Theories of Dopamine Signaling-A Litarature Review (Nadeem ...€¦ · THEORIES OF DOPAMINE SIGNALLING NADEEM, 2015 3 animals were given the dopamine precursor 3,4-dihydroxyphenylalanine

Running Head: THEORIES OF DOPAMINE SIGNALLING NADEEM, 2015 1

Theories of Dopamine Signalling: A Literature Review

Nadia Nadeem

Dr. Becker

PNB 4Q03

December 2015

THEORIES OF DOPAMINE SIGNALLING NADEEM, 2015 2

Introduction

Dopamine is a neurotransmitter that has gained popularity as a research interest over the

past half century. Previously, the long held view in the literature had been that dopamine was a

neural substrate of reward. A link between dopamine and reward was first uncovered in a study

wherein rats, with electrodes implanted in various locations of their brains, were permitted to

press a lever and self-stimulate at will. The rats with electrodes in their septal area were found to

self-stimulate the most, and it was later discovered that they were activating their dopaminergic

pathways (Olds & Milner, 1954). The stimuli-seeking behaviour, coupled with dopaminergic

activation, led to the idea that dopamine contributes to the perception and facilitation of reward.

Since then, a common topic of research and debate has been the function of dopaminergic

signalling. There are three theories of dopamine signalling function that will be considered

within this review: hedonic value, reward learning, and incentive salience. The psychobiological

implications of dopamine within attention deficit hyperactivity disorder (ADHD) and addictions

will also be discussed.

Structure and Function of Dopamine

Dopamine, also known as 3-hydroxytyramine, is a catecholaminergic neurotransmitter

(Beaulieu & Gainetdinov, 2011). A large body of research conducted by Carlsson and his

colleagues (for a review, see Yeragani, Tancer, Chokka, & Baker, 2010) demonstrated that

dopamine was a neurotransmitter and not simply a precursor of norepinephrine, as was

previously thought at the time (Carlsson, Lindqvist, & Magnusson, 1957). Experimentation with

reserpine, a dopamine-depleting drug that causes loss of movement control as seen in patients

with Parkinson’s disease, was conducted on mice and rabbits (Carlsson, Lindqvist, &

Magnusson, 1957). Following the administration of reserpine to induce dopamine depletion, the


animals were given the dopamine precursor 3,4-dihydroxyphenylalanine (L-DOPA), which was

then found to reverse the effect (Carlsson, Lindqvist, & Magnusson, 1957). L-DOPA was then,

and continues to be, used in the treatment of Parkinsonism.

There are two classes of dopamine receptors. The D1 class encompasses subtypes D1 and

D5, and the D2 class includes D2, D3, and D4 (Beaulieu & Gainetdinov, 2011). The D1 and D2

receptor subtypes play a significant role in reward and reinforcement mechanisms (Beaulieu &

Gainetdinov, 2011). Though dopamine receptors are distributed widely throughout the brain, the

D1 class is the most abundant, with high densities in the caudate, putamen, nucleus accumbens

(NAcc), olfactory tubercle, striatum, frontal cortex, and temporal cortex (Daly & Salloway,

1994; Beaulieu & Gainetdinov, 2011).

Two of the primary loci of dopaminergic cell bodies, the substantia nigra (SN) and the

ventral tegmental area (VTA), are the source of the three main dopamine pathways (Gazzaniga,

Ivry, & Mangun, 2014). The nigrostriatal pathway consists of SN dopaminergic neurons

projecting to the dorsal striatum, which has been suggested to play a role in executive functions,

such as action selection and initiation (Balleine, Delgado, and Hikosaka, 2007). The VTA has

two projections, one of which is to the neocortex by way of the mesocortical pathway

(Gazzaniga, Ivry, & Mangun, 2014). The second projection, which is via the mesolimbic

pathway, leads to the NAcc, amygdala, hippocampus, and anterior cingulate cortex (Acc)

(Gazzaniga, Ivry, & Mangun, 2014). The mesolimbic pathway is often referred to as the “reward

pathway” because its activation seems to be correlated with rewarding stimuli (Horvitz, 2000).

