with fear, or an 
increase in heart rate. James and Lange referred to emotion as our perception of 
the physiological systems that activate in response to our environment (Lange, 
1922). 
 Contemporary theory of emotion perception hypothesizes that emotion 
processing activates upon the perception of emotional significance in our 
environment, as in the case of seeing a face (Tracy & Robins, 2008). The stimulus 
elicits a particular bodily response as the physiological reactions related to the 
nature of that emotional stimulus are activated (Lange, 1922). James and Lange 
made a controversial assumption of which instance occurred first, the emotion or 
the behavior. Today, emotion research assumes that cognitive processing activates 
these physiological body states, though many researchers are elaborating upon the 
James-Lange theory of emotion by investigating the interaction between the brain 
and other parts of the body. The James-Lange theory of emotion was certainly a 
motivating idea to begin considering the phenomenon of emotion more 
exclusively.  
 Over the course of a century, cognitive neuroscience and research in 
physiology have built on this operational definition of emotion. For example, 
Damasio and colleagues consider emotion to be the unconscious physiological 
system that activates after an evolutionarily significant stimulus is presented 
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(Damasio, 1998; Damasio et al., 2000). Damasio and colleagues present much of 
their emotion research based on a brain-body feedback loop, a system that takes 
into account that emotion is not merely the conscious perception of the 
physiological change that is taking place. These researchers tell us that 
unconscious feedback from the body is essential to emotional perception. 
 Evidence for the unconscious perception of emotion presented by 
Damasio et al. (2000) suggests that feeling an emotion draws upon both cortical 
and subcortical structures that belong to patterns of neural activity that have 
developed throughout the evolution of our species. These researchers posit that 
emotion be considered a whole-body regulation mechanism closely related to 
maintaining homeostasis, as feeling an emotion draws upon brain structures that 
both receive internal signals, via the peripheral nervous system, and distribute 
these signals, via the spinal cord. Considering basic emotion processes as related 
to homeostasis is important for the theory that has driven much of the work done 
by Damasio and colleagues and Damasio?s somatic-marker hypothesis considers 
the regulatory nature of emotion as an example of how integrative emotion 
systems affect more than conscious perception, as in cases of how stress can lead 
to fatigue and heart disease.  
 With the somatic-marker hypothesis, Bechara and Damasio (2006) suggest 
that emotion systems are integrated at the level of decision-making. In this article, 
Bechara and Damasio propose that distinct bodily feedback systems associated 
with emotional states such as joy and fear are drawn upon when making economic 
decisions. The basis of this theory suggests the significant influence that emotion 
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has on all of cognition while also contributing to the operational definition of 
emotion.  
 Rainville et al. (2006) provided further evidence that distinct 
cardiorespiratory patterns can be elicited by discrete emotions. In this case, the 
same neural systems that influence behaviors associated with homeostasis are 
accessed when basic emotional states are elicited. The relationship between the 
neural activation for emotion and bodily responses is a key component of the 
somatic-marker hypothesis. Damasio and colleagues continue to find evidence 
suggesting that bioregulatory feedback is essential to the nature of emotion 
processing. The involvement of homeostatic mechanisms in a feedback loop with 
neural systems activated by emotion processing suggests that emotion has greatly 
impacted the evolution of our visceral systems. 
 Damasio et al. (2000) found distinct patterns of activation for the 
elicitation of sadness, happiness, anger, and fear. This and other more recent 
models introduce anatomical structures functioning synchronously with the 
perception of discrete emotions and these models contribute to the modern 
approach to studying emotion processing. With some information about the 
history of emotion and how research on emotion has changed with the emergence 
of cognitive neuroscience, we will next consider more specific approaches to 
studying emotion that take into account the functions of the limbic system and the 
impact of subcortical structures on emotion processing.   
 
 
 
 
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Subcortical Models of Emotion 
 While researchers such as William James, Carl Lange, and Antonio 
Damasio draw their attention to how emotion functions outside the central 
nervous system, other researchers have focused more on the subcortical brain 
structures that play a critical role in emotion processing. Among them, one of the 
most influential approaches has come from the work of Don Tucker, whose 
research has had a great influence on unraveling the influence of subcortical 
arousal systems on cognition (Tucker, 1981; Tucker & Williamson, 1984; 
Derryberry & Tucker, 1992).  
 In order to set aside the long-standing view that emotional states and 
biological substrates related to emotion are nonspecific and result in general 
arousal, Derryberry and Tucker (1992) suggested that the initial processing of 
information in our environment gives an advantage to emotional stimuli, so that 
our behavior serves either our appetitive goals or our interest to withdrawal from 
an environmental stimulus, as in the case of danger or threat. The structures that 
contain the neural pathways that these researchers suggest as the foundation of 
emotional processing consist of the brainstem and limbic system structures. They 
state that emotion systems are necessary in the response systems that can 
orchestrate a coordinated effort to evaluate and react to the environment. These 
systems are highly distributed in the brain and specific response patterns have 
developed in order to achieve goal states that we perceive as emotional 
experience. What has been discussed in the review by Derryberry and Tucker 
(1992) has also been supported by work presented by researchers such as 
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Damasio and colleagues that have found highly distributed brain activation while 
participants reported feeling emotion (Damasio et al., 2000). 
 The activation of subcortical structures can emerge upon the presentation 
of auditory or visual sensory information or this activation can be generated from 
within the individual. An interesting example of internal sensory generation is 
found by eliciting emotion using declarative memory, as evidenced by Philippot 
et al. (2003) by asking participants to recall personal memories. Derryberry and 
Tucker (1992) designed a model of the neural pathways that are activated upon 
the presentation of emotional information coming from an external source. These 
researchers theorize that, through evolution, our ability to process emotion has 
developed brain structures that are efficiently organized in order to allocate our 
mental resources to stimuli that are more significant to survival. Their argument 
provides a fundamental framework for a discussion of discrete emotions and 
provides assumptions as to why we have evolved in a way that gives priority to 
emotional information in our environment.  
 Interpreting evidence from brain imaging techniques that reveal the 
activation sites in response to emotional-related environmental stimuli, 
Derryberry and Tucker (1992) speculate that the subcortical structures specific to 
the initial processing of emotion have developed directly from more primitive 
structures that perform basic regulatory as well as basic motor and arousal 
functions essential for homeostasis and the fundamental aspects of survival, such 
as our level of consciousness and our amount of hunger. These emotional 
structures, including the hypothalamus and the limbic system, are organized so 
 14 
that appraisal and judgment can be most efficient. For example, Derryberry and 
Tucker discuss structures within the hippocampus that play a large role in emotion 
processing through the application of long-term memory stores.  
 Derryberry and Tucker (1992) suggest that as our species evolved with 
more complex neural circuitry than other species. They claim that the structures 
crucial for emotion processing, such as those involved in homeostatic responses 
and memory, developed patterns of activation that are more efficient due to their 
close proximity. The authors suggest that due to the particular location of these 
structures and the specific roles that they undertake, their activation appears to be 
critical for our response to an emotional stimulus. The structures critical for 
emotion processing require access to highly distributed neural networks in order 
to fulfill their function, as the brain is capable of activating a global response to an 
emotional stimulus. The involvement of these areas in emotion processing and 
memory demonstrate the importance of the interaction between these two 
cognitive abilities and the impact that arousal systems can have on memory and 
information processing more generally.  
 The model developed by Derryberry and Tucker (1992) functions 
according to how appetitive or aversive the qualities of a stimulus might appear. 
For example, we may react according to the degree which an environmental 
stimulus generates physiological arousal. The emotional structures involved in the 
initial appraisal are suggested to be essential in the evolution of our species, as 
these structures have become integrated among all of our cognitive processes by 
elaborating on fundamental mechanisms of perception. For example, emotion 
 15 
contributes to the perceptual modality of vision through the activation of express 
saccades. This can be seen in the case of the thalamus filtering sensory 
information to be sent via the ventral pathway before sending information to 
cortical structures involved in higher order cognitive processing. Due to the 
complex nature of the neural pathways involved in processing emotional stimuli, 
higher cognitive functions such as memory and learning are often regarded as 
automatic functions influenced by our ability to discern emotional cues within our 
environment so that more emotional information is given priority, as this 
information could be detrimental to our survival.    
 The concept of survival mechanisms was also addressed by Tucker and 
Williamson (1984) in a review of the neurotransmitter systems that underlie 
motor readiness. By changing the qualitative nature of the information perceived 
in our environment, subcortical substrates can give priority to emotional 
information and cue the activation systems related to perceptual arousal and 
motor readiness. Evidence that dopaminergic pathways can be traced to the basal 
ganglia is suggested as the foundation of postural readiness and motivated 
attention, two crucial components of the fight or flight response (Tucker & 
Williamson, 1984). Dopamine is an excitatory neurotransmitter related to motor 
performance generated in the basal ganglia and it is shown to innervate cortical 
areas of the left hemisphere that are involved in reward systems. This evidence 
demonstrates how specific neurotransmitters operating on the level of motor 
behavior are integrated with our neural systems involved in emotion processing. 
 16 
Here, Tucker and Williamson suggest that reward systems use dopamine to 
initiate approach behavior. 
 Additionally, Tucker and Williamson (1984) discuss noradrenergic 
pathways initiated by the locus coeruleus as the basis for perceptual awareness, 
which is necessary for regulating arousal. More specifically, norepinephrine is 
described as having the ability to regulate neural systems by using an advanced 
filtering mechanism in order to find novel stimuli in our environment. This 
subcortical model based on evolutionary significance, motor readiness, and 
arousal advanced by Tucker and colleagues is consistent with another subcortical 
model of emotion referred to as the theory of Motivated Attention.  
 The theoretical construct of Motivated Attention has been of particular 
interest to the research of Bradley and Lang (Lang et al., 1997; Bradley et al., 
2001; Bradley et al., 2003; Schupp et al., 2004; Hillman et al., 2004). This theory 
states that evolutionarily significant stimuli in our environment activate the 
subcortical arousal networks necessary in order for the resources of cognitive 
mechanisms such as attention and memory to be allocated to a particular stimulus 
(Lang et al., 1997; Cuthbert et al. 2003). Bradley and colleagues have put forth 
distinct sets of stimuli that allow Motivated Attention to be tested. Among their 
methodological tools, the International Affective Picture System (IAPS; Center 
for the Study of Emotion and Attention [CSEA], 1999; Lang, Bradley, & 
Cuthbert, 1999) has been shown to be an efficient tool used to stimulate appetitive 
or defensive responses significant to the evolutionary mechanisms regarded as 
emotion. The theory behind this method of emotion elicitation is that salient 
 17 
pictures containing emotionally significant material will activate the same neural 
circuitry related to appetitive and defensive action that is required to assess 
stimuli in our natural environment (Bradley et al, 2001). In this research, it is 
assumed that the semantic content of the pictures (i.e. the situation depicted) 
elicits a physiological response comparable to encountering the real life event. 
 The research conducted in Schupp et al. (2004) is a typical example of 
research in emotional picture processing. Emotional imagery was found to be 
effective due to informational salience and its ability to capture attentional 
resources by depicting highly motivating cues containing evolutionarily 
significant material. An example of this material could be hunger, inspired by the 
evolutionary significance of energy consumption, which could be depicted 
through the image of a delicious piece of cake. This research investigated the 
effectiveness of imagery to elicit an emotional response. The researchers 
anticipated that the quality of content-specific imagery within pleasant and 
unpleasant categories would have a significant effect on emotional perception. 
Pictures of erotica and human threat are considered highly arousing and capable 
of eliciting the most significant responses as they depict moments personally 
relevant to survival, thus encouraging a more thorough evaluation. The research 
by Schupp et al. (2004) tested whether attentional resources are limited and 
whether the emotional content of the pictures would significantly occupy these 
resources. 
 Schupp et al. (2004) presented subjects with emotional pictures previously 
indexed according to their degree of valence and arousal (IAPS: Bradley & Lang, 
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1995), respectively. Content of the emotional imagery was selected as an 
independent variable and physiological responses were recorded as dependent 
variables. At the onset of each picture, ERP responses were recorded with special 
consideration for the late positive potential (LPP), a component associated with 
increased and prolonged attention. Irrelevant to valence, the LPP was found 
according to the arousal levels of the pictures, with the highest LPP found in 
response to human mutilation (i.e. highly arousing, highly negative). Startle 
probes elicited P300 responses, providing further evidence of motivated attention 
while also providing a measure of attentional resources that are being assigned to 
stimuli of evolutionary value. Smaller P300 responses during the viewing of 
arousing pictures provided evidence of attentional resources being occupied and 
prolonged for significant periods of time compared to neutral pictures. Pleasant 
pictures caused the smallest P300 responses compared to unpleasant pictures, 
with highly arousing erotic pictures causing the smallest overall response.  
 This electrophysiological evidence of sustained attention for stimuli with 
high levels of arousal suggests the potential of evolutionarily significant material 
to access our attentional and emotional motivation. Furthermore, this evidence 
demonstrates the motivational significance of highly arousing emotional stimuli, 
with a particular significance for high arousal content (i.e. erotica) to engage 
mental resources conceivably due to the evolutionary implications for 
reproduction. This study also illustrates how the P300 component can be modified 
as a function of valence. 
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 Two additional dependent measures implemented by Schupp et al. (2004) 
were blinks, which were also elicited with a startle probe, and skin conductance 
response (SCR). Blink response amplitudes were most pronounced for unpleasant 
pictures, with the largest blinks caused by images of human threat and mutilation. 
Pleasant pictures showed blink inhibition with the most inhibition for erotic 
pictures. This measure again supports evidence of the appetitive and defensive 
mechanisms involved in emotion processing, as the most pronounced blink 
responses were caused by high arousal emotional stimuli. More importantly, this 
measure provides further evidence for an effect of valence, which revealed a trend 
significant for distinguishing between these appetitive and defensive systems. 
Blinking has obvious implications for avoidance strategies, while approach 
strategies are reasonably suggested by blink inhibition. Lastly, the largest changes 
in SCR were found when participants viewed high arousal pictures. This effect 
was found in both pleasant and unpleasant valence categories. The SCR measure 
was not found to be significantly modified by picture valence, though there was a 
slightly larger change in SCR for unpleasant pictures compared to the pleasant 
pictures. For Schupp et al. (2004), imagery elicitation efficiently isolated specific 
attributes of the emotional processing of highly arousing pictures of sex and 
violence, all of which are most likely relevant to the processing of evolutionarily 
relevant stimuli. 
 In a different lab, Davidson (2000) also measured eye blinks as 
participants viewed negative pictures from the IAPS. In this study, some 
interesting individual differences were measured and Davidson concluded that his 
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results show evidence of distinct emotion regulation strategies. In this case, a 
strategy of emotion regulation refers to an individual?s ability to cope with an 
environmental stressor. Startle probes were presented while participants viewed 
emotional pictures and this measure gauged the extent to which an emotional 
response was elicited. Startle probes given at the offset of the pictures reflected 
the participant?s ability to regulate the experience of negative emotion. A larger 
magnitude of blink responses to negative pictures was found in participants with 
greater right side activation displaying an inability to suppress affective influence. 
Participants that showed stronger left-lateralized activation were successfully able 
to regulate affect and showed a less magnified blink response.  
 These findings of Schupp et al. (2004) and Davidson (2000) demonstrate 
how imagery is considered a technique highly capable of inducing an acute 
emotional state with the potential to effectively modify the perception of valence 
and intensity (i.e. level of arousal). Whereas using pictures has the ability to 
motivate a general response to emotional cues according to valence and arousal, 
researchers are investigating the ability of other elicitation techniques to induce 
discrete emotional responses.  
 Presenting motion pictures as a medium of elicitation of valence and 
arousal is also common and researchers are investigating whether this medium 
has the ability to elicit a more discrete emotional response due its dynamic nature 
(Gross & Levenson, 1995; Rottenberg, 2007). Unlike static imagery, film 
elicitation has the advantage of more closely simulating perception in our 
environment. However, film also carries the disadvantage of producing unreliable 
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responses, as the viewer can attend to different stimuli and several viewers could 
interpret film content in different ways. Therefore, a dependable set of film 
stimuli has yet to be established that is as effective as the IAPS. Gross and 
Levenson (1995) successfully attempted the objective of gathering a sample of 
existing films that would consistently elicit discrete emotional responses. 
Working from of a collection of 248 commercial films and two neutral film 
segments, these researchers identified 16 films that successfully demonstrate 
specific categories of emotion where one type of emotion predominated over the 
others. The experiment resulted in 7 films with the ability to reliably elicit a 
discrete emotional response.  
 In order to identify these films, 78 films were shown to 31 different groups 
out of a total of 494 participants. After each film, participants were asked to rate 
their emotional experience during each film according to an inventory that 
contained an 8 point Likert scale of intensity for each of the following 
possibilities: amusement, anger, intensity, confusion, contempt, contentment, 
disgust, embarrassment, fear, happiness, interest, pain, relief, sadness, surprise, 
and tension. Films varied in their reliability to elicit an isolated emotion and films 
in the categories of amusement, disgust, and sadness were most consistent as 80% 
of the participants submitted an isolated response. Anger, contentment, fear, and 
surprise were somewhat successful in their ability to create consistent response. 
The category of intensity was significant with disgust, which elicited the highest 
intensity response, followed in order of strength by amusement, anger, sadness, 
surprise, fear, and contentment. However, these results did not correlate with 
 22 
ratings of discreteness or how distinct these emotions are when defining them 
individually. The level of discreteness demanded by empirical researchers in the 
field may decide how effective these films are. Gross and Levenson concluded 
that finding completely isolated emotional responses using motion pictures is an 
arduous task and have not further developed their film set.  
 This study provides evidence for the potential of film elicitation to allow 
for more complex emotional feedback in the case of particular emotions, but 
exercising the full potential of this technique will be far from complete until an 
effective set of films is established and replicated. Many of the films used in this 
study were commercially available and viewed previously by some participants; 
these participants showed more intense responses. This issue of individual 
differences may have significantly affected the ability of this technique to elicit a 
reliable emotional response, though this technique is endowed with the potential 
to induce emotion at an advanced level as the visual and auditory perceptions 
when viewing motion pictures closely resemble that of an ecologically valid 
experience similar to our perception of reality.       
 The issue of individual differences has received considerable notice within 
the domain of emotion. Cortical structures and, in particular, the lateralization of 
cerebral hemisphere activation has been an important contributor to how 
individuals process information differently. Emotional information can 
significantly initiate lateralized activation of the cortex and the issue of individual 
differences plays a significant role in the cortical models of emotion literature.  
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A summary of this section on subcortical systems suggests that the organization 
of the brainstem and subcortical systems is critically important for the 
components of activation and arousal to meet their evolutionary goals and 
influence global emotion systems throughout the body (Tucker & Williamson, 
1984; Derryberry & Tucker, 1992; Bradley et al., 2001). The appetitive and 
withdrawal behaviors that are influenced by these subcortical systems are often 
thought of as automatic and the patterns of lower-level activation can also be 
considered primarily to be the unconscious experience of emotion (Derryberry & 
Tucker, 1992; Damasio, 1998; Damasio, 2000).  
 The global aspects of emotion processing may subsequently allow whole 
brain responses that are better prepared to manage spontaneous and changing 
stimuli found in our environment. However, the complex environmental stimuli 
that communicate emotion likely require the activation of structures necessary for 
more than basic cognition, as survival strategies often require more thorough 
processing undertaken by the cerebral cortex. In particular, the cerebral right 
hemisphere (RH) is likely to participate relative to the emotional intensity of the 
stimulus (Tucker, 1981; Borod, Bloom, & Haywood, 1998), as will be illustrated 
in the following section. Theories that discuss hemispheric processing will play a 
key role in establishing the contribution of cortical structures to emotion 
processing. We will now direct our focus to the literature that considers cortical 
structures more directly. 
 
