Available online at www.sciencedirect.com
Biological Psychology 77 (2008) 353–358
www.elsevier.com/locate/biopsycho
Anxiety impairs decision-making: Psychophysiological evidence
from an Iowa Gambling Task
Andrei C. Miu a,*, Renata M. Heilman a, Daniel Houser b,*
a
Program of Cognitive Neuroscience, Department of Psychology, Babes-Bolyai University, 37 Republicii, Cluj-Napoca, CJ 400015, Romania
b
Interdisciplinary Center for Economic Science and Department of Economics, George Mason University,
4400 University Drive, MSN 1B2, Fairfax, VA 22030, USA
Received 23 December 2006; accepted 30 November 2007
Available online 10 January 2008
Abstract
Using the Iowa Gambling Task (IGT) and psychophysiological correlates of emotional responses (i.e., heart rate and skin conductance), we
investigate the effects of trait anxiety (TA) on decision-making. We find that high TA is associated with both impaired decision-making and
increased anticipatory physiological (somatic) responses prior to advantageous trials. For both high and low TA, skin conductance responses
preceding advantageous trials predict decisions. At the same time, somatic responses to choice outcomes reflect differences between high and low
TA sensitivities to punishments and rewards. The pattern of impaired decision-making and increased somatic markers that we find in high TA may
have important implications for neuropsychological decision theory. In particular, it offers an example of defective modulation of somatic signals,
coupled with disrupted discrimination of advantageous and disadvantageous choices.
# 2008 Elsevier B.V. All rights reserved.
Keywords: Anxiety; Emotion and decision-making; Somatic markers
1. Introduction
It is by now widely accepted that emotion plays an adaptive
role in human decision-making (for review see Bechara et al.,
2000; Dunn et al., 2006). Discovering the physiological
correlates and neurobiological underpinnings of emotion’s
influence on decision, as well as the role individual differences
might play in this regard, is the ambitious goal of a rapidly
expanding literature (e.g., Kurzban and Houser, 2001; McCabe
et al., 2001; Decety et al., 2004). Here we contribute to this
literature by reporting data from experiments using the Iowa
Gambling Task (IGT) that provide novel evidence on joint
relationships among trait anxiety (TA), somatic signaling and
decision-making.
IGT is a decision-making task simulating uncertainty of
premises and outcomes, as well as reward and punishment in
controlled laboratory conditions (Bechara et al., 1994). IGT has
proven extremely valuable in studies of the effects of
* Corresponding authors.
E-mail addresses: [email protected] (A.C. Miu),
[email protected] (D. Houser).
0301-0511/$ – see front matter # 2008 Elsevier B.V. All rights reserved.
doi:10.1016/j.biopsycho.2007.11.010
personality in decision-making. For instance, some timely
studies that approached the influence of personality on
decision-making found that sensation-seeking positively
correlated with the frequency of advantageous choices (Reavis
and Overman, 2001), whereas negative emotionality negatively
correlated with the frequency of choices from high-punishment
decks (Peters and Slovic, 2000). These studies suggested
personality differences, particularly those associated with
emotional reactivity such as TA, might provide a partial
explanation for the high variance of IGT performance in
healthy volunteers (Bechara and Damasio, 2005).
TA reflects individual differences in sensitivity to threat
(Spielberger, 1966; Endler and Kocovski, 2001; Gray and
McNaughton, 2000/2003, pp. 338). These individual differences have been functionally translated into attentional,
memory, and interpretative biases towards the preferential
processing of aversive stimuli (e.g., Calvo et al., 2003). The
biological basis of this personality dimension has been
extensively studied from the genetic (Lau et al., 2006; Lesch
et al., 1996; Buckholtz et al., in press) to the neural systems
level (Grachev and Apkarian, 2000; Yamasue et al., 2008;
Paulus et al., 2004). These studies indicated that TA is
considerably supported by additive genetic factors, some of
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A.C. Miu et al. / Biological Psychology 77 (2008) 353–358
which are already known (e.g., variants of the serotonin
transporter and monoamine oxidase A genes), and it is
associated with morphological, neurochemical and functional
brain differences in neural networks (e.g., prefrontal cortex,
amygdala) that were previously related to emotion.
