The Decimal Effect: Behavioral and Neural Bases for

The Decimal Effect: Behavioral and Neural Bases for
a Novel Influence on Intertemporal Choice in
Healthy Individuals and in ADHD

Catherine Fassbender1, Sebastien Houde2, Shayla Silver-Balbus2,
Kacey Ballard2, Bokyung Kim2, Kyle J. Rutledge1, J. Faye Dixon1,
Ana-Maria Iosif 3, Julie B. Schweitzer1, and Samuel M. McClure2

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

Astratto

■ We identify a novel contextual variable that alters the evalu-
ation of delayed rewards in healthy participants and those diag-
nosed with attention deficit/ hyperactivity disorder (ADHD).
When intertemporal choices are constructed of monetary out-
comes with rounded values (per esempio., $25.00), discount rates are greater than when the rewards have nonzero decimal values (per esempio., $25.12). This finding is well explained within a dual sys-
tem framework for temporal discounting in which preferences
are constructed from separate affective and deliberative pro-
cesses. Specifically, we find that round dollar values produce
greater positive affect than do nonzero decimal values. Questo

suggests that relative involvement of affective processes may
underlie our observed difference in intertemporal preferences.
Inoltre, we demonstrate that intertemporal choices with
rounded values recruit greater brain responses in the nucleus
accumbens to a degree that correlates with the size of the be-
havioral effect across participants. Our demonstration that a
simple contextual manipulation can alter self-control in ADHD
has implications for treatment of individuals with disorders of
impulsivity. Overall, the decimal effect highlights mechanisms
by which the properties of a reward bias perceived value and
consequent preferences.

INTRODUCTION

Problems with self-control are some of the most detrimen-
tal for individuals as well as society, with obesity, excessive
debt, and substance abuse representing major health and
economic concerns (Madden & Bickel, 2009; Reynolds,
Leraas, Collins, & Melanko, 2009; Madden, Petry, Badger,
& Bickel, 1997). These issues all have one feature in com-
mon: People opt for more immediately rewarding options
and undervalue future benefits to their overall detriment.
To understand such phenomena, research has posited
that future outcomes are evaluated using hyperbolic or
quasihyperbolic discount functions, which effectively de-
scribe the tendency to overvalue immediate rewards
(Frederick, Loewenstein, & OʼDohoghue, 2002). In these
functions, value rapidly decreases as rewards are delayed
from the present and decreases more slowly as rewards
are delayed from future times.

The discount rate expressed in hyperbolic discounting
is the critical factor determining relative preferences for
immediate rewards. Discount rates depend on a wide
variety of contextual and personal variables, such as the
nature of the reward, its modality (McClure, Ericson,

1University of California Davis Medical Center, 2Stanford University,
3University of California Davis

© 2014 Istituto di Tecnologia del Massachussetts

Laibson, Loewenstein, & Cohen, 2007; Bickel & Marsch,
2001), its magnitude (Verde, Myerson, & McFadden,
1997; Thaler, 1981), and even the scent in the experi-
mental room (Li, 2008). Individual factors that predict
differences in delay discounting include age (Steinberg,
2010; Sozou & Seymour, 2003; Verde, Fry, & Myerson,
1994), health (Chao, Szrek, Pereira, & Pauly, 2009), informazioni-
ligence (Shamosh et al., 2008), and some psychiatric dis-
orders (Ahn et al., 2011; Heerey, Robinson, McMahon, &
Gold, 2007). Peters and Büchel (2011) refer to these de-
pendencies as trait (immutable, per esempio., person-related) E
state (mutable, framing/context) factors that affect dis-
counting rates. The prototypical disorder associated with
greater discounting and poor self-control is attention
deficit/hyperactivity disorder (ADHD; Marco et al., 2009;
Paloyelis, Asherson, & Kuntsi, 2009; Tripp & Alsop, 1999;
Schweitzer & Sulzer-Azaroff, 1988, 1995; Rapport, Tucker,
DuPaul, Merlo, & Stoner, 1986).

Process theories of temporal discounting propose a
dual system model of decision-making to begin to capture
the many influences on relative preferences for immediate
reward (van den Bos & McClure, 2013). The first system is
posited to be myopic in nature and is linked to positive
emotional reactions to rewards. We use the term “affec-
tive” to represent this system (Loewenstein, 1996), Quale
is thought to be subserved by brain areas including the

Journal of Cognitive Neuroscience 26:11, pag. 2455–2468
doi:10.1162/jocn_a_00642

l

l

/

/

/

/
j

T
T

F
/

io
T
.

:
/
/

H
T
T
P
:
/
D
/
o
M
w
io
N
T
o
P
UN
R
D
C
e
.
D
S
F
io
R
o
l
M
v
e
H
R
C
P
H
UN
D
io
io
R
R
e
.
C
C
T
.
o
M
M
/
j
e
o
D
tu
C
N
o
/
C
UN
N
R
UN
T
R
io
T
io
C
C
l
e
e

P

D
P
D
2
F
6
/
1
2
1
6
/
2
1
4
1
5
/
5
2
1
4
9
5
4
5
7
/
9
1
5
7
7
8
o
2
C
0
N
6
_
2
UN
/
_
j
0
o
0
C
6
N
4
2
_
UN
P
_
D
0
0
B
6

4
G
2
tu
.
e
P
S
T
D
o
F
N
B
0

7
S
M
e
IO
P
T
e
M
l
io
B
B
e
R
R
UN
2
R
0
2
io
3
e
S

/
j

F

T

.

/

tu
S
e
R

o
N

1
7

M
UN

2
0
2
1

nucleus accumbens (NAcc) in the ventral striatum, IL
ventromedial pFC (vmPFC), and other areas involved in
evaluating rewards (Kable & Glimcher, 2007; McClure
et al., 2007; McClure, Laibson, Loewenstein, & Cohen,
2004). These brain reward regions have been linked to
affective responses (Knutson & Greer, 2008; Panksepp,
2004) and are thought to signal reward value in a stereo-
typed manner acquired through associative learning (Daw,
Niv, & Dayan, 2005; Schultz, Dayan, & Montague, 1997).
The second process is hypothesized to be far sighted
in nature, slow and rule-based in response, but flexible
enough to adaptively control behavior. We refer to this
as the “deliberative” system. It is thought to be subserved
by the dorsolateral pFC (dlPFC) and posterior parietal
cortex (pPC; McClure et al., 2004, 2007).

Here we explore a novel effect on temporal discount-
ing that appears to arise from differences in affective
responses to reward prospects. The effect results from
changing a seemingly innocuous feature of offered mone-
tary rewards. Specifically, within-subject discount rates dif-
fer when choices are constructed from monetary rewards
with rounded decimal values (per esempio., $25.00) or numbers with nonzero decimal value (per esempio., $25.12). Individuals tend
to choose more impulsively when the choice is consti-
tuted of monetary rewards that are rounded numbers.
We refer to this as the decimal effect. As rounded decimal
amounts ($25.00) are more common in daily experience than are nonzero decimal values ($25.12; con .99 a pos-
sible exception), we speculate that this effect may result
from greater familiarity and hence perceptual fluency
with rounded dollar values (cf. Oppenheimer & Frank,
2008; Alter & Oppenheimer, 2006). Our primary aim is
to provide a process account of the decimal effect. On
the basis of data from several experiments, we will argue
that nonzero decimal values in monetary rewards influ-
ence affective responses to the rewards and consequently
influence how individuals trade off present for delayed
ricompense.

Our first study, Experiment 1, demonstrates the deci-
mal effect. In Experiment 2, we show behavioral evidence
that the decimal effect is related to increased positive af-
fect to rounded monetary rewards. In Experiment 3, we
provide fMRI evidence to support our main conclusions.
In Experiment 4, we provide an extension of the decimal
effect, testing whether rounded values have the ability to
increase the value of delayed rewards. Our final study,
Experiment 5, examines the decimal effect across a wide
developmental period between typically developing con-
trols and participants with ADHD.

EXPERIMENT 1

Affective processes may signal value in an automatic,
stereotyped manner that is slowly acquired through ex-
perience. We hypothesized that differential experience
with monetary rewards with rounded values relative
to nonzero decimal values may bias how the rewards

are processed by facilitating automatic responses and
consequently influencing intertemporal preferences
(Butterworth, 1999). We tested this prediction in our first
experiment.

Methods

Participants

We recruited 28 participants; 12 at Stanford University
(eight men, mean age = 20.26 years, range = 18–22 years)
E 16 from Baylor College of Medicine and the greater
Houston area community (10 men, mean age = 26.38 years,
range = 20–36 years). (See Table 1 for inclusion/exclusion
criteria for all studies and Table 2 for demographic data
for Experiments 1–4.) We excluded one participant from
each site because they failed to submit choices on all
trials. Participants from Baylor College of Medicine com-
pleted the task while undergoing fMRI scanning (Vedere
Experiment 3).