 
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Cortical Models of Emotion 
 Whereas subcortical models originated from the James-Lange theory of 
emotion that is concerned with perceived bodily changes, cortical models of 
emotion diverge with the argument that emotion is the cause of change in the 
body. The theories based on underlying, unconscious mechanisms of emotion are 
important for understanding behavior, but in order to lead an extensive discussion 
of the nature of emotion, we must also consider the fact that conscious perception 
and that emotion can be initiated by cortical tissue. As an alternative to the James-
Lange theory of emotion, Walter Cannon and Philip Bard (1920) asserted that the 
cortex initiates emotion-related behavior. Their theory suggests that conscious 
awareness plays a critical role in emotion processing. 
 Though we assume that subcortical structures are organized according to 
their responsibilities specific to processing incoming stimuli that require an 
assessment of emotionality, we must also consider the possibility that this 
organization is a coincidence. Given this possibility, it is essential to gather 
evidence from other domains in cognitive neuroscience to further establish the 
order of emotional brain systems. Support for organized emotional networks have 
been found elsewhere and, when considering research on the emotional 
functionality of the cerebral cortex, we find further evidence that our brain 
anatomy is organized for appraising specific stimulus attributes hemispherically 
(Davidson, 2000).  
 In a review of his work on laterality, Richard Davidson (2003) considers 
the effects of emotion on language processing using evidence from brain imaging 
 25 
and electrophysiological techniques. His work has found that the efficiency of 
eliciting an emotional reaction from participants in his lab is influenced by 
individual differences in emotion processing (Davidson, 2003). His elicitation 
measures, such as watching an emotional film or viewing emotional imagery, are 
used as a means of identifying the underlying patterns of individual biases in 
attention and susceptibility to the content of an emotional stimulus (Davidson et 
al., 1990; Wheeler, 1993; Davidson, 2003). Unique circumstances arise when 
dealing with emotionality and personal experience and Davidson?s term ?affective 
style? refers to a reaction that is unique to each participant as a result of his or her 
adaptation to the environment and the individual?s ability to regulate emotion 
(Davidson, 1994; Davidson et al., 2000; Davidson, 2003). Davidson speculates 
that the differences in how we process emotional information individually are 
influenced by amygdala and activity in the prefrontal cortex (PFC), a brain region 
assumed to play an important role in higher order cognition (Wheeler, 1993; 
Davidson, 2001; Davidson, 2002). 
 Anticipation and inhibition are important roles undertaken by subcortical 
structures, but specific areas located within the PFC are also involved in these 
cognitive functions (Wheeler, 1993; Davidson, 2001; Davidson, 2002). 
Davidson?s claim is that a specific hemisphere of the PFC is activated under 
circumstances that involve decisions on whether approach or withdrawal from a 
particular object or behavior, and lateral activation is especially necessary when 
goals are inconsistent with the initial information appraised from a stimulus, such 
as when pain from an injury is encountered while eating a delicious fruit or 
 26 
potential food can be made of a dangerous animal (Davidson et al., 2000; 
Davidson, 2003). The PFC influences reactions when faced with uncertainty or 
when a novel response is necessary for more elaborate goals (Davidson, 2003). 
Davidson focuses on individual biases in emotion responses localized in the PFC 
and how hemispheric specificity can influence these particular reactions. 
 Davidson has found more activation in a particular hemisphere relevant to 
the valence of emotional stimuli and his laterality hypothesis has successfully 
predicted whether individuals will respond with a valence bias, as in when 
stronger activation for negative information is observed among certain 
individuals. Much of Davidson?s work shows a laterality bias for positive stimuli 
in the left hemisphere (LH), while the right hemisphere (RH) seems to be 
activated by negative material and Davidson has attributed each hemisphere with 
its respective valence processing bias. There is a considerable amount of literature 
documenting hemispheric differences in PFC activity as a function of emotional 
valence (Davidson, 1992; Davidson, 2003; Heller, 1993). 
 Possible alternatives to Davidson?s valence theory of hemispheric 
specificity have suggested that the LH serves an inhibitory role over the RH in 
emotion processing (Tucker, 1981; Tucker & Williamson, 1984). For example, 
when enhanced activation of the RH is found in response to negative stimuli, this 
alternative explanation indicates this is due to a lack of LH inhibition over the 
RH. Research presented by Don Tucker also has implications for research related 
to hemispheric processing (Tucker, 1981; Tucker & Williamson, 1984; 
Derryberry & Tucker, 1992) and his reviews encourage researchers to consider 
 27 
the interaction of the two cerebral hemispheres. More specifically, Tucker 
emphasizes that, regardless of asymmetry, a natural balance between the cerebral 
hemispheres is necessary for normal, unbiased cortical activation and accurate 
information processing.  
 Tucker (1981) and Tucker and Williamson (1984) also raise the issue of 
whether the emotional processing contribution of PFC in the left and right 
hemispheres is due to activation or inhibition. More specifically, the inhibition 
theory suggests that the LH plays a large role in emotion processing as an 
inhibitory mechanism over the emotional activation of the RH. The LH has shown 
enhanced activation in cases of anxiety, while the RH has been shown to have less 
activation in cases of clinical depression and somewhat less activation in the case 
of individuals exposed to negative mood induction (Tucker, 1981). Furthermore, 
in what could be called Tucker?s state-dependent theory of mood, he suggests that 
the reduced activation of the RH in depression is due to the transient nature of 
depression-related behavior. Lack of inhibition, hence, lack of activation in the 
LH is proposed as the actual cause of depression, as this is similar to the 
inhibitory influence of cortical structures on responses taken on by the limbic 
system. 
 Derryberry and Tucker (1992) discuss how the RH is more capable of 
applying integrative strategies involving global connections between different 
brain structures. They suggest that this hemisphere is more capable in the 
communication of emotion as the RH has stronger connections with areas outside 
the brain. At the neuronal level, overlapping axonal connections are prevalent in 
 28 
the RH, suggesting networks that are more highly distributed. The RH also is 
more responsive to stimulus-induced physiological responses that distribute 
activation more generally across the brain as opposed to focused, localized motor 
responses more common in the LH. Tucker?s theory of laterality is further 
supported by evidence of the primarily inhibitory nature of dopamine and its 
prevalence in the LH. The evidence provided by Don Tucker to support his 
inhibition theory does not specifically make a distinction between subcortical and 
cortical structures.   
 Subcortical anatomy is also considered by Davidson (2001; 2002; 2003) as 
he illustrates the importance of the amygdala and its crucial function in the 
motivation of further processing so that attentional resources can be directed in 
proportion to the emotional significance of a stimulus. Davidson assumes a 
general role of the amygdala in emotion processing, though his evidence suggests 
a negativity bias in this structure that is reasonably due to an evolutionary 
proclivity to react aversively when confronted with novel stimuli as a defensive 
precaution (Davidson, 2003). After initial assessment of an environmental 
stimulus and the immediate reactions necessary are considered, a more complete 
evaluation can make sense of ambiguous properties. Therefore, Davidson?s 
position regards cortical processing as playing a larger role in evaluating 
emotional stimuli, as emotional information requires more advanced processing 
than that which can occur at the arousal level in the subcortex (Davidson, 2003).  
 Electroencephalography (EEG) is a frequent method for examining 
emotion processing at the cortex. Davidson (2003; see also Wheeler et al., 1993) 
 29 
describes an investigation in his laboratory that tested whether cortical activation 
is a valid means to test an individual?s sensitivity to emotion elicitation using film 
clips. In order to detect lateral asymmetries in hemispheric activation, a baseline 
EEG response was collected as a dependent measure of activation before positive 
and negative film clips were used to induce a transient valenced mood state. In 
addition to the EEG measure, participants were asked to rate their emotional 
experience during the films.   
 Baseline responses were averaged using a within-subjects analysis in order 
to compare the level of mood change and, as predicted, the results showed a 
positive correlation between a lateral activation bias and the degree of valence 
response given. Participants with more LH activation at baseline rated their 
experience during the positive films as more affectively positive, while those with 
stronger RH activation at baseline demonstrated that they experienced negative 
films as more negative than participants with greater baseline LH activation. 
Davidson (2003) reported that physiological data collected before the 
experimental trial indicated a personality bias and effectively predicted 
participant?s reaction to emotional stimuli. Davidson and colleagues focus on 
individual difference biases in emotion processing localized in the PFC and they 
investigate what hemispheric specificity can tell us about personality. Davidson 
(1994) and Davidson, Jackson, and Kalin (2000) suggest that emotional 
experience can change frontal EEG patterns of activity. 
 Personality is relevant to the current research as personality traits in the 
form of negative attentional biases can indicate symptoms of dysphoria. Our 
 30 
investigation will induce a transient negative mood state in order to investigate 
what aspects of sentence processing are trait-specific compared to aspects of 
emotional cognition related to current mood state. The focus on mood-state 
specific processing has been influenced by research that has looked at aspects of 
how depressed individuals process emotional words (reviewed by Gotlib & 
Neubauer, 2000).  When considering theoretical models of cognitive bias in 
depression, researchers must make a distinction between the state-dependent 
aspects of current mood and those better accounted the enduring trait-specific 
characteristics of cognition influenced by affective experience (see discussion by 
(Matthews & MacLeod, 1994). 
 A discussion of how emotion is organized at the cortical level suggests 
that appraising an emotional stimulus is more complex than the automatic 
responses initiated by subcortical structures. In order to discuss trait-specific 
differences in personality versus more fluctuating state-specific phenomenon, we 
will consider models of emotion that consider how mood state is modified at the 
cortical level and how life experience and mood state interact.  
 
