Creativity through the eyes Arousal and the prediction of creative task performance by Locus

35 Pages·2017·1.26 MB·English

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Creativity through the eyes
Arousal and the prediction of creative task performance by Locus Coeruleus-norepinephrine
modes.

Matthijs Dekker
U1262091 / 991987

Master thesis
Communication- and Information Sciences
Corporate communication and digital media

Faculty Humanities
Tilburg University

Supervisor: dr. K.A. de Rooij
Second reader: H.K. Schraffenberger BEng MsC

January, 2017
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Abstract
In order to develop creative ideas, which are original as well as effective, several cognitive
processes are required involving divergent and convergent thinking. Previous research
suggested that creative task performance is influenced the release of noradrenaline, causing
arousal, in the Locus Coeruleus-norepinephrine system (LC-NE). This LC-NE system
mediates the changes between exploitation and exploratory control states. Previous studies
suggested that activity in the LC-NE system is indicated by pupil diameter. Tonic pupil sizes
are associated with an exploratory control state, whereas phasic pupil are associated with an
exploitative control state. This study measured the pupil diameter of participants while they
performed a creative task. Different phases in the experiment are characterized by divergent
and convergent thinking. It is examined whether tonic and phasic pupil sizes can predict the
creativity of generated ideas during divergent and convergent thinking. It was found that (i)
phasic pupil sizes are linear and quadratic predictors of effectiveness during divergent
thinking; (ii) tonic pupil sizes are linear predictors of originality during divergent thinking.
These findings suggest that creativity can be predicted during divergent thinking in a creative
process.
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Creativity through the eyes
Creativity among individuals and cultures can lead to happier, fuller and healthier lives
(Richards, 2010). It benefits the adaption to an unpredictable future, and supports shaping this
future to be beneficial. For example, creativity is highly important in today’s world with
constant changes and hypercompetitive markets (Kaufman & Sternberg, 2010; Harvey &
Novicevic, 2002). Creative task performance strengthens innovative performance, problem
solving capabilities and is required to avoid failure (Kotler, Armstrong, Saunders, & Wong,
2014; Proctor, 1991; Damle, 2015). Currently there is a limited understanding of the factors
that enable creative thought. Therefore, this study aims to provide an understanding about
factors that predict creative task performance during the creative process.
In order to be creative, both originality and effectiveness are required. Namely,
something which is original can be useless if it is not effective (Runco & Jaeger, 2012; Stein,
1953). Creative task performance, the degree to which individuals develop ideas that are both
original and effective, involves cognitive processes interacting in a dynamic fashion (Isaksen,
Dorval, & Treffinger, 2011; Mumford, Madeiros, & Partlow, 2012). These processes involve
variation in divergent and convergent thinking, organized in the creative problem solving
framework by Isaksen et al. (2011) and Mumford et al. (2012). Divergent thinking generates
ideas by combining disparate forms of information in new ways, while convergent thinking
generates one single solution to a problem (Addis, Pan, Musicaro, & Schacter, 2016).
Divergent thinking leads to original ideas, but in order to become effective, convergent
thinking is necessary to analyze and evaluate these original ideas (Baas & van der Maas,
2015).
Creative task performance during divergent and convergent thinking is influenced by
arousal. Arousal can be defined as vigilance and alertness while being awake (Carter, de
Lecea, & Adamantidis, 2013). An inverted U-shape relationship between arousal and creative
task performance reveals that very low or extremely high levels of arousal prohibit people
from efficient creative activities, whereas moderate levels of arousal enhance creativity (Kim,
2006; de Dreu, Baas, & Nijstad, 2008; Seo, Bartunek, & Barrett, 2010). Arousal is caused by
the release of noradrenaline and dopamine in the cortical circuitry due to a link between
working memory function and the Locus Coeruleus-norepinephrine system (LC-NE)
(Dreisbach & Goschke, 2004). During periods of extremely high arousal, attentional selection
becomes so restricted that particular cues cannot be processed, while periods of very low
arousal lead to drowsiness and inattention (Gilzenrat, Nieuwenhuis, Jepma, & Cohen, 2010).
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Instead, focusing on the LC-NE modes during different control states can identify the
multifaceted effects of arousal on creative performance (Gilzenrat et al., 2010).
Recent studies found evidence that LC-NE activity mediates changes between
exploitation and exploratory control states (Jepma & Nieuwenhuis, 2011; Gilzenrat et al.,
2010; Hayes & Petrov, 2016). An exploitation control state is accompanied by enhanced
performance and focus on a current task, whereas an exploratory control state enhances
engagement on non-task related information. The adaptive gain theory implies that an
exploitation state is accompanied by the phasic mode of the LC-NE, whereas an exploratory
control state is accompanied by the tonic mode of the LC-NE (Jepma & Nieuwenhuis, 2011;
Gilzenrat et al., 2010; Hayes & Petrov, 2016; Aston-Jones & Cohen, 2005). A tonic LC-NE
mode is characterized by an increased baseline pupil diameter and enhanced engagement on
non-task related information (i.e. exploration). Conversely, a phasic LC-NE mode is
characterized by a decreased baseline pupil diameter and enhanced engagement in the current
task (i.e. exploitation). Despite these findings, no studies examined whether creative
performance could be predicted based on LC-NE modes via pupil diameters. It could be
assumed that phasic and tonic LC-NE modes can provide a new perspective in the role of
arousal during creative thought.
An exploratory control state, predicted by a tonic LC-NE mode, contributes to
divergent thinking by disengaging from the current task and increasing cognitive flexibility
(Jepma & Nieuwenhuis, 2008). Evaluating and planning original ideas is a convergent process
in which individuals convert several original ideas into one effective plan. An exploitation
control state, predicted by a phasic LC-NE mode, contributes to convergent thinking by
focusing and increasing performance on the current task. Preliminary research showed that
reduced activity in the LC-NE predicted divergent thinking, whereas increased activity in the
LC-NE predicted convergent thinking (Heilman, 2016; Heilman, Nadeau, & Beversdorf,
2003). However, to the knowledge of this author no previous studies have shown whether LC-
NE modes, monitored by pupil diameters can predict creative task performance. It is assumed
that changes in the LC-NE modes predict the creative task performance of an individual.
Consequently, the following research question underlines this study:

“Do phasic and tonic LC-NE modes predict creative task performance during
divergent and convergent phases in the creative process in different ways?”
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This research is deemed scientifically relevant for the following reasons. First, this
research seeks to fill the gap of knowledge between the synergy of the LC-NE and creative
task performance. To date, there has been research on examining and identifying individuals’
creative task performance (Mumford et al., 2012; Kuncel, Hezlett, & Ones, 2004; Baas,
Roskes, Sligte, Nijstad, & de Dreu, 2013). It is revealed that LC-NE activity is related to the
diameter of an individual’s pupils. None of these studies examined the prediction of tonic and
phasic LC-NE modes on divergent and convergent phases in the creative process via pupil
diameters. This study aims at providing evidence for the involvement of LC-NE modes on
creative task performance as well as introducing an additional measure for creative task
performance. Second, this study is conducted within a context of high external validity. As the
contribution to society is an important aspect of creativity, this study is based on a realistic
corporate issue. Therefore, the practical effectiveness of the solutions is addressed in this
study.
This research also has societal relevance as creative task performance is highly
required in hypercompetitive markets (Kaufman & Sternberg, 2010; Harvey and Novicevic,
2002). Therefore, it is important to understand creativity and how it can be strengthened and
assessed. By understanding the link between LC-NE activity and creativity, people can be
trained to utilize creative task performance in order to increase competitiveness and become
more valuable for organizations. In addition, organizations are already assessing potential
candidates on their creative task performance (Oldham & Cummings, 1996). This study aims
to assess creativity more effectively and can therefore be useful to organizations in order to
find employees who can contribute to the competitiveness, problem solving capabilities and
growth (Kotler et al., 2009).
This thesis is structured in the following way. The theoretical framework provides an
in-depth exploration of the key concepts ‘creativity’, and the ‘creative process’. Furthermore,
literature regarding ‘exploration and exploitation control states’ and the relation with ‘phasic
and tonic modes’ will be explored and applied. The third chapter explains the method for this
research in terms of chosen samples, experimental design, materials and procedure. The
fourth chapter will statistically present the results and subsequently the hypotheses will be
confirmed or rejected. The fifth chapter concludes the findings and answers the research
question. Furthermore, it discusses the theoretical and practical implications of this research
and provides suggestions for further research.
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1 Theoretical framework
1.1 Creativity
In order to define creativity, a bipartite definition is required. The first part of the definition
involves originality referring to the uncommonness and innovativeness of an idea (Baas &
van der Maas, 2008). An uncommon and innovative idea can be based on existing knowledge
and information, but the final idea should contain new elements compared to a previous idea
(Stein, 1953). However, an original idea can be useless, as there is the possibility that nobody
ever introduced it because it did not contribute to society. Therefore, a second part is included
in the definition.
Balkin (1990) stresses that the contribution to society is what differentiates creativity
from merely originality. In order to contribute, a creative idea should be practically useful, fit
the context and be appropriate (Runco & Jaeger, 2012). Stein (1953) highlights the
importance of time and people in terms of society. In today’s world with constant changes and
hypercompetitive markets, yesterday’s creative ideas can be ineffective today (Harvey &
Novicevic, 2002; Kaufman & Sternberg, 2010). Furthermore, these ideas should be
considered useful or satisfying by a group of people and the benefits should outweigh the
costs (Balkin, 1990; Rubenson & Runco, 1992; Stein, 1953). This contribution to society is
referred to as effectiveness, which leaves the bipartite definition as a combination of
originality and effectiveness (Montag, Maertz, & Baer, 2012; Runco & Jaeger, 2012).