Materials

Each participant was presented with 62 intertemporal
choices offering an immediate reward and a larger but
delayed reward. For half of the choice trials, rewards had
rounded decimal values (per esempio., $11.00 today or $21.00 In
6 weeks; rounded condition). The other half had only
nonzero decimal values (per esempio., $10.87 today or $20.74 In
6 weeks; decimal condition). We omitted decimal values
Di .25, .50, .75, E .99, as these are common numbers
and may have intermediate effects between our rounded
and nonzero decimal values. Trials were presented in
random order.

The choice trials were derived from the hyperbolic dis-
counting function (Mazur, 1987) that models subjective
value as a function of delay according to the function,

V ¼ r

1 þ kd

;

ð1Þ

where r is the magnitude of the reward, d is the delay
until receipt, and V is the discounted value. For each
trial, a unique discount rate, keq, implies indifference
between the immediate reward and the discounted, Di-
layed reward. Choices were constructed so that each trial
in the rounded condition matched a trial in the decimal
condition with an equal discount rate (keq) and delay. For
the rounded value rewards, magnitudes spanned a range
Di $2 A $33; nonzero decimal values ranged from $2.14 A $32.90. Delayed rewards were available between 7 E
56 days in the future (in 7-day increments). Reward mag-
nitudes could not be exactly equated; così, half of the
decimal values were slightly larger and the other half
slightly smaller than their rounded pairs. As it was not pos-
sible to make the average magnitudes exactly the same,
decimal values were on average 18¢ (±$1.33) smaller than rounded values. This design ensured that both conditions 2456 Journal of Cognitive Neuroscience Volume 26, Numero 11 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e – P – d p d 2 F 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 C 0 N 6 _ 2 UN / _ j 0 o 0 C 6 N 4 2 _ a p _ d 0 0 B 6 sì 4 G 2 tu . e p s t d o f n b 0 sì 7 S M e I p T e m L i b b e r r a 2 R 0 2 io 3 e s / j . / f t u s e r o n 1 7 M a y 2 0 2 1 Tavolo 1. Inclusion/Exclusion Criteria for All Experiments Group Inclusion Criteria HC Exclusion Criteria Ages 18–50 Experiments 1–4 HC Clinical history of neurological, major medical or psychiatric disorder fMRI contraindicationsa Inclusion Criteria HC and ADHD Ages 12–30 IQ over 80 as per WASI Experiment 5 HC HC ADHD ADHD ADHD Exclusion Criteria HC and ADHD HC and ADHD HC HCa HC = healthy control. aExclusion for Experiment 3. t score of 60 or lower on the total DSM total ADHD score 3 or more inattentive and 3 or more hyperactive/impulsive DSM symptoms t score of 65 or higher on the total DSM total ADHD score 6 or more inattentive and 6 or more hyperactive/impulsive DSM symptoms Significant symptoms before age 7 and across at least two domains (per esempio., home and school/work) Any Axis 1 disorder except for ADHD in the ADHD group Clinical history of neurological, major medical of psychiatric disorder History of treatment with psychoactive medication fMRI contraindications spanned the same range of intertemporal trade-offs, while controlling for any bias because of differences in reward magnitude (Thaler, 1981). Procedure Participants had unlimited time on each trial to make their choice. UN 2000 msec blank intertrial interval was Table 2. Demographic and Clinical Characteristics for Participants in Experiments 1–4 Experiment Group Age Age Range Gender (male) N 1 2 3 4 HC HC HC HC 22.4 29.5 26.1 35.5 18–36 19–50 20–36 19–45 17 19 9 92 42 40 16 183 Data are summarized as mean for the continuous variables. used (see Figure 1A). IL 62 trials were split into four blocks of either 15 O 16 trials, with one 15 trial and one 16 trial block for both the rounded and decimal conditions. Block order was counterbalanced according to condition, with half of participants beginning with rounded and ending with decimal trials. Trial order within each block was randomly generated. We used a lottery system in which one of the partici- pantʼs choices was randomly selected and paid to the par- ticipant according to the amount and delay of the selected choice. Participants were instructed to consider each choice seriously as any one could potentially be paid according to their selection. This encouraged participants to remain focused throughout the experiment and to treat all trials as equally determinant of their overall earnings. Estimation of Discount Rates For each participant and condition, discount rates were estimated by maximum likelihood. Participantsʼ binary Fassbender et al. 2457 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e – P – d p d 2 F 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 C 0 N 6 _ 2 UN / _ j 0 o 0 C 6 N 4 2 _ a p _ d 0 0 B 6 sì 4 G 2 tu . e p s t d o f n b 0 sì 7 S M e I p T e m L i b b e r r a 2 R 0 2 io 3 e s / j f . / t u s e r o n 1 7 M a y 2 0 2 1 rithm. This yields condition-specific estimates for k and m. The standard errors of the estimates were obtained by invoking the asymptotic normality of the maximum likelihood estimators. Results Choices revealed the decimal effect: Participants made more impulsive decisions in the rounded relative to the decimal condition. We performed analyses on log- transformed discount rates using nonparametric tests because the distributions of log(k) were nonnormal (Kolmogorov–Smirnov tests, P < .001 for both decimal and rounded conditions). The decimal effect held among 22 of our 26 participants (see Figure 1B). Moreover, discount rates in both the decimal and rounded condi- tions were not significantly different across participants recruited from Stanford University and Baylor College of Medicine ( Wilcoxon rank sum test; p > .24 comparing discount rates in rounded and decimal conditions). We therefore analyzed data collectively across these two groups. Comparing the estimated discount rates across conditions within participants, the mean of the differences between the log-discount rates in the rounded versus deci- mal conditions is positive (0.27) and significantly different from zero (sign test, P < .001). We ruled out two potential confounds associated with the decimal effect. First, we found no difference in RT between the two conditions (mean RT rounded = 3273.04 msec; mean RT decimal = 3088.59; mean rounded − decimal = 184.45 msec, SE 138.59, t(25) = 1.28, p > .20). Secondo, choice consistency was not influenced by task condition. Comparing m values indicated no significant difference (Wilcoxon signed rank test p = .67). Likewise, fitted k values predicted an average of 90.12% E 88.34% of choices in the decimal and rounded conditions, rispettivamente (Wilcoxon signed rank test, p = .17). Reward magnitude is also known to influence discount rates (per esempio., Thaler, 1981). To rule out an influence of mag- nitude on our results, we split choices (by median) into low- and high-magnitude trials, collapsing across decimal conditions. We then estimated k separately for low- and high-magnitude choices per participant. We performed a sign test on the difference in log(k) values across mag- nitudes and found no significant difference ( p = .33). Discussion Consistent with our hypothesis, we found that the nature of the decimal values in monetary rewards influenced intertemporal preferences. We suggested that monetary re- wards containing rounded values would be more percep- tually fluent and therefore trigger affective valuation processes to a greater degree than would nonzero decimal values. As affective processes are thought to be myopic in nature (Loewenstein, 1996), this would account for our observed differences in discount rates. Figura 1. (UN) Intertemporal choices for monetary outcomes with nonzero and rounded decimal values elicit different temporal discount rates. (B) Discount rates are consistently higher for rounded dollar values across participants, producing a robust mean decimal effect. choices between the immediate and delayed rewards were modeled with the exponential version of the Luce choice model (Luce, 2005). If we summarize the sub- jective value of the two alternatives as V1 and V2 for the immediate and delayed rewards, rispettivamente, then the probability of choosing the immediate outcome for an arbitrary k is given by PðChoose V1Þ ¼ ð1 þ expð−mVΔðkÞÞ−1 ð2Þ where VΔ(k) is the difference V1 − V2 for some value of k. Likewise, the probability of choosing the delayed outcome is equal to 1 − P(Choose V1). The parameter m cap- tures how consistent choices are with the fitted discount function. The likelihood of any set of choices per participant is the product of the probability for each observed choice. For each condition (C), we form the likelihood function, Lcðm; kÞ ¼ YS YN s¼1 i¼1 Pi;sðChoose V1Þ J ð1 − Pi;sðChoose V1ÞÞ1−J ð3Þ where J = 1 if the immediate reward is chosen and zero otherwise. We maximized Equation 3 with respect to k and m using a simulated annealing optimization algo- 2458 Journal of Cognitive Neuroscience Volume 26, Numero 11 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e – P – d p d 2 F 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 C 0 N 6 _ 2 UN / _ j 0 o 0 C 6 N 4 2 _ a p _ d 0 0 B 6 sì 4 G 2 tu . e p s t d o f n b 0 sì 7 S M e I p T e m L i b b e r r a 2 R 0 2 io 3 e s / j . T / f u s e r o n 1 7 M a y 2 0 2 1 p ffiffiffi as our primary variable of interest (PA ¼ ðv þ aÞ= ; based 2 on Knutson & Greer, 2008). A two-way, within-subject ANOVA was conducted to compare the main effects of (1) condition (rounded vs. decimal values) E (2) reward magnitude for participantsʼ affect ratings for rewards. We found greater PA for rounded values with a significant main effect of condition, F(1, 38) = 5.48, p = .03. We also found a significant main effect of reward magnitude on PA ratings, F(4, 38) = 29.82, P < .001, with larger values eliciting more positive ratings. These results are shown in Figure 2, where we have plotted normalized ratings (z score corrected within participants across conditions) as a function of re- ward amount. The interaction between condition and reward magnitude was not significant ( p = .18). Similar results held when valence or arousal were analyzed using similar ANOVAs. For valence, there was a main effect of amount, F(4, 38) = 30.50, p < .001, and condition, F(1, 38) = 4.98, p = .03, but no significant interaction ( p = .38). For arousal, there was a main effect of amount, F(4, 38) = 23.96, p < .001, and a trend for condition, F(1, 38) = 3.43, p = .07, with no significant interaction ( p = .23). Because of the large age range in our participants, we conducted additional ANOVA analyses looking for a main effect of age (split into quartiles) or an Age × Reward mag- nitude interaction. We found no significant differences on the basis of participantsʼ age ( p > .46 for both analyses). Discussion These results suggest that participants feel more positive arousal for monetary rewards with rounded compared EXPERIMENT 2 Experiment 2 tested the hypothesis that rounded dollar values differ from nonzero decimal values on the basis of affective response. We primed affective processes by ask- ing participants to rate their emotional reaction (Hsee & Rottenstreich, 2004) to the prospect of winning different amounts of money to determine how rounded and non- rounded monetary rewards are evaluated using emotion- ally based valuation. We manipulated decimal values while holding magnitude comparable. We hypothesized that if valuation of round numbers involves more affec- tive processing, round numbers would generate greater positive affect than comparable nonzero decimal num- bers. The alternative hypothesis is that affective pro- cesses are unaffected by decimal value, in which case affect ratings between rounded and nonzero decimal values should not differ. Methods Participants A total of 54 volunteers were recruited (25 men; mean age = 28.8 years) from the Stanford community and gave written informed consent to participate. Because of a technical error in conducting the experiment, 14 partici- pants did not complete all of the ratings and thus were excluded, in partenza 40 participants for analyses. Materials and Procedure In accordance with the two-dimensional affective circum- plex model of emotion (Watson, Wiese, Vaidy, & Tellegen, 1999; Watson & Tellegen, 1985), we separately assessed valence and arousal to measure the subjective emotional impact of rounded versus decimal monetary rewards. Par- ticipants received an online questionnaire, asking them to make subjective assessments of 10 monetary rewards, five rounded and five with nonzero decimal values. Each rounded reward was matched to a decimal reward; in each pair, the rounded number had a smaller objective value. Each of the 10 numbers was presented in a random order, and participants were asked the following questions: Imagine you have the chance to win $25.00.
How Positive or Negative would you feel?
How Activated/Aroused would you feel?

