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Explaining Enhanced Logical Consistency during Decision Making in Autism

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The emotional responses elicited by the way options are framed often results in lack of logical consistency in human decision making. In this study, we investigated subjects with autism spectrum disorder (ASD) using a financial task in which the monetary prospects were presented as either loss or gain. We report both behavioral evidence that ASD subjects show a reduced susceptibility to the framing effect and psycho-physiological evidence that they fail to incorporate emotional context into the decision-making process. On this basis, we suggest that this insensitivity to contextual frame, although enhancing choice consistency in ASD, may also underpin core deficits in this disorder. These data highlight both benefits and costs arising from multiple decision processes in human cognition.
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Explaining Enhanced Logical Consistency during Decision
Making in Autism
Benedetto De Martino1,*, Neil A. Harrison1,2,*, Steven Knafo2, Geoff Bird2, and Raymond J.
Dolan1
1Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG,
United Kingdom
2Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, United
Kingdom
Abstract
The emotional responses elicited by the way options are framed often results in lack of logical
consistency in human decision making. In this study, we investigated subjects with autism
spectrum disorder (ASD) using a financial task in which the monetary prospects were presented as
either loss or gain. We report both behavioral evidence that ASD subjects show a reduced
susceptibility to the framing effect and psycho-physiological evidence that they fail to incorporate
emotional context into the decision-making process. On this basis, we suggest that this
insensitivity to contextual frame, although enhancing choice consistency in ASD, may also
underpin core deficits in this disorder. These data highlight both benefits and costs arising from
multiple decision processes in human cognition.
Keywords
autism spectrum disorder; ASD; decision-making; rationality; economics; framing effect; skin
conductance response; SCR
Introduction
Logical consistency across decisions, regardless of how choices are presented, is a central
tenet of rational choice theory and the cornerstone of modern economic and political science
(Luce and Raiffa, 1957; Arrow, 1982). Empirical data challenge this perspective by showing
that humans are highly susceptible to the manner or context in which options are cast,
resulting in a decision bias termed the “framing effect” (Tversky and Kahneman, 1974). We
have previously shown that the amygdala mediates this framing bias, a finding that
highlights the importance of incorporating emotional processes within models of human
decision making (De Martino et al., 2006; Kahneman and Frederick, 2007). An ability to
integrate emotional contextual information into the decision process provides a useful
heuristic in decision making under uncertainty. This is a factor that is likely to assume
considerable importance during social interactions in which information about others is
often incomplete, ambiguous, and not easily amenable to standard inferential reasoning
processes.
Correspondence should be addressed to Benedetto De Martino, Wellcome Trust Centre, University College London, 12 Queen Square,
London WC1 N 3BG, UK. E-mail:b.martino@fil.ion.ucl.ac.uk..
*B.D.M. and N.A.H. contributed equally to this work.
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Published in final edited form as:
J Neurosci
. 2008 October 15; 28(42): 10746–10750. doi:10.1523/JNEUROSCI.2895-08.2008.
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In this study, we investigated the effect of contextual frame on choice behavior of
individuals with autistic spectrum disorder (ASD) (see Fig. 1). Autism is a
neurodevelopmental disorder characterized by deficits in social interaction, qualitative
impairments in communication, and repetitive and stereotyped patterns of behavior,
interests, and activities (Kanner, 1943; Asperger, 1944). From Kanner's earliest description,
it has been recognized that individuals with ASD have a strong tendency to focus on parts
rather than global aspects of objects of interest and are unable to integrate disparate
information into a meaningful whole (weak central coherence theory) (Frith and Happé,
1994; Happé and Booth, 2008).
We previously proposed that susceptibility to a framing bias reflects the operation of an
affect heuristic (De Martino et al., 2006; Kahneman and Frederick, 2007). Here, we show
that individuals with ASD, a condition characterized by marked behavioral inflexibility,
demonstrate a decreased susceptibility to framing resulting in an unusual enhancement in
logical consistency that is paradoxically more in line with the normative prescriptions of
rationality at the core of the current economics theory (Luce and Raiffa, 1957; Arrow,
1982). Furthermore, insensitivity in these subjects to a contextual framing bias was
associated with a failure to express a differential autonomic response to contextual cues as
indexed in skin conductance responses (SCRs), a standard measure of emotional processing.