Factors that Modify Emotion Processing 
 By state-specific processing, the current research refers to the idea that 
mood can influence how we process emotional content, as in the case of how we 
remember emotional content while in a negative mood (Kenealy, 1997; 
Chepenick et al., 2007). Our definition of trait-specific processing refers to the 
influence of stable cognitive traits that occur over a prolonged time period and 
result in cognitive biases that are persistent irrespective to mood. For example, an 
 31 
individual diagnosed with clinical depression is likely to have distinct personality 
traits developed throughout his or her experience with affect that influence lexical 
organization (Atchley, Ilardi, & Enloe, 2003).  
 In making the distinction between trait-like versus state-like systems, 
Wendy Heller (1990; 1993) proposes that the modification of emotional 
experience is localized in the PFC. She presents a definition of emotional state as 
a function of this system combined with the RH, which has a more long-lasting 
role in personality and on-going attentional biases. Heller?s model of emotional 
state utilizes the Circumplex model of affect (Lang et al., 1985; Russell, 1980), a 
multidimensional continuum illustrated by 2 overlapping axes: valence and 
arousal. According to the model, all possible emotional states fall somewhere in 
the four quadrants that range from high to low (arousal) and pleasant to 
unpleasant (valence). The current study has adopted this theoretical approach as 
the emotional stimuli range from pleasant to unpleasant, though only items rated 
low in arousal will be used in the current design.  
 The connectivity model is a theoretical construct in the depression 
literature that considers this trait-specific approach. In this theory, the absence of 
executive control causes allows for compensation initiated by subcortical 
structures that inappropriately employ emotional resources in generating a 
physiological response (see discussion by Levin et al., 2007; for executive 
function and the role of PFC, see Miller & Cohen, 2001). Without higher-order 
control over cognitive resources, brain structures in the limbic system that are 
strategically positioned along pathways oriented for stimulation and the initiation 
 32 
of behavior may respond improperly to the environment and, in the case of 
depression, show a negative bias in attention (Gotlib, Ranganathand, & 
Rosenfeld, 1998; Davidson, 1993).  
 The amygdala plays a significant role in emotion processing and 
hyperactivity in this structure has been found in some cases of depression (Beck, 
2008; Davidson, 2003). This structure being hyperactive can lead to depressive 
symptoms as it is primarily involved in the evaluation of aversive stimuli (Beck, 
2008; Davidson, 2003). This structure has great significance in the development 
of the central nervous system as it processes information critical for survival. The 
amygdala has significance for depression particularly as it activates during the 
processing of stressful life events (Levin et al., 2007). According to Levin et al. 
(2007), regular exposure to stressful events, activating the amygdala and other 
structures involved in stress response networks, could contribute to a general 
tendency to respond aversively and develop response patterns resembling those 
found in depression. 
 With stressful experiences recurring early in life, physiological systems 
affected by emotional cues from the environment have the potential to adapt and 
depression symptoms could develop (Levin et al., 2007). This adaptation to the 
environment can influence the cortical and subcortical regions already discussed 
in the current review related to emotion. This includes the lateralization of brain 
activation and the release of regulatory hormones and neurotransmitters in 
response to persistent signals in an individual?s surroundings (Teicher et al., 2003; 
McEwen, 2007; Gunnar & Quevedo, 2007). In mood disorders such as 
 33 
depression, different biological patterns can develop across an individual?s 
lifespan in response to stress and anxiety, emphasizing the connection between 
depression, environmental stimulation, and the biological substrates that modulate 
emotional reactivity (Klaasen et al., 2002).  
 Impairment in the hippocampus can lead to hyperactivity in the amygdala 
resulting in symptoms of depression (Levin et al., 2007). Those with recurrent 
exposure to stress might experience ambiguous circumstances as stressful and 
have an inclination to respond aversively to stimuli they encounter in their 
environment. How hormonal mechanisms in the brain are activated in early 
experience, particularly due to stress, and the impaired ability to regulate 
emotional experiences can be an important factor in whether an individual will 
develop a mood disorder. Activation of hormonal mechanisms related to stress 
can alter emotional structures in the brain or lead these structures to function 
inappropriately. In the current study, we are interested in the biases in emotion-
related language processing that can occur as a result of affective experience.  
There is evidence to suggest that emotional language processing is a trait-like 
phenomenon as similar biases occur in depression and remission from depression 
(Atchley, Ilardi, & Enloe, 2003). Similar biases in attending to emotional 
information are suggested to exist in mood-state specific cases of dysphoria 
(Siegle, Ingram, & Matt, 2002). However, other evidence is available to suggest 
that attention to emotional information is a state-like phenomenon (Ilardi et al., 
2007; Ilardi & Craighead, 1999). 
 34 
 Research in depression has contributed to our knowledge of hemispheric 
specificity and how we process language (Borod, Bloom, & Haywood, 1998; 
Atchley, Ilardi, & Enloe, 2003). For example Richard Davidson has assigned the 
role of the RH to process negative stimuli and processing deficiencies here could 
suggest negative attentional biases (Davidson, 2003). According to Davidson?s 
theory of emotion, depression is indicated by specific patterns of activity and the 
development of problems in the PFC can result in cognitive deficits, further 
indicating the potential role of the PFC in emotion processing (Kim & Hamann, 
2007; Davidson, 1995).  
 The authors discussed thus far have suggested that there are consistencies 
in emotional experience and consistent patterns in the evidence presented related 
to individual differences. Research by Levin, et al. (2007) indicates the potential 
for changes in the environment and life events to contribute to biological 
abnormalities that may result in a deficiency when these individuals encounter 
specific kinds of information having emotional significance. 
 Given that emotion-related experience and anxiety directly influence how 
future emotion-related stimuli will be attended to and categorized, our discussion 
will take into account the research on mood state specific processing more 
specifically. Mood elicitation and the issue of how affective content is processed 
while experiencing valenced mood states has been addressed extensively (Zevon 
& Tellegen, 1982; Watson & Tellegen, 1985; Kenealy, 1997; Tucker et al., 1999; 
Davidson, 2003; Chepenick et al., 2007; Coan & Allen, 2007) and there is a range 
of evidence to suggest that mood is related to subcortical, limbic, and cortical 
 35 
structure activation, particularly localized to such as the amygdala, hippocampus, 
hypothalamus, and specific areas of the PFC (Heller, 1990; Heller; 1993; 
Davidson, 1990; Tucker 1981; Derryberry and Tucker; 1992).  
 Studies utilizing state-dependent processes implementing mood elicitation 
with normal populations as well as trait-dependent processes with depressed 
patients have been shown to reliably estimate how individuals can uniquely 
process information that they encounter in their environment (Gotlib & Neubauer, 
2000). The external factors considered to influence affective experience are 
exemplified language, as in lexical access (Atchley, Ilardi, & Enloe, 2003), and 
picture processing (Bradley et al., 2001; Schupp et al., 2004). Resting baseline 
activation in response to emotional stimuli is also susceptible to environmental 
change related to affective experience (Davidson, 1994; Davidson et al., 2000). 
 The current study will look specifically at what aspects of cognitive 
processing are dependent upon mood state. More specifically, we will investigate 
how processing sentences containing emotional context changes after an induced 
negative mood. Our sample will use non-depressed participants in order to assess 
the potential for differences in mood to show distinct patterns of performance on a 
plausibility task for self-referent sentences. We are interested in how mood 
changes semantic access for emotional words in a sentence and also how a 
negative mood changes the perception of self-referent content.  
 We will investigate cortical involvement in emotion by engaging the 
cognitive processes involved in linguistic processing and aspects of higher order 
cognition considered in the domains of language and memory. In order to provide 
 36 
a thorough description of the goals of the current study, it is necessary to look at 
the literature on emotion and language. The following section discusses how 
emotion has been considered an important factor in the study of language 
comprehension.  
 
