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The effect of delay, utility, and magnitude on delay discounting in an animal model of Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review

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Abstract

The delay discounting paradigm involves choosing between a small, immediate reinforcer (SS) or larger, delayed reinforcer (LL). Children with ADHD tend to choose the SS reinforcer more often than controls, which is interpreted as impulsivity. Studies on an animal model of ADHD, the Spontaneously Hypertensive Rat (SHR), show the same pattern, with SHR preferring the SS reinforcer. However, it is not entirely clear why this pattern exists. It has been proposed that ADHD children tend to be delay averse, i.e. that they actively seek to reduce trial time. An alternative hypothesis is that ADHD children struggle to see the long-term utility of their choices. We reviewed data from eight SHR studies on delay discounting and investigated which hypothesis was the best predictor of LL preference. Results found that SHRs and controls do not differ in overall performance on the delay discounting task, regardless of whether the independent variable is delay between response and reinforcer, magnitude of the reinforcer, or utility of the large reinforcer. However, if utility is held constant while the response-reinforcer delay is manipulated, SHRs show a steeper discounting curve than controls.
The effect of delay, utility, and magnitude on delay discounting in
an animal model of Attention-Deficit/Hyperactivity Disorder
(ADHD): a systematic review
The delay discounting paradigm involves choosing between a small, immediate reinforcer (SS) or larger, delayed reinforcer (LL). Children
with ADHD tend to choose the SS reinforcer more often than controls, which is interpreted as impulsivity. Studies on an animal model of
ADHD, the Spontaneously Hypertensive Rat (SHR), show the same pattern, with SHR preferring the SS reinforcer. However, it is not entirely
clear why this pattern exists. It has been proposed that ADHD children tend to be delay averse, i.e. that the time between response and
reinforcer is something they opt to avoid. An alternative hypothesis is that ADHD children struggle to see the long-term utility of their choices.
We reviewed data from eight SHR studies on delay discounting and investigated which hypothesis was the best predictor of LL preference.
Results found that SHRs and controls do not differ in overall performance on the delay discounting task, regardless of whether the dependent
variable is delay between response and reinforcer, magnitude of the reinforcer, or utility of the large reinforcer. However, if utility is held
constant while the response-reinforcer delay is manipulated, SHRs show a steeper discounting curve than controls. The evidence suggests
the possibility that SHRs may be delay averse.
Delay discounting involves choosing
between a small, immediate reinforcer (SS)
and a larger, delayed reinforcer (LL). In
ADHD studies, ADHD children will typically
show a steeper discounting curve than
controls, displaying impulsivity (Demurie et
al., 2012).
It is hypothesised that ADHD children are
delay averse, because they actively seek to
reduce trial time by choosing the smaller
reinforcer (Sonuga-Barke et al., 1992).
Top: Percentage of LL choices as a function of response-reinforcer delay
for the large reinforcer. Significant only at 12 seconds.
Center: Distribution of LL choices by utility.
Bottom: Preliminary data from a meta-analysis on SHR and delay
discounting. Final weighted d may change pending full data collection.
We collected data from eight studies on
delay discounting that used SHR as
participants (Adriani et al., 2003; 2004; Fox
et al., 2008; Garcia & Kirkpatrick, 2013;
Hand et al., 2009; Íbias & Pellón,
2011;2014; Pardey et al., 2009).
Data was analysed in terms of utility (long-
term value of the large reinforcer relative to
the small reinforcer), response-reinforcer
delay, and magnitude of the large reinforcer.
Preliminary data on a meta-analysis is also presented.
REFERENCES:
Adriani, W., Caprioli, A., Granstrem, O., Carli, M., & Laviola, G. (2003).
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Adriani, W., Rea, M., Baviera, M., Invernizzi, W., Carli, M., Ghirardi, O., . . .
Laviola, G. (2004). Psychopharmacology, 176(3-4), 296-304.
Demurie, E., Roeyers, H., Baeyens, D., & Sonuga-Barke, E. (2012).
Developmental Science, 15(6), 791-800.F
Fox, A. T., Hand, D. J., & Reilly, M. P. (2008). Behavioural Brain Research, 187,
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Garcia, A., & Kirkpatrick, K. (2013). Behavioural Brain Research, 238, 10-22.
Hand, D. J., Fox, A. T., & Reilly, M. P. (2009). Behavioural Pharmacology, 20, 549-
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Íbias, J., & Pellón, R. (2011). Behavioural Brain Research, 223, 58-69.
Íbias, J., & Pellón, R. (2014). Behavioural Brain Research, 271, 184-194
Pardey, M. C., Homewood, J., Taylor, A., & Cornish, J. L. (2009). Journal of
Neuroscience Methods, 176(2), 166-171.
Sagvolden, T. (2000). Neuroscience & Biobehavioral Reviews, 24(1), 31-39.
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The effect of delay, utility, and magnitude on delay discounting in
an animal model of Attention-Deficit/Hyperactivity Disorder
(ADHD): a systematic review
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 3 6 10 12 20 24 30 60
% of LL choices
Response-Reinforcer Delay
Percentage of LL choices as a function of strain and RRD
SHR
WKY
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00
% of LL choices
Utility
Percentage of LL choices as a function of strain and
flexible utility
SHR
WKY
Overall, the SHRs and controls (WKY rats)
did not differ in their percentage of LL
choices regardless of whether the measure
was response-reinforcer delay, magnitude of
the reinforcer, or utility (all ps > .09).