The relationship between TA and decision-making has
received attention only very recently. Using self-report
measures of risk perception and a decision-making task
explicitly involving risk evaluation, several studies found that
TA was associated with increased avoidance of risky decision
and pessimistic risk appraisals (Maner et al., 2007; Maner and
Schmidt, 2006; Mitte, 2007). However, we are aware of no
study investigating effects of TA on decision-making using
complex tasks such as IGT, which is thought to involve covert
emotional signals that might adaptively guide decision-making
even before explicit knowledge about the task is available (see
Bechara et al., 1997; and Maia and McClelland, 2004).
Considering that TA has been associated with preattentional
cognitive biases (for review see Mathews and Mackintosh,
1998), investigating the effect of TA on decisions involving
emotional cues that preattentionally guide performance would
be an important empirical contribution.
The present study investigates effects of TA on IGT
performance, and obtains measures on the physiological
correlates of somatic signals that are expected to inform
decision-making (Bechara et al., 1997; Crone et al., 2004). We
design our study to provide evidence on two key related
hypotheses. First, we hypothesize that high TA participants will
show lower IGT performance compared to low TA participants.
Second, we hypothesize that high TA participants will display this
lower performance concurrently with relatively high task-related
somatic signalling. We discuss below that these two hypotheses,
both of which our data support, are not necessarily inconsistent
with the somatic marker hypothesis (Bechara et al., 2000). The
reason is that the somatic marker hypothesis admits, under certain
conditions, uncoupling of somatic signals and ultimate decisions.
2. Materials and methods
2.1. Participants
Out of an initial cohort of 112 Babes-Bolyai undergraduate students who
agreed to be screened for this study, we selected 11 women and 9 men (mean
age standard deviation [S.D.]: 19.5 1 years) based on their >1 S.D. above or
below average scores on the trait portion of the Romanian version of Spielberger’s
State-Trait Anxiety Inventory (STAI-X) (Spielberger, 1983; Pitariu et al., 1987),
and the anxiety/neuroticism scale of the Romanian version of Zuckerman–
Kuhlman Personality Inventory (Zuckerman et al., 1993; Opre et al., 2003).
The scores on these scales are reported in Table 1. The low TA group included 5
women and 3 men, and the high TA group included 6 women and 2 men, with no
significant socio-demographic (e.g., education, ethnic origin, native language)
differences between these groups. All the participants gave their informed consent
to participate to this experiment. The experimental procedures complied with the
recommendations of the Declaration of Helsinki and the national and institutional
ethical guidelines for experiments with human participants.
2.2. Behavioral task
We used the standardized manual version of IGT, as described in Bechara
et al. (1994). Briefly, participants were presented face downward four decks of
cards labelled A, B, C, and D, with 40 cards in each deck. The participants
received a loan of 2000 Romanian New Currency (RON) facsimile at the
beginning of the game and they were instructed to play the game so as to lose the
least amount of money and win the most. The total number of trials was set at
100 card selections, without the participant being aware of how many cards he
or she was going to pick. Turning each card from any deck carried an immediate
reward (100 RON for A and B, and 50 RON for C and D). However, A and B
were disadvantageous decks because every 10 cards from decks A and B over
the course of trials not only gain 1000 RON but also carried several unexpected
penalties of 150–350 RON (A) or a single large penalty (B) that raised the total
loss to 1250 RON. C and D were advantageous decks because they gained 500
RON over 10 card selections and carried a total loss of 250 RON either
cumulated from several cards associated with 25–75 RON penalties (C), or
from only one 250 RON penalty card. Thus A and B were equivalent in terms of
total loss over trials, and so were C and D in terms of total gain over trials. The
difference was that while A and C had higher frequency but lower magnitude
punishments, B and D had lower frequency but higher magnitude punishments.
Playing mostly from the disadvantageous decks led to an overall loss, while
playing mostly from the advantageous decks led to an overall gain. The
performance of the participant was indexed by the CD–AB score.
2.3. Electrophysiological recordings
During IGT, we recorded electrocardiography (ECG) and skin conductance
(SCR) using a Biopac MP150 system (Biopac Systems, CA, USA). ECG was
recorded with a sample rate of 500 Hz, from three EL258RT Ag-AgCl electrodes filled with isotonic GEL101 gel, positioned in a modified lead-2 placement.