Influence of Emotion on Higher Order Cognition 
Emotion and Language 
 Although there is considerable evidence presented in this review to 
suggest that emotion influences subcortical structures and the nervous system, 
much remains to be established in the domains of language and emotion and what 
these domains can tell us about the contribution of the cerebral cortex to 
emotional language comprehension. Our study is critical as there is limited 
evidence for how we process emotion words at the sentential level (Havas, 
Glenberg, & Rinck, 2007; Hale, 2003; see review by Shanahan, 2008). As part of 
the background to the current research, we will discuss the findings on emotional 
language processing more generally.  
 In a review by Daniel Shanahan (2008), language is considered a vehicle 
for emotional symbolism. He cites Robert Haskell?s (1987) view that language 
conveys meaning and serves to evoke the unconscious schemas that influence our 
thoughts and behavior through the construction of meaning. The models put forth 
by Aaron Beck (2002) give incredible insight into how these schemas might 
influence cognition as a function of life experience. He considers self-schemas 
consistent with a negative self-evaluation relevant to the cognitive aspects of 
depression. The current study will apply Beck?s model by investigating what 
 37 
aspects of mood change how participants judge the plausilibility of sentences that 
are consistent with a positive self-schema and those consistent with a negative 
self-schema. Other work considering emotion and language has explored the 
localization of the mechanisms behind emotion processing in order to better 
understand how language influences cognition. 
 Carl Broca?s work indicated the LH as the seat of language, but it is now 
widely accepted through lateralized brain damage patient evidence that the RH 
possibly plays a larger role in the comprehension and expression of emotional 
language (see review by Beeman & Chiarello, 1998), especially in the case of 
depression (Borod et al., 1998; Atchley, Ilardi, & Enloe, 2003). For example, 
interpreting prosody in speech is regarded as superior in the RH. Prosody that is 
congruent with the content of a sentence has been shown to generate faster 
responses (Nygaard & Queen, 2008). Other examples include the ability of the 
RH to comprehend the narrative of a story and to interpret metaphors due to more 
globally organized semantic access. Many researchers have presented work that 
discusses emotion as being conveyed through the context of language (Barrett, 
Lindquist, & Gendron, 2007; see review Shanahan, 2008) and we now turn to a 
consideration of how emotion influences semantics. 
 Atchley, Ilardi, and Enloe (2003) investigated laterality and semantic 
memory access for emotional words using population samples that varied by 
affective experience. These samples consisted of 23 depressed, 28 remitted-
depressed, and 23 never-depressed controls recruited in an introductory 
psychology course. Behavioral data were collected to investigate hemispheric 
 38 
differences using a priming task with primes presented centrally and targets 
presented using a divided visual half-field paradigm. For their dependent variable, 
participants were asked to make a valence judgment between two words, while 
these researchers recorded reaction time to the valence judgment. Each pair of 
words was evaluated by participants as either related in valence (STUPID-
DIRTY) or unrelated (BRAVE-LAZY). As independent variables, these 
researchers used diagnostic group, valence of the target word, whether the word 
pairs shared the same valence and whether the target word was presented to the 
left or right visual field. 
 The results showed that all 3 population samples demonstrated a 
processing advantage for related pairs presented to the RH (i.e. in the left visual 
field) and this processing advantage was positively correlated with affective 
experience. In the RH, currently depressed and remitted-depressed participants 
showed higher accuracy and faster responses for related pairs of negative valence. 
A RH advantage was also observed among the never-depressed control population 
and this sample showed better accuracy and faster responses for positive items. 
This study provides evidence that semantic networks in the RH are organized 
according to affective experience and, as remitted depressed showed the same 
pattern as the currently depressed. These results using emotional words provide 
evidence that semantic networks are organized in a trait-specific manner.  
 Investigating laterality in response to emotional stimuli presented using 
the divided visual half-field paradigm, Atchley, Ilardi, and Enloe (2003) found 
that language and emotion have a distinct function in each cerebral hemisphere. 
 39 
This paradigm allows for information to be exposed to either the left or right 
hemisphere exclusively by presenting the stimulus to either the left or right visual 
half-field of each eye while participants focus on the center of a computer display. 
The stimulus is presented briefly so that participants unable to move their eyes, as 
to prohibit both hemispheres from gaining access to the information presented. 
Consistent with evidence that the RH has an advantage for processing emotional 
language as in the case of  speech and the facial communication of emotional 
speech (Borod, Bloom, & Haywood, 1998), these researchers found improved 
accuracy and faster responses occurred for stimuli presented in the left visual 
field, supporting the role of the RH in emotion processing. 
 The results of Atchley, Ilardi, and Enloe (2003) are incompatible with 
evidence that has been found showing a LH advantage for positive emotions 
(Davidson et al., 1990) and an overall LH advantage for word processing 
proposed by Carl Broca. This discrepancy is most likely due to the complicated 
nature of cortical processing and linguistic functions being attributed to the LH, 
which activates simultaneously upon the presentation of an emotionally latent 
language stimulus. Results for dominance in the RH for processing emotional 
language are complicated by this overlap in hemispheric processing and it is 
therefore necessary to utilize the visual half-field paradigm to uncover RH 
processes. Research using this paradigm as well as evidence from patient 
populations and lesion patients generally suggest a RH mechanism that 
specializes in emotion processing (Chiarello & Beeman, 1998; Borod, Bloom, & 
Haywood, 1998).  
 40 
 Inconsistent results have been found using normal populations, but 
patients with right hemisphere damage more reliably indicate the function of the 
RH. The research of Borod, Bloom, and Haywood (1998) showed that RH lesion 
patients demonstrated impaired abilities to recognize emotional words and to use 
intense emotional language to express feelings. Speculations on why the RH 
possesses an emotionally specific role in cognition are similar to conclusions 
made by other researchers related to the evolutionary significance of emotion 
processing and functionally distributed processing networks that attribute 
emotional biases hemispherically (Davidson, 1990; Derryberry & Tucker, 1992).  
 Of more relevance to the current study, emotional language has been 
shown affect judgment (Johnson & Tversky, 1985) and evidence from Havas, 
Glenberg, and Rinck (2007) suggests that factors outside of emotion can influence 
the judgment of plausibility. Havas, Glenberg, and Rinck (2007) found that 
judging plausibility is faster when the valence of a sentence matches the 
emotional posture of the face. They postulated that facial posture is simulating 
emotion by partially activating the systems responsible for generating the 
complete emotional response (i.e. smiling with joy). The current research will 
attempt to assimilate previous findings using a mismatch paradigm with the 
induction of a negative mood. We hypothesize that an induced negative mood will 
activate the emotional systems involved in naturally occurring mood, generating 
attention biases in reading comprehension and the judgment of semantic 
plausibility.  
 41 
 Havas, Glenberg, and Rinck (2007) concluded that emotion simulation 
only occurs at the sentential level, as they did not show the same mismatch effect 
using a lexical decision task (i.e. without context). However, these researchers do 
acknowledge that emotion influences word processing when the word directly 
names an emotional state. Their research suggests that emotion is measurable at 
the sentential level and the current design will further these assumptions of Havas, 
Glenberg, and Rinck (2007) by investigating how mood influences sentence 
comprehension.  
 This background on the field of language and emotion gives support for 
models of emotion that are considered trait-specific processing. The work of 
Atchley, Ilardi, and Enloe (2003) and the work reviewed by Borod, Bloom, & 
Haywood (1998) accounts for emotion processing that appears to be less plastic, 
as semantic networks organized by affective experience provide evidence of trait-
specific processing. While the research presented here on processing emotional 
language contributes to trait-specific theories of emotion processing, research in 
the domain of emotional memory has focused more on the aspects of emotion 
processing that are dependent on current mood state.  
 