Participants answered the questions using sliding scales
numbered from 0 A 100 and anchored to 50 on presen-
tation of the question.

Results

As valence (v) and arousal (UN) ratings were significantly
correlated in our data (r2 = .54, P < .0001), we combined these measures on a single dimension of positive arousal Figure 2. Positive arousal reported for the prospect of earning a rounded dollar amount was larger than that reported for nonzero decimal values or marginally greater objective value. Data have been normalized within participants (z score transformed); error bars are standard errors of the mean. Fassbender et al. 2459 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 c 0 n 6 _ 2 a / _ j 0 o 0 c 6 n 4 2 _ a p _ d 0 0 b 6 y 4 g 2 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f / . t u s e r o n 1 7 M a y 2 0 2 1 with those with nonzero decimal values. Not surprisingly, they also reported feeling more positive arousal for greater magnitudes of monetary rewards. Importantly, this differential affective response overcomes the fact that rounded values were smaller in objective value. EXPERIMENT 3 Properties linked to affective and deliberative processes distinguish the functions of the NAcc and dlPFC in inter- temporal choice (Peters & Büchel, 2011; McClure et al., 2004). Affective responses to rewards and related NAcc activity predict individual discount rates (Hariri et al., 2006). Cognitive ability correlates with dlPFC activity and lower discount rates (Shamosh & Gray, 2008; Shamosh et al., 2008). Furthermore, manipulating these systems either pharmacologically (Pine, Shiner, Seymour, & Dolan, 2010) or by direct stimulation (Figner et al., 2010) alters discount rates in the expected directions. In this study, we measure correlates of affective and deliberative pro- cessing while participants make intertemporal choices containing rounded or nonzero decimal values. Given the results from Experiment 2, we conjectured that rounded values would more effectively recruit the NAcc than would nonzero decimal values. fMRI also allows us to test whether rounded and decimal values differentially recruit deliberative processes by measuring activity in the dlPFC and pPC. Methods Participants Out of 28 participants in Experiment 1, the 16 participants from Baylor College of Medicine performed the task while undergoing fMRI scanning. The two participants excluded from the analysis in Experiment 1 were from this group of 16. Materials and Procedure: Behavioral Task Experimental materials and procedures were similar to Experiment 1, except that a 12-sec intertrial interval was included to accommodate the BOLD signal. Participants were paid as in Experiment 1 plus $20 base pay for the fMRI. fMRI Study Procedure Brain images were acquired using a 3-T Siemens Trio MR Scanner at Baylor College of Medicine. A high-resolution (1 × 1 × 1 mm3) T1-weighted anatomical image was first acquired. For functional images, T2-weighted EPIs were acquired (repetition time = 2 sec, echo time = 30 msec, flip angle = 90°; data acquired approx. 30° off the AC–PC line, 37 slices with 2 mm gap, 64 × 64 matrix, 3.0 mm3 isotropic voxels). Data preprocessing and linear regressions were conducted with SPM5. ROI analysis was performed with AFNI using spherical masks of 12 mm diameter. Preprocessing included slice-time correction, realignment, spatial normalization, and smoothing with an 8 mm FWHM Gaussian kernel. Volumes were normal- ized to the Montreal Neurological Institute template and resampled at 4 × 4 × 4 mm3 isotropic resolution. Whole-brain general linear model analyses fit hemo- dynamic responses with a boxcar activation function with RT indicating trial duration and onset given by choice presentation onset. Differences in RTs across choices were thus explicitly modeled. Movement parameters were modeled as covariates of no interest. Results Given that trials in the two conditions were paired, a subtraction of the mean brain response across the two con- ditions reveals the difference in brain activity in rounded versus decimal value choices. One confound with this subtraction is that choices themselves are different and may affect brain activity. We controlled for choice in two ways. Linear models were fit with a nuisance regressor that indicated the choice outcome (immediate or delayed reward). We also conducted hierarchical analyses where a linear model was first fit for choice outcome alone. The fitted choice-related responses were then subtracted from the original data and the residual signals were subjected to a linear model to fit average responses in rounded and decimal trials. Because the two approaches yielded qualitatively identical results, we only present the results with choice included as a nuisance regressor in this discussion. Two separate analyses were conducted to examine the effect of nonzero decimal versus rounded numbers on brain activity in intertemporal choice. First, an omnibus general linear model analysis was performed on the whole brain, coregistered data. This analysis revealed three brain regions that had significantly greater activity in the rounded relative to the decimal condition ( p < .05, corrected for multiple comparisons by false discovery rate). We omit from further discussion one region identified in the right ventrolateral temporal lobe that has not previously been associated with reward processing (peak Montreal Neuro- logical Institute coordinates −60, −56, −4). The other two regions were in the left and right NAcc (Figure 3A; 20, 10, −12 and −16, 10, −12, respectively). Second, we created individual masks on nonnormal- ized data to select the bilateral NAcc and directly analyzed the average activity within this anatomical region. The ROI analysis from subject-specific NAcc confirmed the results of the whole-brain analysis. The difference in NAcc activity measured across participants correlated with the size of the behavioral decimal effect (i.e., Δlog(k) = log(kround) − log(kdecimal)). Participants with greater NAcc activity in the rounded compared with the decimal 2460 Journal of Cognitive Neuroscience Volume 26, Number 11 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 c 0 n 6 _ 2 a / _ j 0 o 0 c 6 n 4 2 _ a p _ d 0 0 b 6 y 4 g 2 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t / . f u s e r o n 1 7 M a y 2 0 2 1 Figure 3. (A) Whole-brain analyses indicate that, on average, the NAcc (bilaterally) is more activated as participants make intertemporal choices with rounded values compared with choices with nonzero decimal values. (B) The NAcc was identified in individual participants using anatomical MRI images. Mean event-related responses in the bilateral NAcc correlated with the size of the decimal effect across individuals (Δlog(k) = log(kround) − log(kdecimal)). condition showed larger increases in discounting rates in the rounded compared with the decimal condition (see Figure 3B; r = 0.74, p = .002). The result holds when omitting the outlier participant at the top right of the plot (r = 0.62, p = .02) and when performing a robust regression ( p = .002). Finally, we had an a priori interest in the dlPFC and pPC given previous work (Figner et al., 2010; Hare, Camerer, & Rangel, 2009; McClure et al., 2004, 2007). No regions in either the dlPFC or pPC were significant in our whole- brain analyses, even at the liberal threshold of p < .1. We therefore specifically looked at average activity in ROIs of 12 mm diameter spheres based on regions identified in previous studies (dlPFC: McClure et al., 2004, 44, 44, 16, and Hare et al., 2009, −48, 15, 24; pPC: McClure et al., 2004, −8, −28, 32). There were no significant differences in rounded minus decimal values for any of these locations (dlPFC: p = .45 and .37, respectively; pPC: p = .55). Furthermore, the trend was for greater dlPFC and pPC activation for choices involving rounded numbers whereas the prediction from behavior would be less activation for rounded compared with nonzero decimal values. Finally, other brain areas were of a priori interest be- cause they have been implicated in reward processing in other studies. Thus ROI analyses were conducted on the vmPFC, amygdala, and hippocampus. The vmPFC is commonly identified in fMRI studies of temporal discount- ing (see Peters & Büchel, 2010, for a review; ROIs from McClure et al., 2004, 0, 44, 12; Hare et al., 2009, 3, 36, −12). Likewise, the amygdala has been implicated in reward pro- cessing (ROI from Knutson, Adams, Fong, & Hommer, 2001) and the hippocampus is implicated in evaluating stim- uli (ROI from Wimmer & Shohamy, 2012). We found no sig- nificant difference between conditions at either of the vmPFC locations ( p > .35 for responses averaged over 12-mm-diameter spheres centered at the indicated loca- zioni). Similarly we found no significant differences in the hippocampus ( p = .22) or in the amygdala ( p = .31). In these latter two regions, the trend was toward greater activ- ity for choices involving decimal values relative to rounded values, contrary to our findings for the ventral striatum. Discussion Our prediction from examining choices between monetary outcomes was that intertemporal choices with rounded values would preferentially recruit brain reward areas, particularly the NAcc. This prediction was supported by the further finding that the degree of activity in the NAcc correlated with individual differences in the decimal effect. “Affective” and “deliberative” modes of valuation are constructs intended to capture aspects of behavior. Al- though there is certainly a link between the properties of these constructs and the function of the NAcc, dlPFC, and pPC, there are substantial differences as well (van den Bos & McClure, 2013). Nonetheless, fMRI allowed us to test for differential involvement of functionally disparate brain systems during intertemporal choices. We confirmed that the affect-related NAcc is differentially recruited during presentation of rounded values. Inoltre, we find no evidence of differential recruitment of brain areas asso- ciated with deliberative processes. Conclusions from this latter finding should be tempered by acknowledging limit- ed power (especially when asserting a null hypothesis); fMRI has relatively low signal-to-noise ratio. Additionally, the dlPFC and pPC are large brain regions whose organiza- tion is not well understood. We found no difference in activity in either of these cortical areas even at very liberal statistical thresholds, but additional work is necessary to confirm this finding. The vmPFC may integrate multiple influences contribut- ing to total subjective value (Rangel & Hare, 2010). The vmPFC receives (primarily indirect) inputs from both the NAcc and dlPFC (Hare et al., 2009) and activity in the vmPFC correlates with time-discounted value (Kable & Glimcher, 2007). Here, the vmPFC displayed a subtle dependence on rounded values in the subgenual cingu- late cortex near that area associated with subjective value Fassbender et al. 2461 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e – P – d p d 2 F 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 C 0 N 6 _ 2 UN / _ j 0 o 0 C 6 N 4 2 _ a p _ d 0 0 B 6 sì 4 G 2 tu . e p s t d o f n b 0 sì 7 S M e I p T e m L i b b e r r a 2 R 0 2 io 3 e s / j / t f . u s e r o n 1 7 M a y 2 0 2 1 (Rangel & Hare, 2010). Tuttavia, the effect in the vmPFC was notably weaker than in the NAcc, suggesting that the decimal value influences temporal discounting by in- fluencing the type of primary motivations represented in the NAcc. EXPERIMENT 4 In Experiment 1, we demonstrated that participants were more likely to choose a larger, delayed over a smaller sooner reward when presented with nonzero decimal values. In Experiment 2 we established that participants did not feel as positively aroused to nonzero decimal values compared with rounded values. Therefore, it may be that the decimal effect arises from preferential affective responses to monetary rewards with rounded values. This effect may act in concert with the myopia generally assumed for the affective system in intertemporal choice to increase discount rates. The NAcc is preferentially ac- tivated by immediate rewards but also maintains some response to delayed outcomes (Kable & Glimcher, 2007; McClure et al., 2004). Allo stesso modo, emotional responses are generally far greater to immediate overdelayed outcomes (Loewenstein, 1996), but delayed rewards still induce positive affect. This raises the question of whether cou- pling rounded values to delayed rewards can enhance an otherwise diminished affective response to the benefit of more far-sighted decision-making. In Experiment 4, we test this idea by crossing decimal value (rounded vs. nonzero decimal) with time (immediate vs. delayed). Methods Participants We recruited a total of 200 participants using