SCRs were recorded via two TSD203 electrodermal response electrodes also
filled with isotonic gel and attached to the volar surfaces of the index and medius
fingers. All the recordings were screened for physiological artifacts (e.g.,
motion) and analyzed offline using AcqKnowledge 3.5. The peak of the Rwaves were used for the calculation of heart rate (HR) in beats per minute
(BPM) in each of the intervals of interest, from which we subtracted the value of an
Table 1
Scores on the trait portion of State-Trait Anxiety Inventory (STAI) and Zuckerman–Kuhlman Personality Inventory of participants included in this study
Category
STAI-TA
ZKPQ anxiety/neuroticism
ZKPQ aggression/hostility
ZKPQ activity
ZKPQ sociability
ZKPQ sensation-seeking
Women
Men
TA low
TA high
TA low
TA high
27.66 W 0.57
2 W 0.3
7.8 5.44
12.2 2.58
8.2 7.1
9 4.18
58.83 W 4.26
18 W 1.41
9.5 2.58
8.33 3.82
8.5 5
11 3.74
26 W 3.74
0.8 W 0.2
4.33 3.05
13.33 1.15
9 3.6
9.33 1.15
57.5 W 4.94
11
8.5 2.12
6.5 4.94
5.5 6.36
10 1.41
Note: The data are reported as mean standard deviation. No participant from this sample scored above 3 on the Infrequency scale of Zuckerman–Kuhlman
Personality Questionnaire (ZKPQ), which suggests either inattention to the content of the items and acquiescence or a very strong social desirability set (Zuckerman
et al., 1993). The unusually high standard deviations of scores other than TA and anxiety/neuroticism are justified by the specific selection of the participants for
opposing extreme scores of TA and anxiety/neuroticism (bold values).
A.C. Miu et al. / Biological Psychology 77 (2008) 353–358
355
individual functional baseline estimated from recordings made during a relaxed
state before the experiment. We made sure that the HR functional baseline was not
contaminated by anticipatory stress mainly by simultaneously monitoring SCRs,
which are a reliable index of emotional arousal. From SCR recordings, we
extracted the area under the curve (mS/s) of SCRs in the intervals of interest,
after the downdrift in the SCR waves was eliminated using the ‘‘difference’’
function of AcqKnowledge, as described in Bechara et al. (1999). It is noteworthy
that the effect of time differences between intervals of interest, particularly
anticipatory intervals (see below), was controlled by estimating SCRs per unit
of time. All the participants included in this study displayed SCRs during the IGT.
The intervals of interest were of two kinds, comprising (i) 5 s intervals after each
card was turned, which, depending on the type of the card, were of the reward or
punishment type; and (ii) ‘‘anticipatory’’ intervals between the end of each 5 s
reward or punishment interval and before the next card selection.
2.4. Data analyses
The behavioral and electrophysiological data were statistically processed
using analysis of variance (ANOVA) followed by Scheffé post hoc tests,
corrected for repeated measures as necessary. All analysis was conducted using
SPSS. The effect of sex on HR and SCR is supported by physiological
mechanisms independent of this task. Consequently, we focused on the main
effects of sex on behavioral performance, and the effects of TA sex interactions on physiological outcome measures.
3. Results
3.1. Behavior
A 2 (TA: high vs. low) 2 (sex: men vs. women) ANOVA of
CD–AB scores indicates that TA (F[1,18] = 4.44, P < 0.05)
has a statistically significant effect on IGT performance
(Fig. 1A). High TA participants show decreased IGT
performance compared to low TA participants (Scheffé test:
mean difference = 5.09; criterion difference = 4.44, P < 0.05).
We find no statistically significant main effect of sex or
interaction of TA sex on behavioral performance. Also,
neither TA nor the interaction of TA sex is significantly
related to the time required to complete 100 trials in IGT
(mean standard deviation: 11.00 1.09 min).
3.2. Anticipatory somatic responses
The analyses of anticipatory HR and SCRs indicated that
before making a selection, participants generally displayed
cardiac deceleration and higher SCRs. The amplitude of
anticipatory SCRs was generally higher for disadvantageous
compared to advantageous trials (F[1,18] = 4.5, P < 0.05).
However, only anticipatory SCRs in advantageous trials
predicted the CD–AB scores in IGT (r2 = 0.087, P < 0.008).
We obtain significant effects of TA on physiological measures
made before advantageous trials, high TA being associated with
increased physiological responses in anticipation of advantageous trials. In contrast, TA had non-significant effects on
anticipatory HR and SCRs in disadvantageous trials. Specifically, in comparison to low TA participants, high TA participants
displayed increased cardiac deceleration (F[1,18] = 16.04,
P < 0.0001) and SCR amplitude (F[1,18] = 7.07, P < 0.008)
before advantageous trials. Our data also reveal a significant
interaction of TA sex on anticipatory HR deceleration and
SCRs in advantageous trials (P < 0.05).