Our findings suggest that a more consistent pattern of choice in the ASD group reflects a
failure to incorporate emotional cues into the decision process, an enhanced economic
“rationality” that may come at a cost of reduced behavioral flexibility.
Materials and Methods
Subjects
Thirty-two subjects participated to the study, with 29 included in the final analysis. Of these
32, three subjects were excluded: one subject was found to be on antipsychotic drug
treatment (Olanzapine) after enrolment, one subject was unable to fully understand the task
instructions, and a third was excluded because he was a statistical outlier (his score on the
framing effect was greater than two SD above the group mean). Therefore, after exclusion, a
total of 29 subjects were included in the final analysis. Fourteen ASD subjects (10 male;
mean age 34.8 ± 7.9 years) were age and intelligence quotient (IQ) matched with 15 controls
(11 male; mean age 32.2 ± 8.5 years). Of note, two subjects in the ASD group were taking a
selective serotonin reuptake inhibitor (SSRI) anti-depressant medication. These subjects
were not excluded as we did not initially anticipate SSRIs to interfere with the cognitive
abilities involved in the task; however, because it has been reported that serotonin can effect
emotional processing (Canli and Lesch, 2007); we also repeated our statistical comparison
excluding these two subjects (see Results). All ASD subjects were diagnosed using
international classification of diseases-10 (ICD- 10) criteria by specialized clinicians before
inclusion (Table 1). An additional subject (ASD group) was excluded from the SCR
analysis, attributable to technical failure. Subjects performed a framing financial decision
making task (see below, Experimental paradigm), previously described in De Martino et al.
(2006). SCR was recorded throughout data acquisition.
The ASD group, comprising 10 males and 4 females, had a mean age of 34.8 years (SD,
±7.9 years) and a mean full-scale IQ score of 112.1 ± 13.5 (mean verbal IQ score, 112.6 ±
11.6; and mean performance IQ score, 109.0 ± 16.1). All ASD subjects had received a
clinical diagnosis of autism or ASD by a specialized clinician before inclusion. In addition,
all subjects had an independent autism diagnostic observation schedule (ADOS) assessment
to quantify the degree of impairment across the domains of communication and reciprocal
social interaction (Lord et al., 2000). The ADOS is a research standardized test that provides
an index of autistic symptoms observed on a particular occasion. All subjects took module 4
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(designed to assess adults) and received two scores: (1) a communication score (labeled
“ADOS score 1” in Table 1) on which the ASD cutoff is 2 and the autism cutoff is 4 and (2)
a reciprocal interaction (or “social”) score (labeled “ADOS score 2”) on which the ASD
cutoff is 4 and the autism cutoff is 7. Overall, the total ADOS score cutoff for ASD is 7 and
the cutoff for autism is 12. We note, however, that the ADOS classification is not a clinical
diagnosis (i.e., based on standardized DSM-IV/ICD- 10) (Table 1) and, although it may
contribute to diagnosis, cannot replace full systematic assessment by a specialized clinician.
For this reason, one ASD subject (subject 24) had a clinical diagnosis of autism, although
scored below the ADOS cutoff for autism spectrum disorder. The control group, comprising
11 males and 4 females, had a mean age of 32.2 ± 8.5 and mean full-scale IQ score of 116.5
± 7.7(mean verbal IQ score, 114.8 ± 8.5; mean performance IQ score, 115.6 ± 8.5). There
were no significant differences between the two groups in age (
p
= 0.41, independent
t
test),
full-scale IQ score (
p
= 0.29, independent
t
test), verbal IQ score (
p
= 0.56, independent
t
test), or performance IQ score (
p
= 0.17, independent
t
test) (Table 1).
The study was conducted with the approval of the National Hospital for Neurology and
Neurosurgery and the Institute of Neurology Joint Research Ethics Committee, London, UK.