As such, this pathway has been the focus of many studies in the dopamine literature. Finally, the

tuberoinfundibular is the fourth dopamine pathway, projecting from the hypothalamus to the

pituitary gland, where dopamine acts to inhibit prolactin release (Daly & Salloway, 1994). For


the purposes of this review, only the nigrostriatal, mesocortical, and mesolimbic dopamine

pathways are relevant.

Theories of Dopamine Signalling

Three theories regarding the function of dopamine signalling have come to prominence:

hedonic value, reward learning, and incentive salience. Each of these hypotheses attempts to

explain what dopamine’s function is, and subsequently, the mechanism by which dopamine

influences behavioural outcomes. There is considerable overlap between the theories, but the

debate lies in the nuances. Each perspective will be considered separately, and it will be

demonstrated that the current literature is divided between reward learning and incentive

salience.

Hedonic Value

The hedonic value theory is the oldest, and considers dopamine to be a neural substrate

for reward. This perspective states that the reason human beings feel pleasure is because certain

stimuli in the environment are rewarding. Thus, rewarding stimuli are sought after for their

pleasurable properties and positive feelings are associated with them, a process in which

dopamine is thought to play a role. This perspective views dopamine firing to be a response to

pleasurable stimuli, which then translates into a feeling of reward. In a way, pleasure is a natural

motivator that guides the individual towards acquiring rewards.

Dopamine is commonly associated with hedonic value as a result of early studies.

Amongst the first theories of dopamine signalling, as it affects cognition and behaviour, was the

anhedonia hypothesis (Wise, 1982). It stemmed from the long-held belief that behaviour is

controlled by reward and punishment, a concept demonstrated by studies of self-stimulation in


rats, whose lever pressing behaviour was interpreted as working for pleasurable reward (Olds &

Milner, 1954). The anhedonia hypothesis claims that neural dopamine systems mediate pleasure

produced by primary and secondary reinforcers, and thus dopamine blockade reduces pleasure

(Wise, 1982). Amongst several lines of evidence in support of this, when rats were allowed to

self-stimulate by pressing levers for IV injections of amphetamine, and were then administered

dopamine antagonists, a decline in self-stimulation was observed; it was interpreted that

dopamine was necessary for the sensation of pleasure (Wise, 1982). This idea became popular in

research and mainstream culture, leading to its label as the “pleasure neurotransmitter” (Berridge

& Robinson, 1998).

Once popular, the hedonic value theory has fallen from prominence in the dopamine

literature. Although many researchers agree that dopamine firing is associated with reward, and

somewhat pleasure, it does not seem to primarily function as a pleasure signal. Wise, the original

proponent of this theory, retracted anhedonia hypothesis in light of several lines of evidence

(Wise, 1994). If dopamine directly influences hedonic value associations, a correlation between

increased dopamine levels and likability should exist, and an absence of hedonic reactions in

severe dopamine depletion is expected. However, neither increasing extracellular dopamine in

dopamine knockdown mice nor stimulating dopamine neurotransmission in normal rat brains

causes an increase in hedonic “liking” reactions in taste reactivity studies (Cagniard, Balsam,

Brunner, & Zhuang, 2006). Similarly, up to a 99% loss of striatal dopamine via 6-

hydroxydopamine (6-OHDA) lesions has no discernable effect on taste reactivity (Berridge,

1989). Additionally, a common argument is that dopamine is correlated with subjective pleasure

ratings, but this hypothesis appears to be incorrect. Patients with Parkinson’s disease report


normal subjective pleasantness ratings for sweet and rewarding foods, despite the deterioration

of dopamine that is characteristic of the condition (Sienkiewicz-Jarosz et al., 2005).

Though plausible, the hedonic value hypothesis is too simplistic. Although dopamine

signalling appeared to be correlated with reward, pleasure did not seem to be the main focus of

the neurotransmitter. The tendency to seek pleasure and avoid pain is a basic component of

human behaviour, but is perhaps not sophisticated enough to account for how one adapts to

changes in the environment. As such, dopamine signalling function research continued in effort

to uncover evidence that would lead to a more robust theory.

Reward Learning

Up until this point, we have considered dopamine’s potential to correlate with pleasure.