Fig. 1. Iowa Gambling Task performance (A), anticipatory skin conductance
responses (SCRs) (B) and heart rate (HR) (C) in high and low trait anxiety (TA)
participants. *P < 0.01.
We investigated whether anticipatory effects developed
during the task by analyzing the effect of TA on physiological
measures in advantageous trials for each block of 20 trials. The
effect of TA on anticipatory HR reached statistical significance
in the second block of trials (F[1,18] = 4.17, P < 0.04), and its
magnitude increased until the last block (F[1,18] = 19.23,
P < 0.0001). Similarly, the effect of TA on anticipatory SCRs
was marginally significant by the end of the first block of trials
(F[1,18] = 3.29, P < 0.07), and its magnitude increased until
the last block (F[1,18] = 10.29, P < 0.004).
3.3. Somatic responses to outcomes
The analyses of physiological responses to reward and
punishment indicate that HR is sensitive to the emotional
valence of the behavioral outcome, with higher cardiac
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A.C. Miu et al. / Biological Psychology 77 (2008) 353–358
deceleration in the trials associated with punishment (mean
difference = 4.96) than in those associated with rewards (mean
difference = 2.95). Moreover, the analyses of physiological
measures as a function of trial (advantageous vs. disadvantageous) and outcome (reward vs. punishment) indicate several
significant differences associated with TA. High TA participants display higher cardiac deceleration in advantageous trials
associated with punishment than those associated with rewards
(F[1,18] = 4.55, P < 0.05). There is also a statistically
significant interaction of TA sex on punishment HR in
advantageous trials (P < 0.01). Low TA participants show
higher reward SCRs compared to punishment SCRs in both
advantageous (F[1,18] = 10.32, P < 0.001) and disadvantageous trials (F[1,18] = 12.74, P < 0.0004). Low TA participants also display higher HR in disadvantageous trials
associated with rewards compared to those associated with
punishment (F[1,18] = 7.51, P < 0.006).
4. Discussion
This study yields two main findings consistent with our
predictions. We find that high TA is associated with impaired
decision-making in IGT, and that this is apparently uncoupled
from the increased and potentially adaptive anticipatory
somatic signals in high TA.
There are at least four mechanisms that might explain the
association between high TA and impaired decision-making.
One is related to the previously demonstrated relationship
between anxiety and the tendency to use fewer cues and
inefficiently select relevant from irrelevant cues in reasoning
tasks (Leon and Revelle, 1985). Indeed, high TA participants
may have attended to a more limited set of data, with the
‘‘blinders’’ caused by their high anxiety (see also the third
mechanism described below) making them focus mostly on the
easily understood rewards, which are the same for every choice
from a given deck. This could have led them to choose from the
high-reward disadvantageous decks more often.1
A second possible mechanism relates to the tendency of
increased declarative elaboration on choices, which has been
associated with high TA (e.g., Calvo et al., 2003). This tendency
would be counterproductive in a complex decision-making task
like IGT in which declarative cues on the optimum gambling
strategy typically become available between trials 50 and 80 in
healthy volunteers (Bechara et al., 1997).
A third mechanism potentially underlying the positive
association between impaired decisions and high TA could
involve distraction by emotions unrelated to the task, which is
more likely to occur in high TA participants (Spielberger, 1966;
Endler and Kocovski, 2001). One such emotion is anticipatory
stress, which has been previously shown to impair IGT
performance (Preston et al., 2007), and to which high TA
participants may be predisposed. This is consistent with the
idea that ‘‘emotion is not one thing’’ (Davidson and van
1
We acknowledge the suggestion made by one of the reviewers in regard to
this mechanism.
Reekum, 2005), allowing that some emotions may have
detrimental consequences to decision outcomes. To the extent
this is true, it might be possible to improve decision-making
through psychological and even pharmacological interventions
(e.g., beta blockers to reduce anxiety interference in high TA).
Finally, it is known that TA correlates with neural activity in
structures including the amygdala, specifically when emotional
stimuli are preattentionally processed (Etkin et al., 2004). IGT
also probably relies on preattentionally processed emotional
cues. Consequently, we speculate that high TA may be
associated with distinct patterns of neural activation triggered
by secondary inducers of somatic signals (i.e., entities
generated by the recall of a personal or hypothetical emotional
event; see Bechara et al., 2000) in structures such as the
amygdala and ventromedial prefrontal cortex. If so, IGT
decisions could be affected.