Experimental paradigm
The experiment was divided into three parts: an instruction phase, a task phase during which
subjects performed the task (during this phase SCR was recorded), and a questionnaire
phase. In the instruction phase, subjects were familiarized with decision-making task and
given a number of practice trials before starting the main behavioral task.
The task was divided into three 17 min sessions. Each session comprised 96 trials (32 loss
frame, 32 gain frame, and 32 catch trials) ordered pseudorandomly. At the beginning of each
trial, participants were shown a message indicating the initial amount of money that they
received to play that trial (e.g., “you receive £50”) (2 s). Four different starting amounts
were used in the experiment: 25, 50, 75, and £100. Participants were instructed that they
would not be able to retain the whole of this initial amount but would have to choose
between a sure and a gamble (risky) option (4 s).
In the gain frame trials, the sure option was presented as the amount of money retained from
the starting amount (e.g., “keep £20” from an initial amount of £50) and in loss frame trials
as the total amount of money lost from the starting amount (e.g., “lose £30” from a total of
£50). The gamble option was identical for both frames and was represented by a pie chart
depicting the probability of winning and losing in green and red, respectively (Fig. 1). Four
different probabilities were used in the experiment: 20, 40, 60, and 80%. All experimental
variables (total starting amount, percentage of the money offered, number of trials per
session) were fully counterbalanced between frame conditions. The expected value of the
options were balanced in each trial (with the exception of the catch trials, see below) and
mathematically equivalent between frames. For example, if participants initially received
£50, they were then required to choose between the options “keep £20” or a gamble with a
40% chance of winning £50 and a 60% chance of winning nothing. Participants were
required to respond within 4 s by key press.
Given the equivalence of the choices in terms of expected outcomes, we included “catch”
trials (32 trials each session) to ensure that subjects remained actively engaged in the
decision-making task throughout the course of the experiment. In these catch trials, in both
frames, expected outcomes for the sure and gamble option were markedly unbalanced: in
half of the trials (“gamble weighted”) the gamble option was preferable (e.g., 95%
probability of winning by taking the gamble option vs a sure choice of 50% of the initial
amount), and for the other half of trials (“sure weighted”) the sure option was preferable
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(e.g., 5% probability of winning by taking the gamble option vs a sure choice of 50% of the
initial amount). As in the main experimental trials, the catch trials were also presented in
either a gain or a loss frame.
Note that the behavioral task they were asked to perform was identical to the one used in the
functional magnetic resonance imaging (fMRI) experiment described by De Martino et al.
(2006).
Behavioral data analysis
The behavioral data were analyzed using the statistic software SPSS. The main effect of
frame was calculated using a mixed measures ANOVA with frame (gain and loss) as the
within subject factor and group (ASD and control) as the between subject factor. Significant
main effects and interactions were then further analyzed using paired and independent
sample
t
tests. Effect of frame within each group (i.e., ASD and control) was calculated as
the percentage of trials in which subjects chose the “gamble” option within each frame. The
incorrect catch trials responses (i.e., when the subject fails to chose the option with the
dominant expected value independently of the framing manipulation) were analyzed using a
two-sample (i.e., ASD and control)
t
test.
SCR data analysis
SCR was recorded using two Ag/AgCl electrodes (skin conductance recorder, AT-64;
Autogenic Systems Laboratory) attached using surgical tape to the palmar surface of
subjects distal phalanges of the second and fourth fingers of the left hand (Dawson et al.,
2000). Conductive gel was applied between the skin and the electrodes. SCR signal and
event markers were sent to an analog-to-digital converter (CED-Power1401) then recorded
on two different channels using the software Spike2 (v5; Cambridge Electronic Design).