More recently, researchers have focused on the role of dopamine in learning. Reward learning is

similar to pleasure in that it involves seeking out reward based on patterns. Learning mechanisms

allow for adjustment in various environments to maximize survival and reproduction. Since

pleasure is a basic and powerful human motivator, it would be logical for a learning mechanism

to develop around it. Reward learning allows for the utilization of naturally appealing rewards to

continuously guide and organize behaviour, a process theoretically facilitated by dopamine

signalling.

The reward learning hypothesis was proposed shortly after the hedonic value perspective

appeared in the literature. It was theorized that dopamine was the neural substrate of reward and

prediction (Schultz, Dayan, & Montague, 1997). This hypothesis was made based on the

observation of firing rates of dopamine neurons. There are two main patterns of firing activity in

dopamine neurons that increase extracellular levels of dopamine (Colombo, 2014). Tonic activity

refers to low, consistent firing patterns that are slow changing, whereas phasic activity consists


of sudden, high firing rates, leading to a temporary and sharp increase of extracellular dopamine

(Colombo, 2014). Studies examining single cell dopamine neuron recordings showed that when

appetitive stimuli were presented to monkeys, there were short, phasic activations (Schultz,

1986; Mirenowicz & Schultz, 1996). Initially, the dopamine neurons showed activation shortly

after the reward was perceived, but following repeated pairings of the cue with the reward, their

phasic activations shifted to just after cue onset (Schultz, Dayan, & Montague, 1997). Then,

when a cue was presented and a reward followed, dopamine would only fire after cue onset and

no change would be recorded once the reward was received. Interestingly, when a cue that had

been previously paired with a reward was presented, but no reward was received, a significant

reduction below baseline firing rate was observed at the time the reward was to be delivered.

Taken together, it was hypothesized that dopamine neurons were encoding the difference

between the expected reward and the obtained reward, termed reward prediction error (RPE), as

well as the temporal information regarding when the reward was to be received (Schultz, Dayan,

& Montague, 1997; Hollerman & Schultz, 1998).

RPE is the hypothetical mechanism by which dopamine neurons facilitate learning. It is

the type of component that the hedonic value theory lacked: the ability to be specific. Whereas

the hedonic value hypothesis would predict dopamine firing during the perception of a reward,

reward learning would predict firing patterns that allow for modulating behaviour following

feedback through positive or negative RPE. When a reward is not predicted by a stimulus,

dopamine firing is observed following onset of the unexpected reward, resulting in a positive

RPE value; this feedback informs the individual that some cue in the environment has lead to a

reward (Schultz, Dayan, & Montague, 1997). A negative RPE value is encoded when a reward

was predicted by some cue but not received, wherein dopamine activity is recorded following the


cue onset but a depression below baseline firing rate is observed once the reward is not delivered

at the expected time (Schultz, Dayan, & Montague, 1997; Hollerman & Schultz, 1998). This

violation of expectation is encoded and leads to an extinction of the response to the cue

(Montague, Dayan, & Sejnowski, 1996). According to this theory, dopamine is an anticipatory

signal and the RPE is the learning mechanism by which certain behaviours are reinforced or

extinguished. As such, this reward learning guides one’s response to cues in the environment.

Though promising, the reward learning theory it not without its criticisms. If dopamine

plays a role in facilitating learning, then a decrease in dopamine is expected to impair reward

learning. However, in learning experiments, dopamine-deficient mice showed preferential

drinking of both sucrose and saccharin infused water over plain water, demonstrating that

dopamine is not necessary for learning a reward association (Cannon & Palmiter, 2003). As well,

the reward learning hypothesis would predict that an increase in dopamine would allow for

quicker learning because its presence in excess would allow for increased facilitation of

stimulus-reward associations. Yet, studies conducted with dopamine transporter knockdown

mice, wherein the mice are hyperdopaminergic, appear to show normal patterns of reinforcement

learning and do not learn any faster despite having excess dopamine (Cagniard et al., 2006).

Though the reward learning hypothesis is not a sufficient explanation, it did add to the

understanding of dopaminergic function. Nevertheless, it is a well-constructed theory that has

utilized the principles of reinforcement learning and applied it to the neural context in an effort to

better understand behaviour.