The effect of TA on IGT performance is also informed by a
previous interesting study by Peters and Slovic (2000) who
report an inverse relationship between negative emotionality
and choices from high-punishment decks. This is particularly
noteworthy in light of the theoretical and empirical work that
connects TA and behavioral inhibition measures (see, e.g., Gray
and McNaughton, 2000/2003 for the former; and Carver and
White, 1994; Zinbarg and Mohlman, 1998, for the latter). The
present study’s results are potentially reconciled with Peters
and Slovic (2000) by noting that we selected extreme TA
participants for our study, while the median split approach was
used by Peters and Slovic (2000) as well as in other recent
studies of TA and decision (Maner et al., 2007; Maner and
Schmidt, 2006; Mitte, 2007). The implication is that it would be
useful to conduct additional research to determine whether the
effects we identify are robust to those with less extreme TA.
In our study high TA was not only associated with impaired
IGT performance but also with increased anticipatory
physiological responses prior to advantageous trials. Moreover,
these physiological responses were evidently acquired during
the task since the magnitude of this effect developed over trials.
This set of results is important for at least three reasons. First, it
seems to support the importance of somatic markers to
decision-making by indicating that advantageous trials were
preceded by increased HR deceleration, a psychophysiological
index of orientation (see, e.g., Bradley, 2000), and an increase
in SCR amplitude. Moreover, anticipatory SCRs in advantageous choices predicted IGT performance. However, since we
did not control the level of declarative knowledge in the task in
this study, these results cannot exclude the involvement of
declarative knowledge in IGT performance (Maia and McClelland, 2004).
Second, at least for high TA, these results seem to provide an
example of uncoupling between decision-making performance
and somatic markers. This is in line with a previous suggestion
that some healthy volunteers may override the adaptive
influence of their somatic markers by higher cognitive
processes (Bechara et al., 2000). Indeed, this is consistent
with the pattern of high autonomic reactivity (e.g., GonzalezBono et al., 2002; Zahn et al., 1991; Cornwell et al., 2006) and
increased tendency to declaratively elaborate on emotional
A.C. Miu et al. / Biological Psychology 77 (2008) 353–358
stimuli (Calvo et al., 2003), which has been previously
associated with high TA.
Finally, it is noteworthy that this is the second study (see also
Crone et al., 2004) in which cardiovascular measures of somatic
signals were collected. HR was found to be not only sensitive to
the emotional valence of the behavioral outcome (reward vs.
punishment), with higher cardiac deceleration to punishment,
but it also provides convergent evidence for increased
sensitivity of high TA participants to punishment (see Gray
and McNaughton, 2000/2003). More specific indices of cardiac
autonomic regulation (e.g., heart rate variability) may be used
in future studies of the involvement of somatic signals in
decision-making.
It is worthwhile to reiterate that we did not observe a
significant effect of sex on IGT performance, although two
previous studies reported that men outperformed women in IGT
(Reavis and Overman, 2001; Bolla et al., 2004). Explanations
for our non-finding could include our relatively small sample
size, or the fact we selected participants with extreme TA
scores.
In summary, our data suggest that high TA is associated
with both impaired decision-making in IGT as well as
increased and potentially adaptive anticipatory somatic
signals connected to emotion. This pattern is consistent with
a defective modulation of somatic signals coupled with
disrupted discrimination of advantageous and disadvantageous choices in high TA.
Acknowledgements
This study was supported by the Romanian Ministry of
Education and Research through grants CEEX 124/2006 and
54/2006. We are grateful to Alina Zlati for help with the
analyses of electrophysiological data, and Drs. Adrian Opre and
Horia D. Pitariu for allowing us to use the Romanian versions of
the ZKPQ and STAI questionnaires. This paper was partially
presented at the IAREP-SABE Conference, Paris, France, 5–8
July 2006.
Contributors: A.C.M., R.M.H. and D.H. designed the
research; A.C.M. and R.M.H performed the research;
A.C.M. and R.M.H. analyzed the data; A.C.M. and D.H.
wrote the paper.
References
Bechara, A., Damasio, A.R., 2005. The somatic marker hypothesis: a neural
theory of economic decision. Games and Economic Behaviour 52,
336–372.