Skin conductance responses and event markers were recorded at 100 Hz. The window of
interest was defined as the 5 s after the subject's decision. Baseline skin conductance was
calculated by averaging the skin conductance level during the 0.5 s before the presentation
of the task. Amplitude of the SCR was defined as the difference between the time-window
peak value and the baseline. Attributable to technical failure, skin conductance for one
subject (ASD) was not recorded, and three further subjects (total of two from each group)
were subsequently excluded because of lack of physiological SCR responses [amplitude <2
microSiemens (S)]. All remaining SCR data were visually inspected and nonphysiological
SCR responses (<10% of the entire data set) were removed before further analysis. SCR
responses to each trial were recorded for each subject. Mean SCR and SD of SCR responses
were then calculated and used to produce
z
-transformed SCR responses for each trial per
subject (Yaremko, 1986)
Z
-transformed SCR results were then analyzed using a 2 × 2 × 2 mixed-measures ANOVA
with within-subject factors of frame (loss frame, gain frame) and choice (risky choice, sure
choice), group (ASD, control) was the between-subject factor.
Results
In accordance with our previously reported findings, all control subjects manifest
susceptibility to the framing effect, reflected in an increased disposition to gamble in loss
compared with gain frames (mean, 14.24 ± 1.68%). This susceptibility to the frame
manipulation was markedly reduced in the ASD group (mean, 7.66 ± 1.95%) (Fig. 2
A
). The
significance of this effect was confirmed in an interaction analysis showing that the ASD
subjects were significantly more consistent (i.e., less influenced by the frame) in their
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pattern of choice compared with controls [ANOVA; group (ASD, control) × frame (gain,
loss);
F
(1,27) = 6.56,
p
< 0.02].
The ASD group also showed mild risk aversion compared with controls evidenced in a trend
level main effect of group (
F
(1,27) = 3.91,
p
= 0.058) (Fig. 2
B
). To ensure that our findings
were not driven by greater risk aversion in the ASD group, we repeated the ANOVA with
individual risk tendency (calculated as percentage of risky choices independently of frame)
as a covariate. This analysis corroborated our previous findings [ANOVA; group (ASD,
control) × frame (gain, loss);
F
(1,26) = 10.03,
p
< 0.005] by showing that the ASD group
was significantly less affected by the framing decision bias even after controlling for
differences in absolute risk attitude. This result held even after reducing the size of the ASD
group (see Materials and Methods) by excluding the two ASD subjects taking SSRI
medication [ANOVA; group (ASD, control) × frame (gain, loss);
F
(1,25) = 5.04,
p
< 0.02].
To control that the ASD subjects were fully engaged in the task and were responding to
monetary incentives similarly to the control group, we analyzed the performance in the catch
trials response (see Materials and Methods) by two-tailed paired
t
test.
This statistical comparison did not show significant difference between the two groups (
t
(27)
= 1.8,
p
= 0.09). Furthermore, in light of a possible trend level effect, we additionally
ensured that the individual performance on catch trials did not impact on the main
conclusion by repeating our critical statistical comparison [ANOVA; group (ASD, control)
× frame (gain, loss);
F
(1,27) = 7.23,
p
< 0.02] covarying out individual performance on the
catch trials; as can be seen, our main effect remained significant.
Acquisition of subjects' SCRs, while they performed the task, enabled us to obtain an on-line
measurement of their autonomic responses to the framing manipulation. Analysis of these
data revealed that the ASD group showed a higher absolute SCR response for each frame
(gain frame, 0.72 ± 0.14 S; loss frame, 0.70 ± 0.12 S) compared with the control group (gain
frame, 0.47 ± 0.15 S; loss frame, 0.54 ± 0.18 S),probably attributable to increased anxiety.
However, the ASD individuals critically showed a lack of a differential response to the
frame manipulation. In fact, although loss and gain frames induced differential skin
conductance responses in controls (
t
(12) = 3.19,
p
< 0.01, paired
t
test), SCR did not
differentiate between frames in the ASD group (
t
(11) = 0.96,
p
= 0.36, paired
t
test) (Fig. 3).
These results were again corroborated by a significant two-way interaction (frame; group;
F
(1,23) = 4.86,
p
< 0.05) but no main effect of group (
F
(1,23) = 0.8,
p
= 0.46) in a 2 × 2 × 2
ANOVA (group, frame, choice). These data further support our contention that ASD
subjects, although having an absolute emotional response, crucially fail to differentially
engage emotional processes in response to the framing manipulation.