Emotional Memory 
 The current study aims to contribute to the issue of how emotion 
influences memory and how memory is changed by affective experience. The 
literature on emotion and memory has been particularly influential in the domain 
of mood-specific processing. This review of emotion might suggest that 
emotional information affects attention more than neutral information, making 
 42 
emotional items more available for recall. However, the effects of mood on 
memory performance are more elusive and have been the subject of much debate. 
One of the most prominent dichotomies in the mood and memory literature 
appears to be a focus on mood-dependent effects versus mood-congruent emotion 
processing (for reviews, see: Blaney, 1986; Buchanan, 2007). 
 Mood-dependent effects occur regardless of the stimulus valence and 
refers to the enhanced memory while experiencing a valenced mood, such as 
sadness (Chepenik, Cornew, & Farah, 2007). According to this theory, enhanced 
retrieval will more likely occur while experiencing the same affective state that 
was experienced during exposure to the stimulus (i.e. mood-congruence between 
learning and retrieval). Mood induction has been a common method of testing this 
phenomenon, though the effectiveness of mood induction has been somewhat 
problematic. For example, cognitive priming effects, demand characteristics, and 
a limited amount of time afforded during an experiment are considered obstacles 
encountered when eliciting mood (Blaney, 1986; Buchanan, 2007). 
  Chepenik, Cornew, and Farah (2007) intended to investigate cognitive 
performance using a sustained mood induction technique. These researchers 
found effects for emotion-related cognitive processes, including a recognition bias 
for negative words, but no effects were found for cognition more generally. More 
conclusive findings have been found when investigating the mood-congruence 
theory of memory, to which we next turn. 
 Mood-congruence is indicated by enhanced processing that occurs for 
affective content when the corresponding affective mood is also present. In this 
 43 
case, there is no need for valence and mood to match at the time of retrieval, 
though affective state is likely to cue retrieval. Contrary to mood-dependence, 
results supporting mood-congruent memory have been much easier to replicate. 
Also contrary to mood-dependent theories, research on mood-congruence is more 
often tested using individual differences, where mood induction is not required. 
Research has found increased memory for information congruent with the valence 
of the negative mood as in the case of improved memory for negative information 
congruent with negative mood (Knight, Maines, & Robinson, 2002). This domain 
is also important for research that considers depressed populations and trait-
specific processing models of emotion. For example, mood-congruence studies 
have shown that depressed populations show enhanced processing for failure 
scenarios, while non-depressed populations show enhanced recall for content 
related to success (Johnson, Petzel, Hartney, & Morgan, 1983).  
 Other studies have suggested that the mood-congruence effect is only 
found when using self-referent material, especially in non-depressed individuals 
(Ingram, 1983; Clark & Teasdale, 1985). Furthermore, actual life experience and 
personal descriptors have also been shown to enhance the effects of mood-
congruent memory (Clark & Teasdale, 1985). Several studies have attempted to 
apply these theories of emotion-related memory, but more research is necessary to 
more accurately establish the differences between these two dominant theories as 
well as important findings for emotion and memory. 
 Levine and Burgess (1997) showed evidence for a nonspecific memory 
advantage while in a negative mood state using a study that asked students to 
 44 
recall a short narrative heard during an introductory psychology class. As a 
dependent variable, amount of recall and recall for specific information was 
recorded. Before participating in the recall task, each student was randomly 
assigned a grade that was an ?A, B, C, or D? on a previous test and this served as 
the independent variable. Each student?s grade provided the elicitation of 
emotional affect that was later collected on a survey in which each student 
assessed his or her own mood among possible selections of happy, angry, sad, 
fearful, surprised, and other. Each discrete emotional category included a 5-point 
rating scale that ranged from ?not at all? to ?very much.?  
 Greater recall for the entire narrative was shown for participants that 
selected happy as their emotional state and had received a passing grade. 
Participants that marked angry or sad also showed enhanced memory for certain 
events within the narrative. For example, angry participants showed enhanced 
recall for goal-oriented information and sad participants had better recall for 
information about event outcomes. The authors concluded that a positive mood 
state can show enhanced recall due to leaving cognitive resources available for an 
incoming stimulus. The categories of anger and sadness require further 
investigation, as there was little evidence provided by Levine and Burgess (1997) 
that distinguished between these distinct categories of negative mood.  
 Overall, Levine and Burgess (1997) supports the theory that mood can 
have a specialized influence how memory is encoded. More specifically and 
consistent with the emotion theories in this review, negative emotions were 
attributed to a general attention bias that was congruent with the respective mood 
 45 
state. Also worth noting, this study controlled for demand characteristics as the 
participants were asked to recall a narrative and not to recall emotion-related 
material. Levine and Burgess found that a negative mood state can enhance recall 
and their data support mood-dependent memory. The following study found 
enhanced recall for negatively valenced items and also considered the influence of 
emotional arousal. 
 Kensinger and Corkin (2003) measured recall for negative words and 
neutral words. In a series of 6 experiments, these researchers provided 18-20 
never-depressed male undergraduates with lists of words and then asked them to 
recognize words seen previously after a 15-minute delay. The dependent variable 
in all experiments was recognition accuracy, based on whether they had seen a 
word presented on the previous list. The unique objective of experiments 3 and 4 
was to look at the difference between high and low negative words. Experiment 5 
controlled for a possible recall advantage due to a semantic integration memory 
strategy and implemented neutral words that were all semantically related. 
Experiment 6 controlled for an enhanced memory effect due to high frequency 
words. 
 Kensinger and Corkin (2003) found enhanced memory for negative words 
compared to neutral words, with the greatest recall for highly arousing negative 
words. This effect was present in all 6 experiments. Enhanced recall for negative 
words was also found in experiment 2, indicating greater recall for the color of 
negative words compared to neutral words. In experiments 3 and 4, enhanced 
memory was found for negatively valent items that were rated high and low in 
 46 
arousal when compared to neutral items. No advantage was found for 
semantically related neutral words in experiment 5 and this suggests that semantic 
integration was not a sufficient memory strategy for these participants. 
Experiment 6 did not find an advantage for high frequency words. The authors 
proposed item distinctiveness as a possible reason for enhanced recall on negative 
items as negative items are more semantically salient when compared to neutral 
items. Another conclusion posited by the authors was an attention bias for 
negative words over neutral words. 
 Although the Kensinger and Corkin (2003) study addressed processing of 
negative words in considerable detail, their study did not assess recall for positive 
words. The current study will also present positive words, which we believe is an 
important component to include in attempting to establish a more comprehensive 
report of the effects of emotional content on memory processing.  
 Deficits in memory processing have contributed to our understanding of 
emotional memory, particularly in the case of memory performance in depression. 
The literature on memory in depression is relevant to the current investigation as 
we are interested in contributing evidence to the research problem of whether the 
symptoms of depression are dependent on mood state or related to trait-specific 
factors. Evidence for deficits in memory processing will be considered next. 
 Depressed individuals may generate a bias for remembering negative 
material and a general fixation on negative material. A negative bias has been 
considered a deficit in the management of attention as an inability to efficiently 
encode stimuli in the environment might result in perseverative attention (Levin et 
 47 
al., 2007). The inability to disengage attentional focus from particular stimuli does 
not allow attention to fulfill its evolutionary role to completion and this could 
result in attentional bias. For example, Joorman and Gotlib (2008) compared 
control participants who received a sad mood induction to depressed individuals 
and found negative memory intrusion effects among only the depressed 
population. Joorman and Gotlib (2008) supports mood-state specific memory. The 
results of Chepenick, Cornew, and Farah (2007) found a negative memory bias 
and difficulty recognizing faces after a sad mood induction. Although this study 
did not show a bias in other cognitive tasks, these researchers concluded that 
cognitive biases in depression may not only be due to sad mood.  
 Many cases of depression indicate a problem in the PFC with the initiation 
of effective cognitive strategies when faced with specific emotional stimuli (Levin 
et al., 2007). Deficits in the LH may lead to overcompensation in the RH, which 
predominantly processes negative material. A general decrease in PFC activity 
has also been observed in depressed individuals combined with this negative bias 
in attention (Levin et al., 2007). The role of the RH in inhibition and avoidance 
processing has been well-established and deficits in this region account for an 
inability to initiate avoidance strategies. As suggested by Levin et al. (2007), 
memory deficits in depression may implicate the hippocampus, which plays a 
large role in relating important environmental cues to different brain regions and 
making associations with new information in the environment. Activation in the 
PFC has been shown to be influenced by emotional cues in the environment that 
 48 
require further processing to play a large role in working memory (Davidson 
1999, Schupp et al. 2004).   
 Higher cognitive functions such as attention and memory are affected by 
the emotional significance of an object or situation. Memories that have 
emotionally significant information are more likely to be given priority and be 
readily available for feedback in appraising a stimulus. For example, information 
that is crucial for survival would be assigned this priority and, in the event that 
relevant information is available, processed immediately (Schupp et al. 2004). 
Under this theory of emotion processing, specific structures activate according to 
whether priority is assigned and appropriate objects or situations are given the 
advantage of being processed in a more expedient manner. Whether emotionally 
laden stimuli and this processing advantage apply to memory has received less 
attention in past research.  
 A stimulus that has emotional significance is processed similarly to all 
stimuli in the environment and can activate any appropriate resource in the brain 
necessary to make sense of that stimulus. Therefore, emotional information is 
processed on both cortical and subcortical levels of brain activity, but there are 
particular structures that are most important for emotion processing. Labeling the 
affective significance of incoming information for further processing is done by 
the amygdala and processing aversive information has been shown to be a specific 
objective of the amygdala (Davidson, 2003). This structure becomes active with 
the presentation of emotional stimuli and is important for responding to the 
affective significance of sensory information.  
 49 
 The limbic system lies between cortical and subcortical structures and 
processes sensory information, including that which is emotionally significant, 
before it sends the information to the frontal cortex for higher cognitive 
processing. The amygdala and other limbic structures have also been linked to 
working memory and the storage of permanent memories. In order to make sense 
of complex emotional stimuli, the frontal cortex appraises material that has been 
designated as emotionally significant by these subcortical structures.  
 Research conducted by Kensinger and Corkin (2003) shows an advantage 
for remembering emotionally valent words over neutral words with a greater 
advantage for recalling words with more arousal. Schupp et al. (2004) have 
proposed the same enhanced effect for negative pictures due to motivated 
attention and these researchers suggest evolutionary significance as the reason for 
priority being given to negative emotional material. Emotional memory 
researchers have also found that a negative mood state aids the availability of 
negative memories (Kern et al. 2002) and other research presented by Anderson 
and Shimamura (2005) suggests that this negative mood state decreases memory 
for the context of events. Similar findings have been found by Davidson (2003) 
suggesting poor memory performance while in a negative mood state. Research 
presented by Kern et al. (2002) is inconsistent with poor memory performance 
while in a negative mood and instead indicates that memory performance is more 
likely enhanced by negative mood, particularly when rated high in emotional 
arousal. 
 50 
 The current research intends to provide further evidence of the influence 
of valenced emotional states on memory performance. We will look specifically 
at how information is processed that is self-schema driven (Beck, 2002; Haskell, 
1987) and how we remember emotion-related content more generally. How the 
theories presented in the current review have been applied in the current study to 
non-depressed individuals and their judgment of valenced self-statements while in 
a negative mood state will be discussed in the following section. Competing 
evidence requires the replication of findings in the domain of emotional language 
and memory processing has led to the current empirical goals, and we now turn to 
the experimental design. 
 
Current Empirical Goals and Predictions 
 In order to provide an adequate discussion of the current empirical goals 
and predictions, we begin with a brief summary of our research design. Our 
investigation will assess reading comprehension for sentences and recall for the 
sentence final word. To provide evidence of how mood influences semantic 
processing, the current study will use mood induction technique specifically 
designed to elicit sadness. Data for reading performance and memory 
performance will be gathered on two separate tasks that will be administered 
while in a neutral mood and while in a negative mood state.  
Reading Performance 
 For the reading task, participants will read sentences word-by-word before 
making a decision based on whether they endorse each sentence as semantically 
plausible or implausible. Each sentence will end with either a positive, negative, 
 51 
or neutral target word. Our targets were selected from multiple papers that 
reported valence norms (Gotlib et al., 1988; Myers, 1980; Siegle, 1995; and the 
Affective Norms for English Words [ANEW], Bradley & Lang, 1999). As we are 
currently interested in how participants process the semantic aspects of language, 
our target words were chosen because they are rated low in level of arousal. Our 
three dependent variables for this reading task are reading time (READ) for the 
sentence final word target, reaction time (RT) for making the semantic plausibility 
judgment based on the entire sentence, and response choice (RESP) for the 
plausibility judgment based on whether participants choose to endorse each 
sentence as plausible or implausible.  
 Reading time refers to the amount of time that the target word is present 
on the screen before the participant advances to the following plausibility 
judgment screen. Reaction time measures the amount of time participants take to 
make their plausibility judgment and will be recorded directly after the participant 
advances past the target word. Response choice measures whether the participant 
endorses each sentence as plausible or implausible and this measure will be 
recorded as responding ?yes? (plausible) or ?no? (implausible). Accuracy could 
be a logical alternative description for RESP, though a description of semantic 
plausibility being accurate misrepresents the nature of the data collected in 
Conditions 1 and 2 (eg. I am essentially a failure/I?d call myself a leader). 
 There will be two independent variables manipulated during the reading 
task. Current mood contains 2 levels and will refer to whether participants are in a 
neutral mood state or a negative mood state. The second independent variable for 
 52 
the reading task is sentence condition and this manipulation contains 6 levels. 
Each sentence will vary upon whether the sentence final word is negative, 
positive, or neutral and whether each sentence is a self-referent or other-referent. 
Within the 6 sentence levels, there will be there is also a manipulation of 
plausibility, where each sentence final word will indicate whether the entire 
sentence is semantically plausible or implausible. Six sentence levels will be 
presented to our participants, but conditions 5 and 6 served as other-referent 
distracters or ?filler? sentences and they will not be reported in the reading task 
results section. Four critical sentence levels considered in our analysis and they 
are listed as sentence conditions 1-4. Table 1 shows examples of all of the 6 
sentence conditions [below].  
Table 1 
Stimulus Examples  
_______________________________________________________________________________ 
 
                 Stimulus Condition                                Example Stimulus        
__________________________________________________________________ 
 
  Negative Self-Statements (1)           People consider me to be worthless. 
  Positive Self-Statements (2)                My family thinks that I am interesting. 
  Neutral, Implausible Self-Statements (3)   Others see me as a desk. 
  Neutral, Plausible Other-Statements (4)     Maids often clean the kitchen. 
  Filler Implausible Other-Statements (5)    The weather was cool and printed. 
  Filler Plausible Other-Statements (6)         Terrorists are often thought of as evil. 
__________________________________________________________________  
Table 1. Examples of the 4 main sentence conditions (1-4) and filler sentence examples (5-6). 
 