Amazonʼs Mechanical Turk. Participants were restricted to be na- tive English speakers and to reside in the United States. We obtained informed consent before participants com- pleted the task. We excluded 17 participants because they selected all smaller, sooner or larger, later choices. This left 183 eligible participants (92 men; mean age = 35.52 years). Participants were randomly assigned to one of two con- ditions, the rounded-immediate (n = 91) or the rounded- delayed condition (n = 92). Materials and Procedure All participants completed two temporal discounting ques- tionnaires, presented via computer, with hypothetical re- ward choices. Each question offered a choice between a particular amount of money today and a larger amount of money after a certain number of days. Participants were instructed to evaluate the questions as if they would actu- ally receive the amount of money at the time specified in the choice. Tuttavia, the choices were hypothetical in nature and did not influence payments. All participants completed the same control questionnaire, which con- sisted of the same choices as constituted the nonzero decimal choices in Experiment 1. Participants completed a second 31-item temporal discounting questionnaire that followed the same structure but differed slightly based on experimental condition. In the rounded-immediate con- dizione, all of the monetary rewards offered today were round numbers (ranging from $2.00 A $31.00), whereas the monetary rewards offered later had nonzero decimal values (ranging from $2.97 A $38.34). In the rounded- delayed condition, all of the monetary rewards offered later were round numbers (ranging from $2.00 A $32.00), whereas the monetary values offered immediately had nonzero decimal values (ranging from $1.34 A $31.09). As in Experiment 1, values for immediate amounts, delayed amounts, and delay length were calculated according to Equation 1 to be matched between conditions on dis- counting rate, keq, and to share similar reward magnitudes and delays. Delay lengths ranged from 7 A 56 days as in Experiment 1. The order of control and experimental questionnaires was counterbalanced between participants for both conditions and trials were presented in random order. Measures of temporal discounting were calculated by maximum likelihood as described for Experiment 1. Results Our dependent measure was the difference in the log- discount rates across experimental and control conditions. As the log-transformed values were not normally distrib- uted (Kolmogorov–Smirnov test for normality; P < .05 for both conditions), we performed nonparametric Wilcoxon signed rank tests. These analyses replicated our previous finding that immediately available rounded values increase discount rates ( p = .008; mean RT control = 3075.3 msec; mean RT rounded = 2735.2 msec; mean rounded − control = 340.1 msec, SE = 383.3 msec). However, we find no change in discounting with rounded-delayed outcomes ( p = .90; mean RT control = 2737.3 msec; mean RT rounded = 2684.6 msec; mean rounded − control = 52.7 msec, SE = 116.0 msec). A two-sided rank sum test indicates that the effect on discount rates was moderately greater for the rounded-immediate than the rounded- delayed condition ( p = .06). There was no difference in choice consistency across rounded-immediate and rounded- delayed conditions (rank sum test of m value estimates across rounded and control conditions, p = .54). Discussion This experiment demonstrates a close coupling between the influence of the affective impact of rewards on temporal discounting and immediacy. In particular, we find that changing decimal values only impacts intertemporal prefer- ences when the rounded value is available immediately. It is certainly possible that decimal value may influence the evaluation of delayed rewards and that this experiment 2462 Journal of Cognitive Neuroscience Volume 26, Number 11 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 c 0 n 6 _ 2 a / _ j 0 o 0 c 6 n 4 2 _ a p _ d 0 0 b 6 y 4 g 2 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t / . f u s e r o n 1 7 M a y 2 0 2 1 simply suffers from lack of power. Thus, we hesitate to conclude that rounded decimal values have no effect on delayed rewards—but instead believe that rounded values preferentially impact the evaluation of immediate outcomes. values would affect self-control choices in both control and ADHD groups. Moreover, we predicted that younger children, in general, would display less self-control, re- flected by a greater tendency to select the smaller, sooner rewards, than would older participants. EXPERIMENT 5 Temporal discounting is tempered by individual and ex- ternal contextual factors (van den Bos & McClure, 2013; Peters & Büchel, 2011). Individual factors that predict dif- ferences in behavior include age and the symptom domain of hyperactivity/impulsivity (Scheres & Hamaker, 2010; Scheres, Tontsch, Thoeny, & Kaczkurkin, 2010; Scheres, Lee, & Sumiya, 2008; Thorell, 2007). However, develop- mental findings in temporal discounting are inconsistent (Christakou, Brammer, & Rubia, 2011; Prencipe et al., 2010), perhaps because the age ranges studied tend to be wide and/or they do not systematically assess other contextual factors. Differential maturation rates of brain systems underlying decision-making may underlie chang- ing self-control across lifespan. Some of these regions (e.g., NAcc, vmPFC, and dlPFC) have also been linked to ADHD impairment (Costa Dias et al., 2013; Scheres, Milham, Knutson, & Castellanos, 2007; Dickstein, Bannon, Castellanos, & Milham, 2006). In this final experiment, we examined self-control across a crucial time of brain devel- opment where there are greater expectations for self- management (12–30 years). We hypothesized that decimal Methods Participants A group of 40 typically developing individuals and a group of 25 individuals diagnosed with ADHD, Combined Type (i.e., significant symptoms of inattention and hyperactivity/ impulsivity) were recruited through the UC Davis MIND Institute. All participants gave written informed consent or verbal assent in addition to written consent from a par- ent or guardian in the case of minors (see Table 3 for de- mographic and clinical information). We included 12 years old as our minimum age because children younger than 12 are less likely to be able to fully appreciate monetary value and conceptualize the temporal delays presented within the paradigm. Participants were randomly assigned to one of two presentation orders, the rounded condition first (n = 31) or the decimal condition first (n = 34). Materials and Procedure A similar set of intertemporal choices was presented to participants as in Experiment 1. As real rather than hypo- thetical rewards are thought to pose more of a challenge Table 3. Demographic and Clinical Characteristics for Participants in Experiment 5 ADHD (n = 25) Healthy Controls (n = 40) Total (n = 65) Demographic Characteristics Gender Female Male Age Age range Clinical Characteristics FSIQa Letter–Word Identification Scorea Math Calculation Scorea DSM Inattention Subscale Scoreb DSM Hyperactive-Impulsive Subscaleb 13 (52%) 12 (48%) 18.6 (5.7) 12–30 115.2 (14.3) 109.0 (12.1) 110.2 (12.5)* 79.3 (12.7)* 79.7 (12.8)* 17 (43%) 23 (58%) 17.6 (4.1) 12–28 117.3 (11.1) 110.6 (9.0) 117.0 (12.6)* 45.6 (6.4)* 45.3 (4.2)* 30 (46%) 35 (54%) 18.0 (4.8) 12–30 116.4 (12.4) 110.0 (10.3) 114.3 (12.9) 58.8 (19.0) 58.7 (18.9) Data are summarized as mean (SD) for the continuous variables and frequency (%) for gender. FSIQ = Full-scale Wechsler Abbreviated Scale of Intelligence. *Wilcoxon two-sample test p < .05. aFrequency missing in healthy control group = 2. bFrequency missing in healthy control group = 1. Fassbender et al. 2463 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 c 0 n 6 _ 2 a / _ j 0 o 0 c 6 n 4 2 _ a p _ d 0 0 b 6 y 4 g 2 u . e p s t d o f n b 0 y 7 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j / t f . u s e r o n 1 7 M a y 2 0 2 1 Table 4. Summary of Mixed Effects Model Examining the Relationship of Group, Condition, Age, and Gender to Delay Discounting Model Term Intercept Group (ADHD) Condition (nonzero decimal) Age Gender (female) Estimate (SE) p 0.054 (0.008) < .001 0.028 (0.011) −0.009 (0.003) −0.003 (0.001) −0.015 (0.011) .019 .004 .027 .161 to self-control in ADHD (Scheres et al., 2008), we em- ployed a lottery system as in Experiment 1. Each individ- ualʼs discount factor, k, was calculated as outlined above. Statistical analyses employed mixed effect models im- plemented in SAS Version 9.3. (using PROC MIXED), be- cause they accounted for the correlated structure of the data because of repeated measures of delay discounting within participant (i.e., rounded and decimal trial types). This approach accommodated three instances of missing data (data excluded due to participants uniformly choos- ing either the immediate or delayed rewards). The core model predicting k included main effects for group (ADHD and control), condition (rounded and nonzero decimal), terms for age and gender, and a random effect for individual. Model assumptions were validated both graphically and analytically (Table 4). Results The analysis revealed a main effect of group, F(1, 41.61) = 5.99, p = .02, with the ADHD group showing significantly greater discount rates (k) than the control group. There was also a main effect of condition, F(1, 60.52) = 8.82, p = .004, with participants displaying the decimal effect (greater impulsivity in the rounded condition; see Fig- ure 4). As predicted, age was also significantly related to delay discounting, with younger age associated with larger discount rates, F(1, 60.12) = 5.17, p = .03. There was neither a significant effect of gender on discount rates, F(1, 57.45) = 2.02, p = .16, nor a significant Group × Condition interaction ( p > .7). Discussion These results replicate our main finding that decimal values influence discount rates—even in those with elevated levels of impulsivity, such as ADHD. The tendency to favor immediately available rewards plays a central role in the de- lay aversion theory (Sonuga-Barke, Taylor, Sembi, & Smith, 1992) and the steeper and shorter delay-of-gratification gradient theory of ADHD (Sagvolden, Aase, Zeiner, & Berger, 1998). Our replication of the decimal effect in impulsive individuals is particularly significant for popula- tions who display a greater tendency to select immediate rewards, such as adolescents and individuals with sub- stance dependence (Madden & Bickel, 2009). Increased discounting is linked to poor health outcomes and re- duced academic achievement and occupational success (Golsteyn, Gronqvist, & Lindahl, 2013). Attempting to improve self-control in individuals with heightened im- pulsivity by altering reward perception would be a novel approach for reducing the negative outcomes associated with impulsivity. Treatment of ADHD and substance use disorders currently involves contingency management in which rewards are given for appropriate behavior (per esempio., Bickel et al., 2010; Barkley, 2006). Although the size and delay of the rewards are typically considered in developing a behavior plan, it has not been considered how to best frame or present rewards in these plans. Our findings sug- gest that future research should assess how framing effects could enhance the value of delayed rewards to increase self-control across conditions associated with impulsivity. D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e o d u c n o / c a n r a t r i t i c c l e e – P – d p d 2 F 6 / 1 2 1 6 / 2 1 4 1 5 / 5 2 1 4 9 5 4 5 7 / 9 1 5 7 7 8 o 2 C 0 N 6 _ 2 UN / _ j 0 o 0 C 6 N 4 2 _ a p _ d 0 0 B 6 sì 4 G 2 tu . e p s t d o f n b 0 sì 7 S M e I p T e m L i b b e r r a 2 R 0 2 io 3 e s / j f . T / u s e r o n 1 7 M a y 2 0 2 1 Figura 4. Rates of impulsive decision-making (k) on a delay-discounting task using real rewards are displayed for individuals with ADHD and typically developing controls across two different conditions. In both conditions, participants were presented with choices between a relatively small immediate monetary reward or a larger, delayed monetary reward. In the round number condition, monetary values were presented as a dollar amount only (per esempio., $5.00), whereas in the decimal number
condition, these values were presented as dollars and cents (per esempio., $5.03).
The ADHD group made more impulsive choices than the typically
developing control group overall, in that they chose the immediate
reward over the larger, delayed reward more often. Introduction of
the decimal condition reduced impulsivity in both the ADHD and
control groups, meaning that, in both groups, individuals tended to
choose the larger, delayed reward more often when the amount was
presented as dollars and cents rather than simply in dollars alone.