Discussion
These findings suggest the ASD group fail to integrate emotional contextual cues into the
decision-making process. This is evident both in a reduced behavioral susceptibility of a
framing effect and an ab sence of a differential SCR response to our contextual
manipulation. The concept that ASD individuals fail to integrate information across
cognitive domains also informs the suggestion that an uneven profile of abilities and
deficiencies in autistic individuals may reveal an imbalance in empathizing and systemizing
behaviors (Baron-Cohen and Belmonte, 2005).
Our SCR results in the context of a high-level decision task supports convergent evidence of
impairment in emotional processing in autism (Baron-Cohen et al., 2000; Adolphs, 2002).
Paradoxically, although this impairment in processing contextual emotional information
protects ASD subjects from the framing bias, leading to more consistent behavior in
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situations of risk, it may come at a cost of the social, emotional, and behavioral deficits that
characterize the condition.
Recent theoretical accounts of decision making have put forward a “two-systems” model of
human judgment (Evans, 2003). This view proposes that human decision making arises
through a combination of intuitive and analytic processes. This model proposes that intuitive
reasoning is rapid and capable of processing large amounts of information in parallel;
however, it is prone to mistakes and strongly influenced by contextual emotional
information (Kahneman, 2003). In contrast, analytical reasoning is more accurate but slow
and computationally demanding. According to this view, the framing bias reflects an affect
heuristic by which normal individuals incorporate a potentially broad range of additional
emotional information into the decision process. In evolutionary terms, this mechanism may
confer a strong advantage because such contextual cues may carry useful, even critical,
information that dictates a rapid response. We propose that this ability is particularly crucial
in a social context in that subtle contextual cues communicate knowledge elements (possibly
unconscious) that allow optimal decisions to be made in uncertain environments (Stanovich
and West, 2002).
In the context of the “two-systems” model of decision making described above, these results
suggest that ASD individuals have an increased tendency toward the analytic type of
decision making, attributable to impairment within their intuitive reasoning mechanisms.
This interpretation would also support the empathizing-systemizing (E-S) theory of autism
(Baron-Cohen and Belmonte, 2005). The E-S theory proposes that the imbalance between
analytic and empathic behavior underlies both the impairment in social skills in ASD and
their enhanced analytical skills. During the framing task, ASD subjects were better able to
ignore biasing contextual information and isolate the critical information about the
numerical value of the sure and risky options. This result is consistent with other
experimental findings showing that ASD have enhanced attention for the task's details but
reduced capacity to deal with the global aspect of the task as predicted by weak coherence
theory (Frith and Happe, 1994).
In a previous fMRI study (De Martino et al., 2006; Kahneman and Frederick, 2007), we
showed that the engagement of an amygdala-based emotional system played a key role in
underpinning a framing effect. These previous results, combined with the SCR data shown
here, suggest that the failure to assign emotional salience to contextual cues and
consequential lack of behavioral bias in ASD may result from an amygdala based
mechanism. A wealth of empirical data supports this hypothesis. First, histopathological
abnormalities of the amygdala such as an increased cell density and a reduced dendritic
arborization have been described in autism (Bauman and Kemper, 1994). Moreover,
Howard et al. (2000) suggested that persons with high-functioning autism showed a similar
neuropsychological profile to that seen in patients with amygdala lesions, particularly a
selective impairment in the recognition of facial expressions of fear. Last, several imaging
studies demonstrate blunted activation of the amygdala in ASD during tasks which involved
processing of facial expressions (Baron-Cohen et al., 2000; Critchley et al., 2000).
An ability to incorporate a broad range of contextual cues into the decision process endows
humans with a clear evolutionary advantage. This requirement becomes particularly acute
when making decisions in social environments in which multiple subtle contextual cues
carry critical information. We suggest that competence in dealing with social uncertainty
involves deployment of affect heuristics. In ASD, a reduction of framing effect might
explain both enhanced analytic and impoverished social abilities, the latter reflecting an
inability to deploy an affect heuristic in complex and uncertain social contexts. Thus, our
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findings suggest a potential core neurobiological deficit in ASD and also speak to limits, and
trade-offs, in human rationality.