Bechara, A., Damasio, A.R., Damasio, H., Anderson, S.W., 1994. Insensitivity
to future consequences following damage to human prefrontal cortex.
Cognition 50 (1–3), 7–15.
Bechara, A., Damasio, H., Damasio, A.R., 2000. Emotion, decision making and
the orbitofrontal cortex. Cerebral Cortex 10 (3), 295–307.
Bechara, A., Damasio, H., Damasio, A.R., Lee, G.P., 1999. Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. Journal of Neuroscience 19 (13), 5473–5481.
Bechara, A., Damasio, H., Tranel, D., Damasio, A.R., 1997. Deciding advantageously before knowing the advantageous strategy. Science 275 (5304),
1293–1295.
357
Bolla, K.I., Eldreth, D.A., Matochik, J.A., Cadet, J.L., 2004. Sex-related
differences in a gambling task and its neurological correlates. Cerebral
Cortex 14 (11), 1226–1232.
Bradley, M.M., 2000. Emotion and motivation. In: Cacioppo, J.T., Tassinary,
L.G., Berntson, G.G. (Eds.), Handbook of Psychophysiology. second ed.
Cambridge University Press.
Buckholtz, J.W., Callicott, J.H., Kolachana, B., Hariri, A.R., Goldberg, T.E.,
Genderson, M., et al. Genetic variation in MAOA modulates ventromedial
prefrontal circuitry mediating individual differences in human personality.
Molecular Psychiatry (May 22), in press.
Calvo, M.G., Avero, P., Miguel-Tobal, J.J., 2003. Multidimensional anxiety and
content-specificity effects in preferential processing of threat. European
Psychiatry 8 (4), 252–265.
Carver, C.S., White, T.L., 1994. Behavioral inhibition, behavioral activation,
and affective responses to impending reward and punishment: the BIS/BAS
scales. Journal of Personality and Social Psychology 67, 319–333.
Cornwell, B.R., Johnson, L., Berardi, L., Grillon, C., 2006. Anticipation of
public speaking in virtual reality reveals a relationship between trait social
anxiety and startle reactivity. Biological Psychiatry 59 (7), 664–666.
Crone, E.A., Somsen, R.J., Van Beek, B., Van Der Molen, M.W., 2004. Heart
rate and skin conductance analysis of antecendents and consequences of
decision making. Psychophysiology 41 (4), 531–540.
Davidson, R.J., van Reekum, C.M., 2005. Emotion is not one thing. Psychological Inquiry 16, 16–18.
Decety, J., Jackson, P.L., Sommerville, J.A., Chaminade, T., Meltzoff, A.N.,
2004. The neural bases of cooperation and competition: an fMRI investigation. Neuroimage 23 (2), 744–751.
Dunn, B.D., Dalgleish, T., Lawrence, A.D., 2006. The somatic marker hypothesis: a critical evaluation. Neuroscience and Biobehavioral Reviews 30 (2),
239–271.
Endler, N.S., Kocovski, N.L., 2001. State and trait anxiety revisited. Journal of
Anxiety Disorders 15 (3), 231–245.
Etkin, A., Klemenhagen, K.C., Dudman, J.T., Rogan, M.T., Hen, R., Kandel,
E.R., et al., 2004. Individual differences in trait anxiety predict the response
of the basolateral amygdala to unconsciously processed fearful faces.
Neuron 44, 1043–1055.
Gonzalez-Bono, E., Moya-Albiol, L., Salvador, A., Carrillo, E., Ricarte, J.,
Gomez-Amor, J., 2002. Anticipatory autonomic response to a public speaking task in women: the role of trait anxiety. Biolgical Psychology 60 (1), 37–
49.
Grachev, I.D., Apkarian, A.V., 2000. Anxiety in healthy humans is associated
with orbital frontal chemistry. Molecular Psychiatry 5 (5), 482–488.
Gray, J.A., McNaughton, N., 2000/2003. The Neuropsychology of Anxiety.
Oxford University Press, New York.
Kurzban, R., Houser, D., 2001. Individual differences in cooperation in a
circular public goods game. European Journal of Personality 15 (S1),
S37–S52.
Lau, J.Y., Eley, T.C., Stevenson, J., 2006. Examining the state-trait anxiety
relationship: a behavioural genetic approach. Journal of Abnormal Child
Psychology 34 (1), 19–27.
Leon, M.R., Revelle, W., 1985. Effects of anxiety on analogical reasoning: a test
of three theoretical models. Journal of Personality and Social Psychology 49
(5), 1302–1315.