2464

Journal of Cognitive Neuroscience

Volume 26, Numero 11

We also replicate the finding that younger individuals
have higher discount rates than do older people, indepen-
dent of the presence or absence of ADHD (Steinberg et al.,
2009). Casey and colleagues (Casey, Duhoux, & Malter
Cohen, 2010; Casey, Jones, & Hare, 2008) propose that
an increase in risky behavior during adolescence is be-
cause of an imbalance between relatively more mature,
subcortical brain systems versus less mature functioning
in cortical regions linked to cognitive control. Studies sug-
gest impaired modulation of hyperactive reward-related
striatal regions by cognitive control regions (cioè., dlPFC)
in adolescence (Christakou et al., 2011; Van Leijenhorst
et al., 2010; Berns, Moore, & Capra, 2009; Galvan et al.,
2006). Brain regions linked to self-control and evaluation
of future outcomes (Galvan et al., 2006) mature later in
development (per esempio., Christakou et al., 2011; Cohen et al.,
2010; Olson et al., 2009). Optimal connectivity between
dlPFC and other regions (pPC, vmPFC) to support more
self-controlled behavior putatively occurs in adulthood
(Luna, 2009). Regions such as the NAcc, which have been
associated with more impulsive choices in Experiment 3,
have also been consistently implicated in ADHD impair-
menti (Hart, Radua, Nakao, Mataix-Cols, & Rubia, 2013;
Scheres et al., 2007).