Acknowledgments
This work was supported by a Wellcome Trust Programme Grant (R.J.D.), a Wellcome Trust funded Clinical
Research Fellowship (N.A.H.), and a Wellcome Trust PhD Scholarship (B.D.M.). We thank Uta Frith, Catherine
Sebastian, and Hugo Critchley.
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Figure 1.
Task. Participants were shown a message indicating the amount of money received to play
in that trial (e.g., “you receive £50”). Subjects then had to choose between a “sure” or a
“gamble” option presented in the context of two different “frames.” The “sure” option was
formulated as either the amount of money retained from the initial starting amount (e.g.,
keep £20 of a total of £50-gain frame) or as the amount of money lost from the initial
amount (e.g., lose £30 of a total of £50-loss frame). The “gamble” option was identical in
both frames and represented as a pie chart depicting the probability of winning or losing.
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Figure 2.
Behavioral data. A, Summary of the susceptibility of subjects to the framing manipulation
(mean ± SE) calculated as a percentage of increased gambling in the loss frame compared
with the gain frame. The susceptibility to the framing manipulation is significantly reduced
in the ASD group (mean, 7.66 ± 1.95%) compared with the control group (mean, 14.24 ±
1.68%) [ANOVA; group (ASD, control) × frame (gain, loss);
F
(1,27) = 10.03,
p
< 0.005]. B,
Percentage of trials in which subjects chose the risky option rather than the sure option for
both frame manipulations: in the control group, subjects gambled in 43.75% (±4.72) of the
trials in the gain frame and 57.99% (±4.70) of the trials in the loss frame whereas in the
ASD group the percentages were respectively 34.52% (±4.99) and 42.19% (±3.64). A group
(ASD, control) × frame (gain, loss) 2 × 2 ANOVA yielded a highly significant main effect
of frame (
F
(1,27) = 72.83,
p
< 0.0001) in accordance with framing effect manipulation
(increase in risk in loss frame compared with the gain frame). The critical two-way
interaction (group, frame) yielded a significant result (
F
(1,27) = 6.56,
p
< 0.02), supporting
our hypothesis that ASD subjects have a significantly reduced susceptibility to the framing
manipulation compared with the control group. Notably, the ASD group showed a mild risk
aversion compared with controls evidenced by trend level main effect of group (
F
(1,27) =
3.91,
p
= 0.058).
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Figure 3.
SCR data. Mean difference in SCR amplitude in S to the loss versus gain frame in each
group. Control group (0.071 S; ±0.026 S) and ASD group (−0.019 S; ±0.034 S) showing
loss of differential SCR response to the framing manipulation in the ASD group compared
with controls [ANOVA (group, frame, choice);
F
(1,23) = 4.86,
p
< 0.05].
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De Martino et al. Page 12
Table 1
Details of participants
Sub# Group Age Gender V-IQ P-IQ F-IQ ADOS score1 ADOS score2 ADOS total score ADOS classification
1 ASD 52.77 M 134 122 132 3 4 7 Autism spectrum
2* ASD 28.23 M 105 90 99 4 7 11 Autism spectrum
3 ASD 29.85 F 104 100 103 4 5 9 Autism spectrum
4 ASD 30.42 F 100 80 91 5 12 17 Autism
5 ASD 22.86 M 112 99 107 4 8 12 Autism
6 ASD 32.7 M 119 125 124 3 7 10 Autism spectrum
7 ASD 42.43 M 123 107 117 4 4 8 Autism spectrum
8 ASD 39.13 M 95 104 99 4 6 10 Autism spectrum
9 ASD 34.86 M 100 102 101 2 6 8 Autism spectrum
10 ASD 29.62 M 125 119 125 3 4 7 Autism spectrum
11 ASD 35.64 F 114 116 116 4 10 14 Autism
12 C 24.17 F 105 113 109
13 C 25.76 M 134 114 128
14 C 32.46 M 103 117 110
15
a
ASD 28.59 M 112 89 102 4 6 10 Autism spectrum
16 ASD 24.7 M 124 125 128 3 6 9 Autism spectrum
17 C 38.68 M 112 111 112
18 C 53.14 M 105 113 109
19 ASD 30.15 M 102 84 94 2 5 7 Autism spectrum
20 C 32.25 F 114 110 113
21
a
C 41.36 M 91 102 95
22 C 23.54 M 125 136 134
23 C 27.87 M 122 121 123
24 ASD 44 M 112 107 110 1 2 3 None
25 C 24.79 M 111 111 112
26 ASD 38 F 112 136 123 3 8 11 Autism spectrum
27 C 28.21 F 108 105 107
28 C 29.2 M 120 110 118
J Neurosci
. Author manuscript; available in PMC 2009 May 15.