Lesch, K.P., Bengel, D., Heils, A., Sabol, S.Z., Greenberg, B.D., Petri, S., et al.,
1996. Association of anxiety-related traits with a polymorphism in the
serotonin transporter gene regulatory region. Science 274 (5292), 1527–
1531.
Maia, T.V., McClelland, J.L., 2004. A reexamination of the evidence for the
somatic marker hypothesis: what participants really know in the Iowa
gambling task. Proceedings of the National Academy of Sciences of the
United States of America 101 (45), 16075–16080.
Maner, J.K., Richey, J.A., Cromer, K., Mallott, M., Lejuez, C.W., Joiner, T.E.,
Schmidt, N.B., 2007. Dispositional anxiety and risk-avoidant decisionmaking. Personality and Individual Differences 42, 665–675.
Maner, J.K., Schmidt, N.B., 2006. The role of risk avoidance in anxiety.
Behaviour Therapy 37 (2), 181–189.
Mathews, A., Mackintosh, B., 1998. A cognitive model of selective processing
in anxiety. Cognitive Therapy and Research 22 (6), 539–560.
358
A.C. Miu et al. / Biological Psychology 77 (2008) 353–358
McCabe, K., Houser, D., Ryan, L., Smith, V., Trouard, T., 2001. A functional
imaging study of cooperation in two-person reciprocal exchange. Proceedings of the National Academy of Sciences of the United States of America
98 (20), 11832–11835.
Mitte, K., 2007. Anxiety and risky decision-making: The role of subjective
probability and subjective costs of negative events. Personality and Individual Differences 43, 243–253.
Opre, D., Kiss, F., Opre, A., 2003. Scala cautarii de senzatii: Aplicabilitate
transculturala [The sensation-seeking scale: Transcultural applicability]. In:
Opre, A. (Ed.), Noi tendinte in psihologia personalitatii: Diagnoza, cercetare si aplicatii [New Trends in Psychology of Personality: Diagnosis,
Research, and Applications]. Asociatia de Stiinte Cognitive din Romania,
Cluj-Napoca, pp. 15–36.
Paulus, M.P., Feinstein, J.S., Simmons, A., Stein, M.B., 2004. Anterior cingulate
activation in high trait anxious subjects is related to altered error processing
during decision making. Biological Psychiatry 55 (12), 1179–1187.
Peters, E., Slovic, P., 2000. The springs of action: affective and analytical
information processing in choice. Personality and Social Psychology Bulletin 26 (12), 1465–1475.
Pitariu, H., Miclea, M., Munteanu, I., 1987. Tipul A de comportament si stresul
profesional la personalul muncitor feminin cu functii de conducere [Type A
behavior and professional stress in women workers in management positions]. Review of Psychology 4, 33–39.
Preston, S.D., Buchanan, T.W., Stansfield, R.B., Bechara, A., 2007. Effects of
anticipatory stress on decision making in a gambling task. Behavioural
Neuroscience 121 (2), 257–263.
Reavis, R., Overman, W.H., 2001. Adult sex differences on a decision-making
task previously shown to depend on the orbital prefrontal cortex. Behavioural Neuroscience 115 (1), 196–206.
Spielberger, C.D., 1966. Anxiety and Behaviour. Academic Press, New York.
Spielberger, C.D., 1983. Manual for the State-Trait Anxiety Inventory. Consulting Psychologists Press, Palo Alto.
Yamasue, H., Abe, O., Suga, M., Yamada, H., Inoue, H., Tochigi, M., et al.,
2008. Gender-common and -specific neuroanatomical basis of human
anxiety-related personality traits. Cerebral Cortex 18, 46–52.
Zahn, T.P., Nurnberger Jr., J.I., Berrettini, W.H., Robinson Jr., T.N., 1991.
Concordance between anxiety and autonomic nervous system activity in
subjects at genetic risk for affective disorder. Psychiatry Research 36 (1),
99–110.
Zinbarg, R., Mohlman, J., 1998. Individual differences in the acquisition of
affectively-valenced association. Journal of Personality and Social Psychology 74, 1024–1040.
Zuckerman, M., Kuhlman, M., Joiremann, J., Teta, P., Kraft, M., 1993. A
comparison of three structural models for personality: the big three, the big
five, and the alternative five. Journal of Personality and Social Psychology
65, 757–768.