GENERAL DISCUSSION

Emotional responses have long been hypothesized to
underlie the short-sighted behavior evident in choices
involving tempting immediate rewards (Loewenstein,
1996; Mischel, 1974). We identify a novel effect on delay
discounting consistent with this assertion: subtle features
of prospective rewards can change affective responses
and impatience.

A large number of effects influence how intertemporal
preferences are formed (van den Bos & McClure, 2013).
One potential unifying framework for understanding these
diverse influences may come from positing independent
neurocognitive systems that underlie the evaluation of
ricompense. We refer to one common dichotomy of such sys-
tems herein as affective and deliberative. We have shown
that such a framework can explain how a relatively in-
nocuous feature of an intertemporal choice, the numbers
following the decimal point, comes to influence discount-
ing. We combined behavioral and neural measures to test
how decimal values alter the affective responses that dis-
tinguish these two modes of valuation. Overall, we have
established a pathway whereby properties of a reward in-
fluence consequent discount rates. Although it is possible
that the decimal effect is better explained by other effects
such as subtle differences in sensory processing or cal-
culation of numerical differences between the rounded
and decimal conditions, we believe this is less likely. Noi
found no evidence in to support differences between
the rounded and decimal conditions in visual or sensory
brain regions nor in decision-related RTs.

It remains to be seen whether the dual system frame-
work will be sufficient to account for the number of factors
known to influence intertemporal preferences. For exam-
ple, people are more patient when the time of reward
outcomes is expressed as an exact date as opposed to
the duration of time from the present (Read, Frederick,
Orsel, & Rahman, 2005). A recent fMRI study has shown
that a similar manipulation, switching from delays to dates,
modulates dlPFC activity, consistent with dual system
theory (Peters & Büchel, 2010). Perhaps as interestingly,
the dual system framework suggests novel effects. IL
idea for the decimal effect arose from considering ways
in which we might modulate NAcc activity.

Positing two neurocognitive systems is almost certainly
an oversimplification of how intertemporal preferences
are actually constructed. The validity of dual system
models of discounting is a source of much debate in
the neuroscience literature (per esempio., Hare et al., 2009; Kable
& Glimcher, 2007). Nonetheless, such models have dis-
tinct advantages in accounting for numerous phenomena
in delay discounting (van den Bos & McClure, 2013). One
important future direction will be to relate dual system
models to construal level theory (Trope & Liberman,
2003). Recent work by Fujita and colleagues has shown
that priming people to think in broader, more abstract
terms (high-level construal) increases self-control (Fujita
& Han, 2009). It is intriguing to hypothesize that thinking
more abstractly depends on the dlPFC and priming this
neural system increases that self-control, but this is pure
speculation at this point. We also acknowledge that there
may be other plausible mechanisms than the dual pro-
cessing account or the familiarity of rounded numbers
that may explain the downstream effect of an increased
affective response to the rounded stimuli studied herein.
Tuttavia, our primary goal for this project was to docu-
ment the outcome of altered affective responses. Future
studies will attempt to determine the mechanism under-
lying the outcome.

The decimal effect also suggests one avenue for inter-
ventions aiming to ameliorate the effects of impulsivity.
Our approach represents a novel attempt to shift impul-
sive behavior in populations associated with poor self-
control by manipulating the choice context. ADHD is
associated with problematic functioning in brain networks
implicated in both cognitive (dlPFC/pPC) and affective/
reward (vmPFC/NAcc) processes (Fassbender & Schweitzer,
2006). Despite this, attempts to modify self-control in
ADHD and adolescents tend to focus on teaching delibera-
tive strategies (Dawson & Guare, 2010). It should be possible
to design choice environments in ways that decrease affec-
tive responses, reduce NAcc activity, and lead to more far-
sighted choices. This suggestion is very similar to Mischel
and colleaguesʼ demonstration that, thinking of the abstract,
physical qualities of a marshmallow increase onesʼ ability to
delay gratification and ultimately obtain more marshmallows
(Mischel & Baker, 1975). The findings here suggest the
neurobiological basis by which these framing effects may

Fassbender et al.

2465

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

l

l

/

/

/

/
j

F
/

T
T

io
T
.

:
/
/

H
T
T
P
:
/
D
/
o
M
w
io
N
T
o
P
UN
R
D
C
e
.
D
S
F
io
R
o
l
M
v
e
H
R
C
P
H
UN
D
io
io
R
R
e
.
C
C
T
.
o
M
M
/
j
e
o
D
tu
C
N
o
/
C
UN
N
R
UN
T
R
io
T
io
C
C
l
e
e

P

D
P
D
2
F
6
/
1
2
1
6
/
2
1
4
1
5
/
5
2
1
4
9
5
4
5
7
/
9
1
5
7
7
8
o
2
C
0
N
6
_
2
UN
/
_
j
0
o
0
C
6
N
4
2
_
UN
P
_
D
0
0
B
6

4
G
2
tu
.
e
P
S
T
D
o
F
N
B
0

7
S
M
e
IO
P
T
e
M
l
io
B
B
e
R
R
UN
2
R
0
2
io
3
e
S

/
j

T

/

.

F

tu
S
e
R

o
N

1
7

M
UN

2
0
2
1

function. It may also be that differential neural activity re-
lates to distinct symptom profiles in individuals with ADHD.
Per esempio, steeper discounting may be because of some
combination of heightened sensitivity to immediate re-
wards, problems with response inhibition, or an ineffective-
ness of future outcomes to influence current behavior.

Reprint requests should be sent to Samuel M. McClure, Depart-
ment of Psychology, Stanford University, 450 Serra Mall, Building
420, Stanford, CA 94305, or via e-mail: smcclure@stanford.edu.

REFERENCES

Ahn, W. Y., Rass, O., Fridberg, D. J., Bishara, UN. J., Forsyth, J. K.,
Breier, A., et al. (2011). Temporal discounting of rewards
in patients with bipolar disorder and schizophrenia.
Journal of Abnormal Psychology, 120, 911–921.
Alter, UN. L., & Oppenheimer, D. M. (2006). Predicting

short-term stock fluctuations by using processing fluency.
Proceedings of the National Academy of Sciences,
U.S.A., 103, 9369–9372.

Barkley, R. UN. (2006). Attention-deficit hyperactivity disorder.

A handbook for diagnosis and treatment (3rd ed.).
New York: The Guildford Press.

Berns, G. S., Moore, S., & Capra, C. M. (2009). Adolescent
engagement in dangerous behaviors is associated with
increased white matter maturity of frontal cortex.
PLoS One, 4, e6773.

Bickel, W. K., Jones, B. A., Landes, R. D., Christensen,

D. R., Jackson, L., & Mancino, M. (2010). Hypothetical
intertemporal choice and real economic behavior:
Delay discounting predicts voucher redemptions during
contingency-management procedures. Experimental
and Clinical Psychopharmacology, 18, 546–552.

Bickel, W. K., & Marsch, l. UN. (2001). Toward a behavioral
economic understanding of drug dependence: Delay
discounting processes. Addiction, 96, 73–86.

Butterworth, B. (1999). A head for figures. Scienza, 284, 928–929.
Casey, B. J., Duhoux, S., & Malter Cohen, M. (2010).
Adolescence: What do transmission, transition, E
translation have to do with it? Neuron, 67, 749–760.

Casey, B. J., Jones, R. M., & Hare, T. UN. (2008). IL

adolescent brain. Annals of the New York Academy
of Sciences, 1124, 111–126.

Chao, l. W., Szrek, H., Pereira, N. S., & Pauly, M. V. (2009).
Time preference and its relationship with age, health, E
survival probability. Judgment and Decision Making, 4,
1–19.

Christakou, A., Brammer, M., & Rubia, K. (2011). Maturation of
limbic corticostriatal activation and connectivity associated
with developmental changes in temporal discounting.
Neuroimage, 54, 1344–1354.

Cohen, J. R., Asarnow, R. F., Sabb, F. W., Bilder, R. M.,

Bookheimer, S. Y., Knowlton, B. J., et al. (2010). A unique
adolescent response to reward prediction errors. Nature
Neuroscience, 13, 669–671.