 Condition 1 contains self-referent statements that end with a semantically 
plausible negative target word, thus, endorsing this condition is not consistent 
with a positive self-evaluation. Condition 2 contains plausible self-referent 
statements that end with a positive target. Conditions 3 and 4 will serve as the 
 53 
neutral control conditions, with condition 3 containing implausible self-referent 
statements that end in a neutral target and condition 4 containing plausible other-
referent statements that end in a neutral target. Due to the difficult nature of 
designing a neutral plausible sentence condition, condition 3 will contain 
implausible sentence final words and condition 4 will serve as a plausible control 
condition that contains the same neutral targets as used in Condition 3. The reason 
for including condition 3 is due to the difficulty in designing neutral self-
statements that are unambiguously neutral. Also, we considered that the 
unambiguously neutral self-statements would not be plausible for every 
participant. Consider the sentence, ?Others consider me to be bearded.? This 
sentence is unambiguously neutral in valence according to our prior norming 
results, but not everyone is bearded, rendering this condition plausible for some 
and implausible for others. The other two conditions present in the current 
experimental design serve as filler sentences and they vary according to the 
valence of the target word as they contain negative, positive, and neutral targets. 
Condition 5 contains implausible other-referent statements and condition 6 
contains plausible other-referent statements.  
 Sentence condition will be entered into the ANOVA as an analysis of the 
4 critical sentence conditions using planned comparisons to assess differences in 
sentence processing between these 4 different types of sentences. Conditions 1 
and 2 are the critical sentence levels as they contain negative and positive targets, 
respectively. These critical sentences are the primary concern of the current 
research design as they were created to allow for the investigation of reading 
 54 
valenced words in a self referent context. Conditions 5 and 6 will not be included 
in the reading performance analysis, though they will be included in the analysis 
for the memory task. 
 As influenced by previous findings, our a priori predictions for the reading 
task are that the data will show that emotional stimuli improve cognitive 
performance (Schupp et. al, 2004; Landis, 2006; Kissler et al., 2007; Herbert, 
Junghofer, & Kissler; 2008; Silvert et al., 2004). This will be shown through an 
overall difference in how participants read sentences that end in emotion-valent 
targets compared to sentences that end with a neutral target. More specifically, 
our a priori predictions for the dependent variables in the reading task are that 
participants will read negative and positive targets faster when compared to the 
neutral targets. We predict that participants will show faster reaction time for 
making the plausibility judgment for conditions containing emotion-related 
targets compared to neutral targets. Regarding the primary sentence conditions 1 
and 2, we predict sentences containing positive words will be read faster overall. 
We also predict a sentence condition by mood interaction will occur for these two 
categories of valenced sentence final words. While in the negative mood, we 
predict an overall decrease in the reading time and reaction time measures as 
compared to the reading time for negative words in a neutral mood. We expect 
that participants will consider negative targets longer because the negative words, 
though less plausible for this never-depressed population, will be consistent with 
their negative mood state. 
 55 
 For response choice, we predict that participants will show a trait-specific 
bias to endorse positive self-statements of Condition 2 and that this response will 
be similar to response choice on the plausible other-referent statements with 
neutral targets of Condition 4. We predict that our never-depressed, non-
dysphoric participants will endorse the critical sentence conditions consistent with 
a positive self- evaluation. In contrast, we expect that participants will judge the 
Condition 1 sentences (with negative final words) as implausible even though 
these sentences are syntactically and semantically possible. A difference between 
conditions 1 and 2 will provide evidence for aspects of trait-specific processing 
found previously (Atchley, Enloe, & Ilardi, 2003; Ilardi et al. 2007).  
 We also predict a significant interaction between mood and sentence 
condition. While in the negative mood, we predict participants be less likely to 
endorse as plausible the positive self-statements Condition 2. Regarding the 
negative sentences of Condition 2, we expect to see a mood-congruent effect on 
reading performance as evidenced by the more likely endorsement of the negative 
self-statements of Condition 1 while in the negative mood. Practice effects are 
inherent in the current design as our procedure did not counterbalance mood. All 
participants were tested in the neutral mood, followed by the negative mood. 
Therefore, the interaction of mood by sentence condition is crucial as it provides 
evidence for mood-state specific effects in reading sentences and for the judgment 
of plausibility. Research regarding the influence of negative mood on reading 
performance is limited (Hettena & Ballif, 1981; Watkins, Teasdale, & Williams, 
 56 
2003; Jacoby, Brewin, & Watkins, 2008;) and the current study intends to provide 
evidence of how mood-state influences language processing.  
Memory Performance 
 The dependent variable to be collected for the memory task is recall 
accuracy. For this task, participants will be asked to recall the target word for 24 
previously viewed sentence stems. Participants will be presented with examples 
of all 6 sentence conditions presented during the reading task and recall accuracy 
will serve as the dependent variable. This dependent variable will be calculated as 
a percentage correct out of the total possible correct in each sentence condition 
(eg. 1.0 = 100% correct, .20 = 20% correct). 
 For the memory task, our independent variable of mood will be the same 
as in the reading task. The memory data will include all 6 sentence conditions and 
include target word valence and self-referent context as independent variables. 
Encoding conditions 5 and 6 for the memory data analysis allows for a more 
comprehensive consideration of how participants remember sentence final word 
targets according to valence and whether there is an advantage for a self-referent 
context.  
 Our a priori predictions for memory performance regarding emotion 
targets are similar to those in the reading task. We predict the data will show 
improved cognitive performance for emotionally-relevant stimuli compared to 
neutral stimuli (Bradley et al., 2001; Schupp et. al, 2004). For example, this 
prediction is consistent with Schupp et al. (2004), who found emotional material 
 57 
requires more mental resources using a startle probe paradigm. This prediction 
will be supported by a significant main effect of target word valence.   
 Based on evidence presented in arousal models of improved memory 
(Levine & Burgess, 1997; Kensinger & Corkin, 2003), our prediction is that a 
negative mood will increase overall recall accuracy with improved memory for all 
sentence targets in the negative mood. The investigation of this prediction will be 
supported by a significant main effect of mood.  
 As we are including only never-depressed we predict enhanced emotional 
recall will occur for positive target words. Considering the mood-congruent 
memory evidence in the current review, we that recall for negative targets will 
increase while in a negative mood state. Our mood-congruence prediction will be 
supported by a significant interaction effect of mood by valence with a planned 
comparison showing that negative targets are more memorable in the negative 
mood.  
 Atchley, Ilardi, Enloe (2003) suggests that positive information is 
processed faster and more accurately in populations that have never experienced 
depression. As our participants are all currently non-depressed, this population 
will show positive bias in the neutral mood that will decrease in the negative 
mood. Atchley, Ilardi, Enloe (2003) found this positive bias in a word valence 
judgment task and we predict that this bias in language comprehension will have a 
similar effect in the domain of memory performance. We predict that if the 
primary influence on memory performance is current mood (i.e. a state-dependent 
effect), then mood should change memory performance for the positive words. If 
 58 
recall memory for the positive targets does not change between the neutral and 
negative moods, the results will be consistent with trait-specific models of 
emotion processing. 
 We will also investigate the influence of self-reference in a 3-way 
interaction of mood by self-reference by valence. This analysis allows for the 
examination of all three independent variables in order to consider how 
remembering negative, positive, and neutral words is affected by reading self-
referent information in a negative mood. Our initial prediction for this analysis is 
that participants will show improved recall for targets that are present in self-
statements. There is evidence for a bias to attend to self-referent information 
(Ingram, 1983) and we predict that the self-statements will be overall remembered 
better than the other-referent sentences presented. We also predict a negative 
memory bias for self-statements while in the negative mood as compatible with 
evidence using depressed populations has suggested a bias to focus on self-
reference while in a negative mood state (Ingram, 1990).  
 
Methodology 
Subjects and Measures 
 Eighty-five (49 males and 36 females, 18-21 years of age) strongly right-
handed Kansas University students were recruited for this study from an 
introductory psychology course in exchange for course credit. Only participants 
with native level proficiency in English and normal or corrected to normal vision 
were accepted. In order to be included in this study, participants must have scored 
between 2 and 9 on the Beck Depression Inventory, which indicates that 
 59 
participants are not currently depressed (Beck et al., 1988). As an additional 
measure that served as part of our inclusion standard, scoring lower than 25 on the 
Inventory to Diagnose Depression-Lifetime edition suggested that participants 
were not currently in a depressed mood state and that they had no history of 
depression (Zimmerman and Coryell, 1987).    
Stimuli and Apparatus 
 Stimuli were displayed on a Dell XPS laptop computer that recorded 
reading time (READ), response choice (RESP), and reaction time (RT) while the 
participants performed the reading task. These stimuli were presented using E-
prime software. Sentences were presented in the center of the screen, one word at 
a time, and participants were allowed to read at their own pace by advancing 
using the spacebar. Two counterbalanced experimental blocks were presented, the 
neutral mood block followed subsequently by the negative mood block. Each 
experimental block contained one reading task and one memory task. Each 
reading task contained 48 randomized sentences, including 24 of our critical 
conditions and each containing 18 self-referent statements. All sentence final 
word targets were chosen according to its negative, positive, or neutral valence 
according to norms reported in previous research (Gotlib et al., 1988; Myers, 
1980; Siegle, 1995; and the Affective Norms for English Words [ANEW], 
Bradley & Lang, 1999). Example sentences are presented in Table 2 [p. 60]. 
 For each experimental block, a memory task was administered and 
recorded using pencil and paper. The stimuli on each memory task included 24 
sentence stems that were presented in the previous reading task and participants 
 60 
were asked to fill in each sentence final word. Each memory task included 12 
self-statements and 12 other-referent statements and all sentence conditions were 
divided equally by valence so that there were 8 negative, 8 positive, and 8 neutral 
sentence targets. Subjects were allowed to work on the memory task at their own 
pace, though they were encouraged to work more quickly after about 10 minutes.  
Table 2 
Sentence Condition Codes  
_______________________________________________________________________________ 
 
   Sentence Condition             Target Valence             Self-Referent     Plausible 
__________________________________________________________________ 
 
                 1                                  Negative                         Yes                 No*  
                 2                                   Positive                          Yes                Yes** 
                 3                                    Neutral                          Yes                 No 
                 4                                    Neutral                           No                 Yes 
                 5                       Negative/Positive/Neutral          No         Yes 
                 6                       Negative/Positive/Neutral          No          No 
__________________________________________________________________  
Table 2. Condition codes for all sentence conditions. *Sentences in Condition 1 are considered 
grammatically plausible, but we have considered them implausible as consistent with a positive 
self-evaluation. **Condition 2 is considered plausible as consistent with a positive self-evaluation.  
 
 
 The independent variable of sentence condition consists of 6 conditions. 
Condition 1 consists of plausible self-statements that end with negative target 
words. Items in condition 1 are considered grammatically plausible, though for 
the purposes of this study, they have been coded as implausible as they are 
inconsistent with a subjective positive self-evaluation. Condition 2 contains 
plausible self-statements ending in positive target words. Condition 3 contains 
semantically implausible self-statements ending with neutral targets. Condition 4 
contains plausible other-referent statements that end with a neutral target word. 
Condition 5 contains plausible other-referent filler sentences that end with 
 61 
alternating negative, positive, and neutral targets. Condition 6 contains 
implausible other-referent filler sentences that end with alternating negative, 
positive, and neutral targets. See table 3 for examples of all sentence conditions 
[below]. 
Table 3 
Stimulus Examples  
_______________________________________________________________________________ 
 
                 Stimulus Condition                                Example Stimulus        
__________________________________________________________________ 
 
    Negative Self-Statements           People consider me to be worthless. 
    Positive Self-Statements         My family thinks that I am interesting. 
    Neutral, Implausible Self-Statements   Others see me as a desk. 
    Neutral, Plausible Other-Statements     Maids often clean the kitchen. 
    Plausible Other-Statements                Tornadoes are a type of natural disaster. 
    Implausible Other-Statements               Albert Einstein was a hamster.       
__________________________________________________________________  
Table 3. Examples of all sentence condition. 
 
Procedure 
 Upon arriving, subjects were seated and asked to read a description of the 
experiment and sign the research consent form. After signing the consent form, 
we administered each participant the Beck Depression Inventory, the Inventory to 
Diagnose Depression, and the Visual Analog Scale (VAS). The VAS offers a 
subjective measure of current mood according to how sad participants indicate 
that they feel at the moment. Each participant was given the VAS upon arrival to 
the study and again after the mood induction in order to assess a subjective level 
of mood.    
Following filling out these forms, participants were given an introduction to the 
sentence reading task, with the directions for the task displayed on the screen as 
 62 
the experimenter read the instructions aloud. As sentences words appeared, 
participants were asked to use their right hand to advance to the next word by 
pressing the spacebar. Oral instructions were given aloud to use the left hand to 
make their judgment of semantic plausibility for each statement by pressing 1, for 
?yes? this is a plausible statement, or 2, for ?no? this statement is implausible or 
doesn?t make sense. Further explanation by the experimenter indicated that a 
period will reveal the sentence final word, followed by a prompt the participant to 
make their plausibility judgment (signaled by ???).   
 Following the first experimental block of the reading task, the first 
memory task was administered and the participant was left to complete the task 
alone. Then, participants listened to instructions given by the experimenter about 
the mood induction procedure. The experimenter mentioned that the experiment is 
completely confidential and that the participant was free to leave at any time with 
full participation credit. Following these oral instructions for the mood induction, 
further instruction were given by a narrator on a recording and an 8 minute 
musical score was played to the participant via headphones. During the mood 
induction portion of the experiment, the participant was left in the room alone to 
encourage a more intimate setting. Once the recording ended, the experimenter 
asked participants to write a brief description (1 or 2 sentences maximum) of the 
sad moment they were thinking about while listening to the musical score. This 
was followed by the administration of two questionnaires assessing current mood 
state, the second VAS and the Multiple Affect Adjective Checklist Depression 
Scale (MAACL-D) (Zukerman & Lubin, 1965), which provided an additional 
 63 
self-report measure of current mood as participants mark items on a list of 
adjectives that refer to possible mood states. The MAACL-D was only 
administered while in the negative mood. 
 For the second half of the experiment, a second practice block was given 
before the participant performed the second experimental block of the reading 
task with a new set of sentences followed the second corresponding memory task. 
After the memory task, the experimenter debriefed the participant and he or she 
was allowed to leave. On average, the entire experiment took about 50 minutes to 
complete. 
 The two experimental blocks of the reading task were separated by the 
mood induction procedure delivered via headphones using Windows Media 
Player software. For the induction of negative mood, participants were asked to 
consider a sad moment in their life while listening to the musical score, entitled 
Prokokiev?s ?Russia under the Mongolian yoke.? This form of mood induction 
have been found to successfully elicit a transient negative mood as assessed using 
self-report measures such as the VAS (Teasdale & Taylor, 1981; Clark & 
Teasdale, 1985; Gemar et al., 2001; Richell & Anderson, 2004). Therefore, the 
second within-subjects independent variable was current mood state, of which the 
two levels were neutral (before the mood induction) and negative (after the mood 
induction). Current mood state was rated using measures of self-report that 
included VAS (before and after the mood induction) and Multiple Affect 
Adjective Check List Depression Scale (after the mood induction). 
 64 
 According to the VAS, the mood induction was considered successful by 
the participants, F(1, 47) = 46.37, p < .001. Scores for the VAS in the neutral 
mood (M = 12.18, SD = 13.08) were significantly smaller than the VAS scores in 
the negative mood (M = 26.38, SD = 17.13), reflecting increased negative affect 
while in the negative mood state. However, mean scores for the Multiple Affect 
Adjective Check List Depression Scale were not consistent with the VAS. 
According to this self-report measure, participants rated their mood as moderately 
positive (M = 3.66, SD = 18.33). These two self-report measures suggest that 
participants felt more sadness after the mood induction procedure when compared 
to scores recorded before the mood induction (VAS), but that participants still 
considered themselves in a positive mood (MAACL-D). 
 