Europe PMC Funders Author Manuscripts Europe PMC Funders Author Manuscripts
De Martino et al. Page 13
Sub# Group Age Gender V-IQ P-IQ F-IQ ADOS score1 ADOS score2 ADOS total score ADOS classification
29 C 30.22 M 112 130 122
30 C 40.84 M 122 109 117
31 C 43.45 F 111 110 111
32 C 28.66 M 118 124 122
C, Control; V-IQ, verbal-IQ score; P-IQ, performance IQscore; F-IQ, full-scale IQ score; M, male; F, female; ADOS score 1, communication score; ADOS score 2, reciprocal interaction score.
a
Excluded (see Materials and Methods).
J Neurosci
. Author manuscript; available in PMC 2009 May 15.
... Intergroup bias might emerge differently among individuals with autism spectrum disorder (ASD), who are characterized by altered social interaction and atypical interests (5-10). Previous studies have suggested that individuals with ASD tend to be less sensitive to context stimuli, and make more rational and/or consistent decisions (11)(12)(13)(14)(15)(16). For example, loss/gain framing effects have been reported to be lower when individuals with ASD make choices between gambles (13,17). ...
... Previous studies have suggested that individuals with ASD tend to be less sensitive to context stimuli, and make more rational and/or consistent decisions (11)(12)(13)(14)(15)(16). For example, loss/gain framing effects have been reported to be lower when individuals with ASD make choices between gambles (13,17). Farmer et al. (14) showed that individuals with ASD were less influenced by decoy options in an attraction effect task. ...
... Moreover, our recent research has also supported such attenuated cognitive bias in ASD; we showed that the sunk cost effect was lower in individuals with ASD (sunk cost is defined as the tendency to continue an investment, or take an action, although future costs are larger than benefits, if costs of time, money, or effort were previously incurred) (15,16). Choice consistency is regarded normative in the conventional economic theory (13)(14)(15)(16); therefore, these previous findings contribute to a better understanding of ASD by showing a valuable strength and difficulty in decision-making of individuals with ASD (18)(19)(20). ...
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Groups are essential elements of society, and humans, by nature, commonly manifest intergroup bias (i.e., behave more positively toward an ingroup member than toward an outgroup member). Despite the growing evidence of various types of altered decision-making in individuals with autism spectrum disorder (ASD), their behavior under the situation involving group membership remains largely unexplored. By modifying a third-party punishment paradigm, we investigated intergroup bias in individuals with ASD and typical development (TD). In our experiment, participants who were considered as the third party observed a dictator game wherein proposers could decide how to distribute a provided amount of money while receivers could only accept unconditionally. Participants were confronted with two different group situations: the proposer was an ingroup member and the recipient was an outgroup member (IN/OUT condition) or the proposer was an outgroup member and the recipient was an ingroup member (OUT/IN condition). Participants with TD punished proposers more severely when violating social norms in the OUT/IN condition than in IN/OUT condition, indicating that their decisions were influenced by the intergroup context. This intergroup bias was attenuated in individuals with ASD. Our findings deepen the understanding of altered decision-making and socioeconomic behaviors in individuals with ASD.