Costa Dias, T. G., Wilson, V. B., Bathula, D. R., Iyer, S. P.,
Mills, K. L., Thurlow, B. L., et al. (2013). Reward circuit
connectivity relates to delay discounting in children with
attention-deficit/hyperactivity disorder. European
Neuropsychopharmacology, 23, 33–45.

Daw, N. D., Niv, Y., & Dayan, P. (2005). Uncertainty-based
competition between prefrontal and dorsolateral striatal
systems for behavioral control. Nature Neuroscience, 8,
1704–1711.

Dawson, P., & Guare, R. (2010). Skills in children and
adolescents: A practical guide to assessment and
intervention (2nd ed.). New York: Guilford Press.

Dickstein, S. G., Bannon, K., Castellanos, F. X., & Milham,
M. P. (2006). The neural correlates of attention deficit
hyperactivity disorder: An ALE meta-analysis. Journal of
Child Psychology and Psychiatry, 47, 1051–1062.

Fassbender, C., & Schweitzer, J. B. (2006). Is there evidence
for neural compensation in attention deficit hyperactivity
disorder? A review of the functional neuroimaging literature.
Clinical Psychology Review, 26, 445–465.

Figner, B., Knoch, D., Johnson, E. J., Krosch, UN. R., Lisanby, S. H.,
Fehr, E., et al. (2010). Lateral prefrontal cortex and self-control
in intertemporal choice. Nature Neuroscience, 13, 538–539.

Frederick, S., Loewenstein, G., & OʼDohoghue, T. (2002).
Time discounting and time preference: A critical review.
Journal of Economic Literature, 40, 351–401.

Fujita, K., & Han, H. UN. (2009). Moving beyond deliberative

control of impulses: The effect of construal levels
on evaluative associations in self-control conflicts.
Psychological Science, 20, 799–804.

Galvan, A., Hare, T. A., Parra, C. E., Penn, J., Voss, H., Glover, G.,
et al. (2006). Earlier development of the accumbens relative
to orbitofrontal cortex might underlie risk-taking behavior
in adolescents. Journal of Neuroscience, 26, 6885–6892.
Golsteyn, B. H. H., Gronqvist, H., & Lindahl, l. (2013). Time
preferences and lifetime outcomes (No. 7165). Discussion
Paper Series. Forschungsinstitut zur Zukurift der Arbeit.
Verde, L., Fry, A., & Myerson, J. (1994). Discounting of delayed
ricompense: A life-span comparison. Psychological Science, 5,
33–36.

Verde, L., Myerson, J., & McFadden, E. (1997). Rate of temporal
discounting decreases with amount of reward. Memory &
Cognition, 25, 715–723.

Hare, T. A., Camerer, C. F., & Rangel, UN. (2009). Self-control
in decision-making involves modulation of the vmPFC
valuation system. Scienza, 324, 646–648.

Hariri, UN. R., Brown, S. M., Williamson, D. E., Flory, J. D., de Wit,
H., & Manuck, S. B. (2006). Preference for immediate over
delayed rewards is associated with magnitude of ventral
striatal activity. Journal of Neuroscience, 26, 13213–13217.
Hart, H., Radua, J., Nakao, T., Mataix-Cols, D., & Rubia, K. (2013).

Meta-analysis of functional magnetic resonance imaging
studies of inhibition and attention in attention-deficit/
hyperactivity disorder: Exploring task-specific, stimulant
medication, and age effects. JAMA Psychiatry, 70, 185–198.

Heerey, E. A., Robinson, B. M., McMahon, R. P., & Gold,

J. M. (2007). Delay discounting in schizophrenia.
Cognitive Neuropsychiatry, 12, 213–221.

Hsee, C. K., & Rottenstreich, Y. (2004). Music, pandas, E
muggers: On the affective psychology of value. Journal
of Experimental Psychology: General, 133, 23–30.

Kable, J. W., & Glimcher, P. W. (2007). The neural correlates
of subjective value during intertemporal choice. Nature
Neuroscience, 10, 1625–1633.

Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001).
Anticipation of increasing monetary reward selectively recruits
nucleus accumbens. Journal of Neuroscience, 21, RC159.
Knutson, B., & Greer, S. M. (2008). Anticipatory affect: Neural

correlates and consequences for choice. Philosophical
Transactions of the Royal Society of London, Series B,
Biological Sciences, 363, 3771–3786.

Li, X. (2008). The effects of appetitive stimuli on out-of-domain
consumption impatience. Journal of Consumer Research,
34, 649–656.

Loewenstein, G. (1996). Out of control: Visceral influences on
behavior. Organizational Behavior and Human Decision
Processes, 65, 272–292.

2466

Journal of Cognitive Neuroscience

Volume 26, Numero 11

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

l

l

/

/

/

/
j

T
T

F
/

io
T
.

:
/
/

H
T
T
P
:
/
D
/
o
M
w
io
N
T
o
P
UN
R
D
C
e
.
D
S
F
io
R
o
l
M
v
e
H
R
C
P
H
UN
D
io
io
R
R
e
.
C
C
T
.
o
M
M
/
j
e
o
D
tu
C
N
o
/
C
UN
N
R
UN
T
R
io
T
io
C
C
l
e
e

P

D
P
D
2
F
6
/
1
2
1
6
/
2
1
4
1
5
/
5
2
1
4
9
5
4
5
7
/
9
1
5
7
7
8
o
2
C
0
N
6
_
2
UN
/
_
j
0
o
0
C
6
N
4
2
_
UN
P
_
D
0
0
B
6

4
G
2
tu
.
e
P
S
T
D
o
F
N
B
0

7
S
M
e
IO
P
T
e
M
l
io
B
B
e
R
R
UN
2
R
0
2
io
3
e
S

/
j

F

/

.

T

tu
S
e
R

o
N

1
7

M
UN

2
0
2
1

Luce, R. D. (2005). Individual choice behavior: A theoretical

analysis (Dover ed.). New York: John Wiley & Sons.

Luna, B. (2009). Developmental changes in cognitive control
through adolescence. Advances in Child Development
and Behavior, 37, 233–278.

Madden, G. J., & Bickel, W. K. (2009). Impulsivity: IL
behavioral and neurological science of discounting.
Washington, DC: APA Books.

Madden, G. J., Petry, N. M., Badger, G. J., & Bickel, W. K. (1997).

Impulsive and self-control choices in opioid-dependent
patients and non-drug-using control participants: Drug
and monetary rewards. Experimental and Clinical
Psychopharmacology, 5, 256–262.

Marco, R., Miranda, A., Schlotz, W., Melia, A., Mulligan, A.,
Muller, U., et al. (2009). Delay and reward choice in
ADHD: An experimental test of the role of delay aversion.
Neuropsychology, 23, 367–380.

Mazur, J. E. (1987). An adjusting procedure for studying delayed
rinforzo. In M. l. Commons, J. E. Mazur, J. UN. Nevin,
& H. Rachlin (Eds.), Quantitative analysis of behavior:
Vol. 5. The effect of delay and intervening events on
reinforcement value (pag. 55–73). Hillsdale, NJ: Erlbaum.
McClure, S. M., Ericson, K. M., Laibson, D. I., Loewenstein, G.,

& Cohen, J. D. (2007). Time discounting for primary rewards.
Journal of Neuroscience, 27, 5796–5804.

McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen,
J. D. (2004). Separate neural systems value immediate
and delayed monetary rewards. Scienza, 306, 503–507.

Mischel, W. (1974). Processes in delay of gratification. Advances

in Experimental Social Psychology, 7, 249–292.

gratification. Journal of Abnormal Child Psychology, 14,
191–204.

Read, J. P., Frederick, S., Orsel, B., & Rahman, J. (2005).
Four score and seven years from now: The date/delay
effect in temporal discounting. Management Science, 41,
1326–1335.

Reynolds, B., Leraas, K., Collins, C., & Melanko, S. (2009). Delay
discounting by the children of smokers and nonsmokers.
Drug and Alcohol Dependence, 99, 350–353.

Sagvolden, T., Aase, H., Zeiner, P., & Berger, D. (1998).

Altered reinforcement mechanisms in attention-deficit/
hyperactivity disorder. Behavioural Brain Research, 94,
61–71.

Scheres, A., & Hamaker, E. l. (2010). What we can and cannot
conclude about the relationship between steep temporal
reward discounting and hyperactivity-impulsivity symptoms
in attention-deficit/hyperactivity disorder. Biological
Psychiatry, 68, e17–e18.

Scheres, A., Lee, A., & Sumiya, M. (2008). Temporal reward

discounting and ADHD: Task and symptom specific
effects. Journal of Neural Transmission, 115, 221–226.