Incentive Salience

We have now considered both the hedonic value and reward learning hypotheses as

respectable candidates in the dopamine signalling literature. The reward learning hypothesis has


considerable weight and is a popular idea in the literature. The strongest opponent of reward

learning is the incentive salience hypothesis. In this theory, reward is composed of “wanting”,

“learning”, and “liking”, wherein dopamine only facilitates the “wanting” component, which is

known as incentive (Berridge & Robinson, 1998). “Wanting” refers to motivation; according to

this theory, dopamine takes a neutral representation and transforms it into an attractive, attention

capturing incentive (Berridge & Robinson, 1998). In this way, an item becomes desired and

some associative learning occurs, but these are separable components such that incentive

salience is what is necessary to drive behaviour. Dopaminergic activity associates motivation

with physiologically relevant, reward-related stimuli (Berridge & Robinson, 1998). Through

experience, an unconditioned stimulus that is “liked” has an incentive value assigned to its

predictor (the conditioned stimulus), which makes the liked reward also a wanted reward

(Berridge & Robinson, 1998). An important component of this theory is that incentive salience is

applied to targets that are physiologically relevant, and vice versa, such that there is motivation

to obtain natural rewards that benefit the individual (Berridge & Robinson, 1998; Berridge,

2007). In this way, incentive salience is potentially how stimuli values are updated as they

pertain to physiological relevance, and is what orients individuals to specific and relevant cues in

their environment.

Associative learning is the proposed mechanism by which incentive is associated with

stimuli, and is mediated by mesolimbic dopamine projections (Berridge, Robinson, & Aldridge,

2009). These stimuli can be innate, unconditioned stimuli, or neutral-turned-conditioned stimuli;

a conditioned stimulus acquires motivational status when it is associated with an innate reward

(Berridge, Robinson, & Aldridge, 2009). Incentive salience is attributed in a proposed three-

stage process. First, “liking” of the unconditioned stimulus leads to “wanting” of the conditioned


stimulus. Then, “reboosting” of the incentive salience by “wanting” the conditioned stimulus

occurs as a result of its association with reward over multiple occurrences. Finally, “wanting” is

attributed to the conditioned stimulus, and as a result, so is motivation to obtain the conditioned

stimulus (Berridge, 2007; Berridge, Robinson, & Aldridge, 2009).

There is strong evidence in support of the incentive salience hypothesis. One example of

support is from the study of ventral pallidal activation. Dopaminergic inputs are located in the

ventral pallidum, meaning that dopamine activation influences ventral pallidal activation; this is

a way to measure the consequences of dopaminergic activation (Tindell, Berridge, Zhang,

Peciña, & Aldridge, 2005). Mesolimbic dopaminergic activation has been found to temporally

shift from predictive cues, those that signal an upcoming reward, towards motivational cues,

which are those immediately preceding the reward; this pattern appears to be encoded by ventral

pallidal neurons (Tindell et al., 2005). This result implies that dopamine does not act as a

predictive signal, but rather as a facilitator of the assignment of motivation to a cue in order to

influence behavioural outcomes. As well, dopamine-deficient mice, which retain preferences for

sweet rewards, initiate licking of sucrose rewards less often than control mice (Cannon &

Palmiter, 2003). This demonstrates that hedonic value remains the same despite low levels of

dopamine, but more importantly that there is little motivational drive to consume the reward.

Similarly, dopamine transporter knockdown mice retain the same preference for rewarding foods

despite having elevated dopamine levels, but show increased motivation to work for a food

reward (Cagniard et al., 2006). As well, studies have demonstrated that when an association has

been made between a conditioned stimulus and an unconditioned stimulus, wherein both are

unpleasant tasting, when the unconditioned stimulus becomes physiologically relevant the

conditioned stimulus is actively sought after (Berridge & Schulkin, 1989). Although the


unconditioned stimulus may have never been experienced in a hedonic context, when it becomes

physiologically relevant, its associated conditioned stimulus is attributed with motivational

value. This demonstrates how incentive salience is assigned to the conditioned stimulus over

repeated occurrences, making it attractive on its own (Berridge & Schulkin, 1989). These cases

illustrate how dopamine plays a role in associating incentive with a stimulus, and in turn leading

to increased drive to acquire the reward.