1.2 Creative process
The creative process is strengthened by a combination of divergent and convergent thinking
(Jones & Estes, 2015). Both types of thinking contribute differently to the process of creative
thought. Whereas divergent thinking focuses on generating original ideas by combining
disparate forms of information in new ways, convergent thinking narrows several original
ideas into one optimal creative idea (Addis et al., 2016; Jones & Estes, 2015). This entire
process of creative thought contains several phases which are each related to divergent and
convergent thinking.
The framework showing the several stages within the process of creative problem solving
are displayed in Figure 1 (Isaksen et al., 2011, p. 31) created a framework showing the several
stages within the process of creative problem solving (Figure 1).
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Figure 1. Creative problem solving framework. Reprinted from Creative approaches to problem solving: A framework for
innovation and change (p. 31), by S.G. Isaksen, K.B. Dorval, and D.J. Treffinger, 2011, London, England: SAGE
publications. Copyright 2011 by SAGE publications, Inc.
This framework is based on three process components and one management
component, each consisting of different phases which are related to divergent or convergent
thinking (Isaksen et al., 2011). The first component, “understanding the challenge”, involves
the preparation and stating of the problem. The phases included in this component are
constructing opportunities, exploring data, and framing problems. These phases assist in
developing a clear definition of the problem. The second component, “generating ideas”,
involves generating many original ideas to solve a problem. Only one phase is included in this
component with a similar name. The third component, “preparing for action”, involves the
convergence of the many original ideas into an effective and creative idea which can solve the
problem. This component consists of the phases developing solutions and building
acceptance. Figure 2 gives an overview of the components addressed in this study, belonging
to the divergent and convergent phases. The width of the graph shows that the divergent
phases lead to a high number of original ideas, whereas the convergent phases lead to a small
number of creative ideas.
The “planning your approach” component is referred to as a management component
which involves keeping track of thinking processes during the creative problem solving
process. Furthermore, choices about tools and locations are involved in this component.
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Figure 2. Divergent to convergent thinking

The framework by Isaksen et al. (2011) is constructed in a dynamic fashion which allows
for cycling back to previous phases in cases of failure and dissatisfaction. For example, when
the original ideas generated with divergent thinking prove insufficient to construct a creative
idea, more information and knowledge can be gathered. This dynamic process enhances the
creativity of ideas by providing a greater range of options (Connelly et al., 2000; Mumford,
Baughman, Threlfall, Supinski and Costanza, 1996). The number of times cycling back can
differ per individual, as the strength of convergent and divergent thinking differs per person.
An individual’s ability to perform a creative task depends the behavior and cognitive
skills during the execution of the different phases of the creative process. Cognitive
flexibility, extraversion, openness to new experiences and the ability to disengage from a
current task predict an individual’s divergent thinking abilities (Baas et al., 2008; de Dreu,
Nijstad, Baas, Wolsink, & Roskes, 2012; Kuncel et al., 2004). In contrast, self-confidence,
planning, perseverance and the ability to focus on a current task predict an individual’s
convergent thinking abilities (Balkin, 1990; de Dreu et al., 2012; Kuncel et al., 2004). Balkin
(1990) stresses that the coherence of these skills and characteristics determine the strength of
creative task performance. For example, intelligence is necessary in order be creative,
however, solely intelligence does not make an individual creative (Karwowski et al., 2016).
Creative people are able at making connections were these connections did not exist
previously (Balkin, 1990). In short, each phase requires certain cognitive skills and behavior
in order to perform effectively. The combination of these phases, associated cognitive skills,
and personal characteristics contribute to the emergence of creative ideas.