Thus, contrary to what is often reported in
the literature, the SHRs do not differ in their
performance relative to controls, and
therefore do not display the same impulsivity
as observed in ADHD children.
There was one exception to this pattern:
If the utility was held constant, then SHRs
would show a steeper discounting curve
than controls as response-reinforcer delay
increased. This finding may suggests that
SHRs are delay averse compared to
controls, similar to ADHD children (Fox et
al., 2008; Hand et al., 2009).
However, this manipulation was only
possible by manipulating the inter-trial
interval. A possibility therefore exists that
this pattern reflects a sensitivity to inter-trial
delays rather than response-reinforcer
delays.
Furthermore, the data on which this
exception was based on only one set of rats.
Department of Behavioral Sciences
The Spontaneously Hypertensive Rat (SHR)
is a validated animal model of ADHD
(Sagvolden et al., 2000). While SHRs tend
to show the same impulsive behaviour as
ADHD children in the delay-discounting
paradigm (e.g. Fox et al., 2008), we cannot
be certain that they display this behaviour
for the same reason. There are two primary
hypotheses that attempts to explain
discounting in SHRs:
1) Delay aversion hypothesis: The SHRs
are delay averse and choose the SS
option more frequently as the response-
reinforcer delay increases, because they
want to avoid the waiting between their
response and the reinforcer.
2) Optimality hypothesis: The SHRs are not
able to see the long-term value, or utility,
of their choices, and so choosing the SS
option more frequently is a result of them
discounting the utility of the options more
than controls do.
r = .57
r = .50
-8.00
-6.00
-4.00
-2.00
0.00
2.00
4.00
6.00
8.00
Effect size g
Distribution of effect sizes (g)
g= -0.175
SHR ->
controls ->
... If testing is terminated after a fixed time duration, then reward maximizing depends on the SS/LL reward magnitude ratio and the SS/LL trial length ratio (i.e. how much more valuable is the LL choice in the long run: Sjoberg, Holth & Johansen, 2016). The experimenter can easily calculate the reward maximizing, or "optimal", choice, and human participants are often informed about the experimental parameters beforehand and can make a reasonable mental assessment of what choice produces the most rewards. ...
... A related model of foraging describes energy gain over time by dividing the size of the reward by the delay before it is received, which effectively gives an index of rewards per second for each response, or EoR: expectation of rates (Bateson & Kacelnik, 1996). An expansion of the EoR equation involves calculating the relative weight of LL compared to SS for each choice trial, based on ratios of reward magnitude, delay length, and inter-trial-interval lengths, in order to get a measure of the long-term value for choosing the LL alternative (Sjoberg et al., 2016). Another approach takes into account perception of time, and describes reward discounting as the actual reward value divided by the sum of pre-and post-reward delays (Blanchard, Pearson, & Hayden, 2013). ...
Article
Full-text available
The delay discounting paradigm involves choosing between a small, immediate reward and a larger, delayed reward. As the delay between response and reinforcer increases for the large reward, people with Attention-Deficit/Hyperactivity Disorder (ADHD) tend to choose the small reward more often than controls. Studies on an animal model of ADHD, the Spontaneously Hypertensive Rat (SHR), find similar results. This pattern is typically interpreted as impulsive behaviour, implying that an unwillingness to wait decreases the likelihood of choosing the large reward. Alternatively, the results can be interpreted in terms of optimality, where a switch in preference from large to small rewards indicates sub-optimal behaviour. We critically discuss available evidence on delay discounting in ADHD and the SHR model, and evaluate whether an optimality perspective provides a useful interpretation of the data. Our findings suggest that optimality is a term that contributes little to explaining behaviour in delay discounting, outside of acting as a mathematical measure of reward maximization. Impulsive behaviour is best explained as a consequence of controlling variables, first and foremost the delay between response and reward, but also to a certain degree the inter-trial-interval and the reward magnitude.
... If we were to manipulate the magnitude of the large reinforcer then we will also find a change in performance [57,63]. How do we know that the SHRs are sensitive to temporal delays, and not to other changes in the experimental setup, such as the inter-trial interval [60], reinforcer magnitude [63], or the relative long-term value of the reward [64]? ...
Article
Full-text available
Background Animal models of human behavioural deficits involve conducting experiments on animals with the hope of gaining new knowledge that can be applied to humans. This paper aims to address risks, biases, and fallacies associated with drawing conclusions when conducting experiments on animals, with focus on animal models of mental illness. Conclusions Researchers using animal models are susceptible to a fallacy known as false analogy, where inferences based on assumptions of similarities between animals and humans can potentially lead to an incorrect conclusion. There is also a risk of false positive results when evaluating the validity of a putative animal model, particularly if the experiment is not conducted double-blind. It is further argued that animal model experiments are reconstructions of human experiments, and not replications per se, because the animals cannot follow instructions. This leads to an experimental setup that is altered to accommodate the animals, and typically involves a smaller sample size than a human experiment. Researchers on animal models of human behaviour should increase focus on mechanistic validity in order to ensure that the underlying causal mechanisms driving the behaviour are the same, as relying on face validity makes the model susceptible to logical fallacies and a higher risk of Type 1 errors. We discuss measures to reduce bias and risk of making logical fallacies in animal research, and provide a guideline that researchers can follow to increase the rigour of their experiments.
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