Results ? Reading Task 
 
Reaction Time (RT) 
 
 A main effect of mood did not reach statistical significance, F(1, 78) = 
.406, p = .53.  While in a neutral mood, participants responded to the plausibility 
probe (M = 656.51ms, SD = 531.33) as quickly as participants in the negative 
mood (M = 685.73ms, SD = 425.41). There was a significant main effect of 
sentence type, F(3, 78) = 7.16, p < .001. The results for RT in the four critical 
sentence types are presented in Table 4 [pg. 65].  
 
 
 
 
 
 
 
 65 
Table 4 
Reaction Time: Sentence Type 
_______________________________________________________________ 
                               Neutral Mood        Negative Mood       Across Mood 
_______________________________________________________________ 
       Condition                   MEAN                   MEAN           MEAN   
______________________(ms)____________(ms)________ (ms)__________ 
 
        Negative           585.87  (269.28)     700.17  (485.80)      643.02 (377.54)    
         Positive            699.14  (794.30)     722.63  (484.18)     710.89 (639.24)  
   Neutral Implaus     574.89  (290.90)     598.37  (334.18)     586.63 (312.54)    
     Neutral Plaus       766.13  (770.83)     721.75  (397.47)     743.94 (584.15) 
_______________________________________________________________ 
Table 4. Estimated marginal means presented in milliseconds (ms), with standard deviations in 
parentheses, for sentence type in the neutral mood, the negative mood, and the average across 
mood for sentence type. 
 
 Across sentence type, post-hoc comparisons with Bonferroni adjustments 
indicated that the critical valenced sentences of conditions 1 and 2 were not 
significantly different (p = .17). Participants reacted significantly faster to the 
neutral implausible self-statements of condition 3 than to conditions 2 and 4 (p < 
.05) and condition 3 was not statistically different than the negative self-
statements of condition 1 (p < .09). The negative sentences of condition 1 were 
marginally different from the neutral plausible sentences of condition 4 (p = .06). 
The reactions to positive sentence of condition 1 did not react differently from the 
neutral plausible sentences of condition 4 (p = 1). Participant reaction was 
significantly slower to the neutral plausible statements of condition 4 than to 
condition 3 (p < .05). 
 The interaction effect of mood by sentence type did not reach statistical 
significance, F(3, 78) = 1.15, p = .22. Though the interaction of mood by sentence 
type did not reach significance, we performed planned comparisons with least 
significant difference adjustments based on our a priori predictions regarding the 
 66 
influence of mood on sentence processing according to target valence. Planned 
comparisons revealed that participants responded more slowly to the plausibility 
probe in condition 1 while in the negative mood (p < .05). While in the negative 
mood, participants were slower to reject the self-statements with negative targets 
(M = 700.17, SD = 485.80) as compared to the neutral mood state (M = 585.87, 
SD = 269.28). A change in mood did not affect reaction time for any other 
sentence condition. For the results of the mood by sentence type interaction, see 
Figure 1 [below]. 
Reation Time: Mood X Sentence Type
400
450
500
550
600
650
700
750
800
negativeSRS positiveSRS neutralSRS neutralNSRS
RT
(m
s)
Neutral Mood Negative Mood
       
Figure 1. Reaction time results: The effect of mood by sentence type. 
 
 
 
 
Reading Time (READ) 
 
 There was a statistically significant main effect of mood, F(1, 78) = 10.70, 
p < .001. The estimated marginal means for this main effect indicate that all 
 67 
participants read the sentence final word faster while in a negative mood (M = 
880.97, SD = 423.28) as compared to reading time during the neutral mood state 
(M = 1001.37, SD = 491.21)(*see Table 5). An effect of sentence type did not 
reach significance, F(3, 78) = 1.65, p = .18. The reading time results for sentence 
type are presented in Table 5 [below]. 
             
Table 5 
Reading Time: Sentence Type 
_______________________________________________________________ 
                               Neutral Mood        Negative Mood      Across Mood 
_______________________________________________________________ 
        Condition                 MEAN                   MEAN                  MEAN   
_____________________(ms)_____________(ms)___________(ms)_______ 
 
         Negative          1014.66  (400.56)   939.35  (448.71)    977.01  (424.64) 
          Positive           1005.94  (455.74)   901.27  (481.80)    953.61  (468.77) 
     Neutral Implaus     969.98  (352.59)   896.16  (341.91)    933.07  (347.25)                                       
       Neutral Plaus     1014.89  (755.96)   787.09   (421.10)    901.00  (588.53) 
  *Across Condition  1001.37 (491.21)    880.97  (423.28) 
_______________________________________________________________   
Table 5. Estimated marginal means presented in milliseconds (ms), with standard deviations in 
parentheses, for sentence type in the neutral mood, the negative mood, the average across mood 
for a main effect of sentence type, and the average across sentence type for a main effect of mood. 
 
  
 The interaction of mood by sentence condition did not reach statistical 
significance, F(3, 78) = 2.338, p = .074. Though the interaction of mood by 
sentence condition did not show significance, planned comparisons with least 
significance difference adjustments indicated that sentence target conditions 2 and 
4 were read differently than the targets in conditions 2 and 3. While in the 
negative mood, the positive targets of condition 2 (p < .05) and the neutral 
plausible targets of  condition 4 (p < .05) were read faster. Reading time for the 
negative targets of condition 2 and the neutral implausible targets of condition 3 
 68 
reached marginal significance (p < .06). Reading words faster in all sentence 
conditions while in a negative mood possibly indicates that these results were 
influenced by practice effects. The results for the mood by sentence type 
interaction are displayed in Figure 2 [below]. 
Reading Time: Mood X Sentence Type
400
500
600
700
800
900
1000
1100
Negative SRS Positive SRS Neutral SRS Neutral NSRS
RE
AD
 (m
s)
Neutral Mood Negative Mood  
         Figure 2. Reading time results: Means for the interaction of mood by sentence type. 
 
 
 
Response Choice (RESP) 
 
 Regarding the difference in response choice for the negative and positive 
self-statements, considering the data as a reflection of participants choosing a 
positive-evaluation implies that there was no difference between how participants 
endorsed the positive and negative self-statements. However, after converting 
response choice to the likelihood that participants accept sentences as plausible 
(i.e. say ?yes?), we find this data more meaningful. 
 69 
 A main effect of mood did not reach statistical significance, F(3, 78) = 
.20, p = .66. The estimated mean likelihood of how participants endorsed sentence 
plausibility was similar in a neutral mood (M = .90, SD = .01) to how participants 
chose while in a negative mood (M = .89, SD = .01). A main effect of sentence 
type reached significance, F(3, 78) = 17.047, p < .001. Regardless of mood, 
planned comparisons with Bonferroni adjustments indicated that participants were 
far more likely to endorse the positive self-statements over the negative self-
statements. Participants endorsed the negative (condition 1) and positive 
(condition 2) self-statements consistent with a positive self-evaluation similarly. 
How participants rejected the negative self-statements of condition 1 was not 
different from how they accepted the positive self-statements of condition 1 (p < 
.54).   
 Across sentence type, participants were least likely to endorse as plausible 
the neutral implausible self-statements of condition 3 (significantly different from 
conditions 1, 2, and 4, p < .001) and most likely to endorse the neutral plausible 
general-bias statements of condition 4 (significantly different from conditions 1, 
2, and 3, p < .05).  Participants were significantly more likely to endorse the 
negative self-statements over the neutral implausible self-statements (p < .05). 
Participants were significantly more likely to endorse as plausible the positive 
self-statements compared to the neutral implausible self-statements (p < .001).  
 The results for the main effect of sentence type are displayed in Table 6 as 
the percentage likelihood that participants endorsed each condition as plausible. 
[p. 70]. 
 70 
Table 6 
Response Choice 
______________________________________________________________ 
 
 Response      Negative             Positive            Neutral  SRS       Neutral SRS        
   Choice      Condition 1        Condition 2          Condition 3        Condition 4 
______________________________________________________________ 
 
     Yes         17% (26%)         85% (16%)            3% (8%)     92%(11%) 
_______________________________________________________________ 
Table 6. Percentage of likelihood, with standard deviations in parentheses, for responding 
?yes? in plausibility judgment task as compared across sentence condition.  
 
 The mood by sentence type interaction did not reach statistical 
significance, F(3, 78) = .44, p = .72. Planned comparisons with least significance 
difference adjustments did not reach significance and revealed that response 
choice did not significantly change with a change in mood.  
 
Discussion ? Reading Task 
 
 For the reading task, our a priori predictions were that participants would 
show faster reaction time on the plausibility judgment for emotion-related targets. 
We also predicted faster reading time for emotion-related target words. For 
response choice, we predicted that normal participants would be more likely to 
endorse positive self-statements as consistent with previous evidence showing a 
trait-specific bias in cognitive performance based on life experience (Atchley, 
Ilardi, & Enloe, 2003). We also predicted that participants would be more likely 
to endorse negative self-statements while in a negative mood, which would 
provide evidence for a mood-congruence effect on reading comprehension.  
 For the independent variables in the reading task, we predicted an 
interaction of mood by sentence type, providing evidence that reading 
 71 
comprehension and making plausibility judgments are affected by a negative 
mood state. The prediction of a mood by sentence type interaction mediated by 
target valence (Conditions 1 and 2) would provide evidence that emotional-related 
content affects reading comprehension while in a negative mood. A mood by 
sentence type interaction mediated by self-reference (Conditions 1, 2, and 3) 
would suggest that self-referent context affects reading comprehension while in a 
negative mood. 
 Regarding the main effect of mood, faster RT for implausible sentences is 
somewhat surprising in light of previous findings showing that reading 
implausible sentences is more difficult than plausible sentences (Speer & Clifton, 
1998). Making a plausibility judgment may have been easier for the implausible 
sentences of Condition 3 as we used implausible sentence target words that may 
have been obvious.  
 In support of our predictions, the RT data indicated that judging the 
plausibility of self-statements and other-referent statements is affected by 
negative mood. Negative mood increased the length of time participants spent 
making all plausibility judgments. More specifically, negative mood influenced 
the length of time participants spent making a decision about negative self-
statements. Though the RT results for a mood by valence interaction did not show 
significance, the planned comparison analysis suggests that participants were 
slower to reject the self-statements with negative targets while in a negative 
mood.   
 72 
 Regardless of mood state, the RESP analysis indicated that participants 
were more likely to endorse the positive self-statements over negative self-
statements. The direction of this finding supports our prediction based on previous 
evidence for trait-specific processing of lexical information (Atchley, Ilardi, & 
Enloe, 2003; Joorman & Gotlib, 2008). These never-depressed participants judged 
the positive self-statements similarly to the neutral general-bias statements. 
Conversely, our participants processed the negative sentences of condition 1 
similarly to the implausible sentences in condition 3. The response choice results 
are interesting in light of past research that has shown the opposite effect in 
depressed populations (Atchley, Ilardi, & Enloe, 2003). This evidence asserts 
aspects of sentence processing as trait-specific in never-depressed populations.
 Reaction time was shown to be a more reliable variable over reading time 
and response choice as an indicator of mood-congruent language processing. A 
comparison of the reaction and response choice data suggests that reaction time 
may be more sensitive than response choice for detecting the influence of current 
mood state on sentence processing. Furthermore, the delayed reaction time effect 
for negative self-statements occurs even though participants are spending less 
time overall reading the sentence final words while in a negative mood, as 
reflected by reading time being reduced for the critical sentence final words in all 
conditions after the mood induction. 
 Further evidence is needed in order to explain why there is a difference 
between how reaction time and reading time are affected by mood, especially as 
we are tempted to consider the possibility that reading sentences faster in the 
 73 
negative mood may be due to practice effects. Reducing the possibility of practice 
effects during the second experimental block may be necessary for research 
investigating how cognitive performance is changes after a mood induction 
procedure.  
 As we did not find mood-congruent effects for all of our dependent 
variables, our results for reaction time results may indicate that only specific 
aspects of language comprehension are affected by mood. In the case of reaction 
time, participants took longer to make the plausibility judgment in the negative 
mood. A recent study suggests that mood does not affect all aspects of cognition, 
but that mood may have specialized effects on the cognitive processing of 
emotional material, as in the case of memory performance for information that is 
congruent with the valence of mood state (Chepenick, Cornew, & Farah, 2007).  
 