1.3 Arousal
Some of the cognitive skills required in a creative process (e.g. working memory capacity,
comprehension, planning) are associated with arousal (de Dreu et al., 2008; Kim, 2006; Seo et
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al., 2010). Arousal is defined as the degree of vigilance and alertness during periods of
wakefulness (Carter et al., 2013). Wakefulness is referred to as a conscious state in which
individuals can perceive and interact with their environment. The cue utilization hypothesis
states that increased levels of arousal lead to enhanced selection and processing task-relevant
information. For example, Martindale and Greenough (1973) found a significant relation
between high arousal and creative performance, whereas low and medium levels of arousal
showed non-significant results. This study was conducted via a Remote Associates Test
(RAT) which focuses on convergent thinking abilities. Similar findings were retrieved via an
Alternate Uses Task (AUT) which focuses on divergent thinking abilities (Dreu et al., 2008).
The effect of arousal on these cognitive processes can be explained by the release of
noradrenaline and dopamine in the cortical circuitry, and in particular a connection between
the working memory function and the Locus Coeruleus-Norepinephrine (LC-NE) (Dreisbach
& Goschke, 2004). The LC-NE system controls the cognitive processes moderating the level
of attention and behavioral performance of an individual on a current task (Sara, 2009).
Furthermore, it is the only source of norepinephrine, a neurotransmitter modulating arousal, in
the cortex (Heilman, 2016; Howells, Stein, & Russell, 2012)
Seo et al. (2010) found that increased levels of arousal enhance focus and attention on
a current task. This is partially supported by Yerkes and Dodson (1908) who revealed an
inverted U-shape relationship concerning arousal and creative task performance (Figure 3).
The study by de Dreu et al. (2008) supported this relationship by conducting a brainstorming
experiment for product improvement. During this experiment, participants with very low or
extremely high arousal performed less creative behavior. These extreme levels of arousal shut
down cognitive systems which are required to perform creative behavior. For example,
extremely low levels of arousal lead to drowsiness and inattention to a task, which hinders
optimal convergent thinking. Extremely high levels of arousal lead to highly restricted
attentional selection and a rigidity of focus, which hinders optimal divergent thinking
(Gilzenrat et al., 2010). Participants with a moderate level of arousal performed the most
enhanced levels of creative behavior due to an active working memory capacity and
functioning of the LC-NE (de Dreu et al., 2008).
Focusing solely on low, intermediate, and high levels of arousal in the LC-NE could
restrict the multifaceted effect of arousal in the creative process. The cue utilization
hypothesis states that increased levels of arousal enhance convergent thinking by restricting
selection impact performance by restricting selection of extant information. However, this
restricted selection could hinder divergent thinking. Therefore, in order to investigate the
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multifaceted effect of arousal, this study focuses on different LC-NE modes and their effect
on exploratory and exploitative states of mind.

Figure 3. Inverted U-curve of arousal

1.4 Exploration and exploitation
The previously described creative problem solving framework comprises of both divergent
and convergent thinking, in which extant knowledge and information are first explored and
subsequently exploited to generate creative ideas (Isaksen et al., 2011). The divergent
thinking phases are associated with an exploratory state of mind, involving certain
characteristics described in section 2.2. Subsequent convergent thinking phases are associated
with an exploitative state of mind, involving the characteristics described in section 2.2. The
interaction between these states of mind contribute to the production of creative ideas.
The interaction between the states of mind affect the creative task performance of an
individual. The ambidexterity hypothesis states that an individuals’ ability to switch
appropriately between exploration and exploitation, determines the effectiveness of cognitive
processes which enhance creative task performance (Gupta, Smith, & Shalley, 2006;
Laureiro-Martínez et al., 2015). Research by Laureiro-Martínez et al. (2015) showed that the
LC-NE is more activated during exploring compared to exploiting. This was measured by
conducting a four-armed bandit test in which participants chose between slot machines to
receive the highest pay-out. Participants explored different slot machines or exploited only
one. Whereas the total number of exploratory- and exploitative choices did not predict the
most advanced decision-making performance, the switching from between the states of mind
did. Especially switching from exploration to exploitation predicted the most effective