... Autism Spectrum Disorder (ASD) is characterised by difference in social communication and interaction combined with a pattern of restricted and repetitive behaviours, interests and activities (APA, 2013;WHO, 2018). Evidence for the Dual Process Theory of Autism has been shown through a more 'logically consistent' style of thinking by individuals with a diagnosis of ASD than control groups without ASD (De Martino et al., 2008), also characterised as 'circumspect reasoning bias' (Brosnan et al., 2014). Individuals with a diagnosis of ASD also show less susceptibility to the biases which are associated with intuitive processing (Farmer et al., 2017;Fujino et al., 2019;Shah et al., 2016;see Kahneman, 2011). ...
... The Dual Process Theory of Autism proposes that the default interventionist position is attenuated or absent in autism, resulting in defaulting to deliberative processing. This results in more logical accurate responses, less influenced by potentially erroneous biases in groups with a diagnosis of ASD (Brosnan et al., 2016(Brosnan et al., , 2017De Martino et al., 2008;Farmer et al., 2017;Fujino et al., 2019;Lewton et al., 2019;Shah et al., 2016). The pattern of the autism group reflecting an attenuated pattern of the control group effects (see Fig. 1 and a small within-participants effect in the autism group and a medium to large within-participants effect in the control group) is suggestive of an attenuated rather than absent default-interventionist position for individuals with a diagnosis of ASD. ...
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Art appreciation reflects an initial emotional and intuitive response to artwork evaluation, although this intuitive evaluation can be attenuated by subsequent deliberation. The Dual Process Theory of Autism proposes that individuals with Autism Spectrum Disorder (ASD) have a greater propensity to deliberate and reduced intuition compared to matched controls. Evaluations of high- and low-quality artworks were undertaken by 107 individuals with a diagnosis of ASD and 145 controls. Controls consistently evaluated high-quality artworks to be much better quality than the low-quality artworks, reflecting intuitive processing. The ASD sample showed a reduced difference in evaluations between high- versus low-quality artwork, which reflects reduced intuitive processing and greater deliberative processing and is consistent with predictions by the Dual Process Theory of Autism.
... In this study we try to examine the possibility of innate randomness. As far as decision making is concerned, ASD individuals are faced with difficulties, and are generally slower in taking decision and show less intuitive and more deliberate reasoning (Brosnan et al., 2014;Farmer et al., 2017;Luke et al., 2012;Vella et al., 2018).To account for those characteristics of ASD and based on experimental knowledge, De Martino proposed a model according to which individuals with ASD would more heavily rely on system 2 when taking decisions (De Martino et al., 2008). ...
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Introduction. The fast, intuitive and autonomous system 1 along with the slow, analytical and more logical system 2 constitute the dual system processing model of decision making. Whether acting independently or influencing each other both systems would, to an extend, rely on randomness in order to reach a decision. The role of randomness however, would be more pronounced when arbitrary choices need to be made, typically engaging system 1. The present study aims to examine arbitrary decision making in high functioning ASD individuals, focusing on system 1 focusing on the expression of innate randomness. Methods. High function ASD participants (36 adults, 33 male) and age and gender matched neurotypicals (40 adults, 33 male) performed the random number generation task. The task was modified in order to limit the contribution of working memory and allow any innate randomness mechanisms expressed through system 1 to emerge. Results. The random number sequences produced by ASD individuals and neurotypicals did not differ in their randomness characteristics and no significant differences were identified when the sequences were examined using a moving window approach. When machine learning was used there were more than one combinations of variables that could discriminate the groups with a very high accuracy rate. Conclusions. Our findings indicate that individual patterns during random sequence production are consistent enough between groups to allow for an accurate discrimination between the ASD group and neurotypicals.
... De acuerdo con Freling et al. (2014) congruencia entre la apelación del mensaje y el destinatario del mensaje y no es simplemente una cuestión de la valencia del estímulo/mensaje utilizado. Según los resultados, la visualización de anuncios con texto negativo activa más rápidamente el sistema emocional, provocando una mayor excitación fisiológica (De Martino et al., 2008) y una respuesta conductual, en línea con Vining y Ebreo (2002). Esta activación podría explicar la rápida atención prestada a la amenaza indicada por el texto. ...
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Wien, Med. F., Hab.-Schr., 1943 (Nicht f. d. Austausch).