Scheres, A., Milham, M. P., Knutson, B., & Castellanos,

F. X. (2007). Ventral striatal hyporesponsiveness during
reward anticipation in attention-deficit/hyperactivity
disorder. Biological Psychiatry, 61, 720–724.

Scheres, A., Tontsch, C., Thoeny, UN. L., & Kaczkurkin, UN.

(2010). Temporal reward discounting in attention-deficit/
hyperactivity disorder: The contribution of symptom
domini, reward magnitude, and session length.
Biological Psychiatry, 67, 641–648.

Mischel, W., & Baker, N. (1975). Cognitive appraisals and

Schultz, W., Dayan, P., & Montague, P. R. (1997). A neural

transformations in delay behavior. Journal of Personality
and Social Psychology, 31, 254–261.

Olson, E. A., Collins, P. F., Hooper, C. J., Muetzel, R., Lim, K. O.,
& Luciana, M. (2009). White matter integrity predicts delay
discounting behavior in 9- to 23-year-olds: A diffusion tensor
imaging study. Journal of Cognitive Neuroscience, 21,
1406–1421.

Oppenheimer, D. M., & Frank, M. C. (2008). A rose in any

other font would not smell as sweet: Effects of perceptual
fluency on categorization. Cognition, 106, 1178–1194.
Paloyelis, Y., Asherson, P., & Kuntsi, J. (2009). Are ADHD
symptoms associated with delay aversion or choice
impulsivity? A general population study. Journal of the
American Academy of Child & Adolescent Psychiatry,
48, 837–846.

Panksepp, J. (2004). Affective neuroscience: The foundations

of human and animal emotions. New York: Oxford
Stampa universitaria.

Peters, J., & Büchel, C. (2010). Episodic future thinking reduces

reward delay discounting through an enhancement of
prefrontal-mediotemporal interactions. Neuron, 66, 138–148.

Peters, J., & Büchel, C. (2011). The neural mechanisms of

inter-temporal decision-making: Understanding variability.
Trends in Cognitive Sciences, 15, 227–239.

Pine, A., Shiner, T., Seymour, B., & Dolan, R. J. (2010).

Dopamine, time, and impulsivity in humans. Journal of
Neuroscience, 30, 8888–8896.

Prencipe, A., Kesek, A., Cohen, J., Lamm, C., Lewis, M. D.,
& Zelazo, P. D. (2010). Development of hot and cool
executive function during the transition to adolescence.
Journal of Experimental Child Psychology, 108, 621–637.
Rangel, A., & Hare, T. (2010). Neural computations associated

with goal-directed choice. Current Opinion in Neurobiology,
20, 262–270.

Rapport, M. D., Tucker, S. B., DuPaul, G. J., Merlo, M., &
Stoner, G. (1986). Hyperactivity and frustration: IL
influence of control over and size of rewards in delaying

substrate of prediction and reward. Scienza, 275,
1593–1598.

Schweitzer, J. B., & Sulzer-Azaroff, B. (1988). Self-control:
Teaching tolerance for delay in impulsive children.
Journal of the Experimental Analysis of Behavior, 50,
173–186.

Schweitzer, J. B., & Sulzer-Azaroff, B. (1995). Self-control in
boys with attention deficit hyperactivity disorder: Effects
of added stimulation and time. Journal of Child Psychology
and Psychiatry, 36, 671–686.

Shamosh, N. A., Deyoung, C. G., Verde, UN. E., Reis, D. L.,
Johnson, M. R., Conway, UN. R., et al. (2008). Individual
differences in delay discounting: Relation to intelligence,
working memory, and anterior prefrontal cortex.
Psychological Science, 19, 904–911.

Shamosh, N. A., & Gray, J. R. (2008). Delay discounting and
intelligence: A meta-analysis. Intelligenza, 36, 289–305.
Sonuga-Barke, E. J., Taylor, E., Sembi, S., & Smith, J. (1992).
Hyperactivity and delay aversion-I. The effect of delay on
choice. Journal of Child Psychology and Psychiatry, 33,
387–398.

Sozou, P. D., & Seymour, R. M. (2003). Augmented discounting:
Interaction between ageing and time-preference behaviour.
Proceedings of the Royal Society B: Biological Sciences,
270, 1047–1053.

Steinberg, l. (2010). A dual systems model of adolescent
risk-taking. Developmental Psychobiology, 52, 216–224.
Steinberg, L., Graham, S., OʼBrien, L., Woolard, J., Cauffman, E.,
& Banich, M. (2009). Age differences in future orientation
and delay discounting. Child Development, 80, 28–44.
Thaler, R. H. (1981). Some empirical evidence on dynamic

inconsistency. Economic Letters, 8, 201–207.

Thorell, l. B. (2007). Do delay aversion and executive function

deficits make distinct contributions to the functional
impact of ADHD symptoms? A study of early academic
skill deficits. Journal of Child Psychology and Psychiatry,
48, 1061–1070.

Fassbender et al.

2467

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

l

l

/

/

/

/
j

F
/

T
T

io
T
.

:
/
/

H
T
T
P
:
/
D
/
o
M
w
io
N
T
o
P
UN
R
D
C
e
.
D
S
F
io
R
o
l
M
v
e
H
R
C
P
H
UN
D
io
io
R
R
e
.
C
C
T
.
o
M
M
/
j
e
o
D
tu
C
N
o
/
C
UN
N
R
UN
T
R
io
T
io
C
C
l
e
e

P

D
P
D
2
F
6
/
1
2
1
6
/
2
1
4
1
5
/
5
2
1
4
9
5
4
5
7
/
9
1
5
7
7
8
o
2
C
0
N
6
_
2
UN
/
_
j
0
o
0
C
6
N
4
2
_
UN
P
_
D
0
0
B
6

4
G
2
tu
.
e
P
S
T
D
o
F
N
B
0

7
S
M
e
IO
P
T
e
M
l
io
B
B
e
R
R
UN
2
R
0
2
io
3
e
S

/
j

T

F

/

.

tu
S
e
R

o
N

1
7

M
UN

2
0
2
1

Tripp, G., & Alsop, B. (1999). Sensitivity to reward frequency

in boys with attention deficit hyperactivity disorder.
Journal of Clinical Child & Adolescent Psychology, 28,
366–375.

Trope, Y., & Liberman, N. (2003). Temporal construal.

Psychological Review, 110, 403–421.

van den Bos, W., & McClure, S. M. (2013). Towards a general

model of temporal discounting. Journal of the Experimental
Analysis of Behavior, 99, 58–73.

Van Leijenhorst, L., Zanolie, K., Van Meel, C. S., Westenberg,

P. M., Rombouts, S. A., & Crone, E. UN. (2010). What motivates

the adolescent? Brain regions mediating reward sensitivity
across adolescence. Cerebral Cortex, 20, 61–69.

Watson, D., & Tellegen, UN. (1985). Toward a consensual

structure of mood. Psychological Bulletin, 98, 219–235.
Watson, D., Wiese, D., Vaidy, J., & Tellegen, UN. (1999). IL
two general activation systems of affect: Structural findings,
evolutionary considerations, and psychobiological evidence.
Journal of Personality and Social Psychology, 76, 821–838.

Wimmer, G. E., & Shohamy, D. (2012). Preference by

association: How memory mechanisms in the
hippocampus bias decisions. Scienza, 338, 270–273.

D
o
w
N
l
o
UN
D
e
D

F
R
o
M

l

l

/

/

/

/
j

F
/

T
T

io
T
.

:
/
/

H
T
T
P
:
/
D
/
o
M
w
io
N
T
o
P
UN
R
D
C
e
.
D
S
F
io
R
o
l
M
v
e
H
R
C
P
H
UN
D
io
io
R
R
e
.
C
C
T
.
o
M
M
/
j
e
o
D
tu
C
N
o
/
C
UN
N
R
UN
T
R
io
T
io
C
C
l
e
e

P

D
P
D
2
F
6
/
1
2
1
6
/
2
1
4
1
5
/
5
2
1
4
9
5
4
5
7
/
9
1
5
7
7
8
o
2
C
0
N
6
_
2
UN
/
_
j
0
o
0
C
6
N
4
2
_
UN
P
_
D
0
0
B
6

4
G
2
tu
.
e
P
S
T
D
o
F
N
B
0

7
S
M
e
IO
P
T
e
M
l
io
B
B
e
R
R
UN
2
R
0
2
io
3
e
S

/
j

/

F

.

T

tu
S
e
R

o
N

1
7

M
UN

2
0
2
1

2468

Journal of Cognitive Neuroscience

Volume 26, Numero 11The Decimal Effect: Behavioral and Neural Bases for image
The Decimal Effect: Behavioral and Neural Bases for image
The Decimal Effect: Behavioral and Neural Bases for image
The Decimal Effect: Behavioral and Neural Bases for image
The Decimal Effect: Behavioral and Neural Bases for image
The Decimal Effect: Behavioral and Neural Bases for image

Scarica il pdf