 
Results ? Memory Task 
Negative Mood (MOOD) 
 
 A main effect of mood state was significant, F(1, 82) = 15.17, p < .001. 
Participants had better memory performance while in the neutral mood (M = .51, 
SD = .11) and worse memory while in the negative mood (M = .46, SD = .12).  
 
Target Word Valence (VAL) 
 
 A main effect of valence was statistically significant, F(2, 86) = 172.08, p 
< .001. Planned comparisons with least significant difference adjustments 
indicated that the most accurate recall was for positive target words and the 
comparison between the negative sentences and positive sentences showed 
 74 
marginal significance (p = .06). Negative targets were recalled more accurately 
than neutral targets (p < .001). Participants showed the least accurate recall for 
neutral targets (p < .001). The results for the analysis of valence are presented in 
Table 8 [below]. 
Table 8 
Valence 
_____________________________________________________ 
                                                Neutral           Negative       Across Mood 
_____________________________________________________ 
                          
              Target word          
       Valence (VAL)      MEAN             MEAN             MEAN 
_____________________________________________________ 
 
          Negative           .27 (.20)            .22 (.19)          .25 (.20) 
           Positive            .30 (.23)            .25 (.21)          .28 (.22) 
           Neutral             .03 (.07)            .02 (.07)          .03 (.07) 
     Across Valence      .51 (.11)            .46 (.12) 
________________________________________________________________ 
  Table 8. Results for Valence: Estimated marginal means, with standard 
  deviations in parentheses, in the neutral and negative mood and also across  
  mood. 
 
 The interaction of mood by valence did not reach statistical significance, 
F(1, 86) = .56, p < .57. Planned comparisons with least significant difference 
adjustments revealed that there were no significant differences among different 
valence categories that changed with mood. 
 
 
 Investigation of Self-Reference (SELF) 
 
 The main effect of self-reference was significant, F(1, 86) = 960.64, p < 
.001. Planned comparisons with least significant difference adjustments indicated 
that participants showed better recall for other-referent statements (M = .70, SE = 
 75 
.01) than for self-statements (M = .27, SE = .01), (p < .001). An interaction effect 
of mood by self-reference did not reach significance, F(1, 86) = .43, p = .51.  
 The 3-way interaction of mood by self-reference by valence did not reach 
statistical significance, F(2, 86) = .46, p = .633. Planned comparisons with least 
significant difference adjustments did not shown significance. We did find that 
the interaction of self-reference by valence reached significance, F(2, 86) = 55.06, 
p < .001. Within the self-referent sentences, post-hoc comparisons with 
Bonferroni adjustments indicated that both the negative and positive statements 
were significantly different from the neutral statements (p < .001). There was a 
marginal difference between the negative and positive self-statements (p < .07). 
 
Discussion ? Memory Task 
 
 The memory task was successful in showing that mood influenced recall 
for the critical final word of previously read sentences. We found that a negative 
mood decreased overall memory performance as we observed a decrease in recall 
for all sentence targets while in a negative mood. The decrease in recall 
performance may be due to negative mood; though this finding is not consistent 
with past research that has suggested that memory performance improves while in 
a negative mood (Kern, et al., 2005; Levine & Burgess, 1997).  Possibly the most 
parsimonious explanation for the decrease in memory performance is the fan 
effect (Anderson, 1974; Anderson & Reder, 1999; Moeser, 1979). The fan effect 
refers to interference among competing associations to a concept held in memory. 
Due to the limited amount of spreading activation that can occur in memory, more 
memory associated with one source makes it difficult to access any one 
 76 
association connected with the memory source (see also Anderson, 2005). For the 
current findings, the self-statements may be considered high-fan as all 
associations are connected to one source, the self (i.e. I, me, myself). The fan 
effect may have reduced recall while in the negative mood due to interference 
from similar sentence stems that appeared in the memory task performed while in 
the neutral mood. Furthermore, the fan effect could also explain better memory 
for the other-referent statements as these concepts would have only received one 
or two memory associations. For example, ?Lawyers can be shifty? and ?Lawyers 
can be pleated? would have two associates (i.e. shifty, pleated) connected to one 
concept (lawyers). 
 Another possibility contributing to poor memory for the self-statements in 
the negative mood could be interference produced while in the neutral mood as 
this may have resulted in a disruption in source monitoring (Johnson, Hashtroudi, 
& Lindsay, 1993). Source memory refers to our ability to remember details or 
feature of a memory, more importantly for the current data, when we acquired the 
information. Cook, Hicks, and Marsh (2007) have asserted that attention to 
valenced content can reduce source monitoring. Counterbalancing mood by 
testing two separate groups or testing recall for each mood state on separate days 
are important steps for future exploration of the current findings.  
 Another possible explanation for this inconsistency with past research may 
be due to the sentence final word targets in the current study being rated low in 
emotional arousal. Though this is not the most parsimonious explanation for a 
decrease in memory, this is an important difference between the current study and 
 77 
previous research designs. Regarding decreased memory performance, target 
words with higher levels of arousal may be necessary for improved memory 
performance. The low arousal rating of our emotional targets may be why we did 
not see a significant effect of mood-congruent memory processing. For future 
research, it will be necessary to include emotional items containing high arousal 
ratings in order to more precisely identify how level of arousal can affect recall.  
 The method of mood induction utilized in the current study (i.e. sadness) 
may be regarded as low in arousal, possibly further explaining inconsistent 
findings with past research. Negative mood can vary in level of arousal, such that 
sadness is regarded as low in arousal while anger or frustration may be considered 
a high arousal, negative mood state. Previous research has proposed sadness and 
anger as separate mood categories (Lerner & Keltner, 2001; Rusting, 1998) 
 Our final conclusion based on the finding of decreased memory 
performance while in a negative mood state is that, given participants showed 
faster reading time scores while in the negative mood state (for discussion, see pg. 
70), participants may not have efficiently encoded these words into short-term 
memory. Failure to read the sentence final words long enough for sufficient 
encoding into memory to take place likely contributed to an overall decrease in 
recall performance while in the negative mood state. This conclusion is further 
supported by the data suggesting that participants read the implausible sentence 
final words of Condition 3 as fast as sentences containing plausible sentence final 
words while in the negative mood state. 
 78 
 Considering the valence of the critical target word, we found an overall 
memory performance bias to recall positive targets among these non-depressed 
participants and this happened regardless of mood state. This finding contributes 
to trait-specific models of emotion processing supported by research showing a 
cognitive processing advantage for positive items in non-depressed populations 
(Atchley, Ilardi, & Enloe, 2003).  
 We found that participants showed greater recall for emotionally-valent 
targets over neutral targets and this is consistent with the findings of Kensinger & 
Corkin (2003). However, it was also likely that the nature of our neutral self-
referent sentences contributed to this effect. In order to produce neutral self-
referent sentences, we chose to use implausible targets due to the difficulty in 
designing unambiguously neutral self-referent statements that remain neutral 
across our random sample. It is possible that the implausibility of the neutral self-
statements contributed to the reduced memory performance that we are seeing for 
these stimuli. 
 The investigation of self-reference and recall indicated that self-statements 
were processed differently than the other-referent statements. More specifically, 
self-referent statements showed less recall accuracy than other-referents and this 
does not support our initial hypothesis based on evidence that dysphoric mood 
influences the processing of self-referent material by focusing attention on self-
referent content (Ingram, 1990; Ingram & Wisnicki, 1999). Again, the fan effect 
(Anderson, 1974; Anderson & Reder, 1999; Moeser, 1979) has implications for 
these findings due to the redundant nature of the self-referent sentence stems 
 79 
being associated with only one concept, the self. Many of these items contained a 
similar stem and interference may have occurred with a task to remember the 
sentence final word among several similarly constructed sentence stems.  
 Possibly contributing to this explanation based on the fan effect, Anderson 
and Shimamura (2005) suggests that negative mood may result in a decrease in 
the memory for the context of events and it could be possible that our data 
indicate a decrease in context-specific memory as participants in this study 
showed poor recall for items that required memory for the sentence stem in order 
to more accurately remember the sentence final words.  
 
Conclusions 
 
 To summarize, the goals of this research were to investigate the effect of 
negative mood on cognitive performance in the domains of language 
comprehension and memory. Before and after a mood induction, participants 
made plausibility judgments about sentences containing emotional targets. We 
measured aspects of reading comprehension and a recall task allowed for the 
assessment of memory performance when emotional stimuli were present. The 
mood induction was designed to investigate how performance changes with a 
negative mood compared a neutral mood state.   
 Past research has found that words rated high in arousal can generate a 
valence effect on recall (Kern et al., 2003) and the current study indicates that 
emotionally-relevant words that were rated low in arousal can also be found to 
show a significant effect on reading negative words and recall performance. The 
current design did not compare the effects of high versus low arousal, but the 
 80 
current findings indicate that the semantic features related to valence alone can 
influence reading comprehension without drawing heavily on cognitive systems 
activated by arousal. An independent variable that addresses high versus low 
arousal would provide more conclusive data relevant to how arousal and valence 
affect recall.  
 Considering our predictions for the memory task, a mood congruency 
effect did not occur. Previous researchers have found enhanced retrieval for 
information that is consistent with the valence of current mood state (Chepenik, 
Cornew, & Farah, 2007). However, we found that memory performance goes 
down generally in a negative mood state regardless of the valence of the material 
that is to be remembered. Our mood induction technique may not have been 
sufficient to significantly change mood or may have been too transient to have a 
lasting effect on cognitive processing. Possible differences in the mood induction 
procedure are a possible explanation for not replicating previous findings. It will 
be necessary for future researchers concerned with how reading comprehension is 
affected by mood to implement a mood induction technique that is high in arousal 
in order to delineate sadness and anger as distinct categories of negative mood. 
 In addition to the possible difference of arousal level in the mood 
induction technique, how we recall information presented at the sentential level is 
another possible explanation for this inconsistency with previous findings as this 
format may have increased cognitive load (Hale, 2003; Baddeley, 1988). 
Recalling information presented at the sentential level increased the amount of 
information to being held in working memory, leaving less cognitive resources 
 81 
available to recall the sentence final words. Increasing cognitive load has been 
shown to impair memory encoding (Fletcher, Shallice, & Dolan, 1998). Further 
evidence is needed to establish how sentence comprehension is affected by trait-
like biases in emotion processing. 
 The current study contributes to understanding how emotional words 
influence language comprehension. The majority of the effects found in the 
current study suggest that how we read emotional sentences and later recall that 
information is trait-specific. Our data provide an example of how mood state can 
affect language processing, but more research is needed to establish what specific 
aspects of language and memory processing are affected by mood state. We found 
that mood changes performance only in particular aspects of cognitive processing, 
as in the case of how long we it takes to judge plausibility when reading negative 
information in self-referent statements and our ability to recall critical sentence 
information.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 82 
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