The incentive salience theory appears to have relatively few criticisms and seems to be

widely supported in the literature. The majority of criticisms are of the incomplete nature of

some components within the theory. For example, dopamine seems to play a role in associative

learning, but studies previously mentioned in this paper have demonstrated that learning can

occur despite low levels of dopamine (Cannon & Palmiter, 2003; for a review, see Cannon &

Bseikri, 2004) and does not occur any faster or more efficiently with higher levels of dopamine

(Cagniard et al., 2006). If dopamine’s role in learning is not through the implementation of RPE,

then the mechanism is largely unknown (Berridge, 2007). As such, further research must be done

to examine the nuances in dopaminergic transmission as they relate to reward. Another potential

issue would be about how incentive salience applies to complex behaviours. In simple,

physiologically driven circumstances, it is clear that motivation is assigned to a cue that will lead

to a natural reward. However, in the modern context, there are a host of complex cues that affect

physiological needs indirectly, such as tertiary reinforcers. In general, a tertiary reinforcer is a

result of conditioning through association with a secondary reinforcer. An example of a tertiary

reinforcer would be attending university, which is associated with the secondary reinforcer of

acquiring a job and earning money, which is associated with the primary reinforcer of obtaining

basic needs. It is clear that modern social problems, such as post-secondary education, have


physiological relevance; the issue is the mechanism by which incentive salience can be assigned

to the tertiary reinforcer since it is further removed from the primary reinforcer. In general,

tertiary reinforcers are those that are not directly related to a salient primary reinforcer, but still

influence behaviour in some way. However, it is possible that dopamine does not have the ability

to assign incentive to more complex reinforcers because of their subjectivity and less obvious

physiological relevance. Further studies must be conducted to examine the extent of dopamine’s

role in complex behavioural outcomes. In general, the criticisms of incentive salience do not

appear to be against the structure or validity of the theory, but rather are aimed at the finer details

and conceptual gaps.

The literature appears to be in general agreement with the incentive salience theory. It

incorporates hedonic value and reward learning, but outlines their role as dissociable from

incentive. In a way, the incentive salience approach retains the valuable concepts of the other

two theories while adding a motivational component to explain how the information is translated

into behaviour. Nevertheless, incentive salience and reward learning remain the two most

popular theories, and the literature is seemingly divided.

Dysfunctions of Dopamine

One way to tease apart the dopamine signalling theories is to examine dopamine

disorders. In this review, attention deficit hyperactivity disorder (ADHD) and addictions will be

considered. Each disorder will be examined from the perspectives of reward learning and

incentive salience as they are the two most popular and well-supported hypotheses in the

dopamine literature. The hedonic value hypothesis has not been considered a sufficient theory in


the literature, and so it will not be discussed in its own right, but rather as an overarching theme

as it relates to reward.

ADHD

Attention deficit hyperactivity disorder (ADHD) is a condition whose pharmacological

treatment is dopamine agonists. It is hypothesized that ADHD is a result of chronically low

levels of dopamine, and thus low levels of neural activity, which leads to hyperactivity for the

sake of stimulation (Wender, 1973). Neuroimaging studies support this hypothesis. There

appears to be a disruption in mesoaccumbens dopamine in adult ADHD patients, wherein there is

a reduction in dopamine synaptic markers (Volkow et al., 2009) and a reduction in dopamine

transporter levels (Volkow et al., 2007). In this way, dopamine deficiency is a significant

component of ADHD. The role of dopamine in ADHD will be examined from the perspectives

of reward learning and incentive salience.

ADHD and Reward Learning

From the reward learning perspective, patients with ADHD have malfunctioning reward

systems, which contributes to the symptoms of impulsivity and hyperactivity (Aarts et al., 2014).

There are two main dopaminergic theories. In accordance with the dopamine transfer deficit

(DTD), there is reduced anticipatory dopaminergic activation to predictive cues, leading to the

inability to associate a cue with an upcoming reward (Tripp & Wickens, 2008). Another theory is

the dynamic developmental theory (DDT), which assumes that there are lower levels of tonic

dopamine, leading to a shorter delay-of-reinforcement gradient and resulting in impulsive

behaviours (Sagvolden, Johansen, Aase, & Russell, 2005). In this way, patients with ADHD

show a preference for immediate rewards and learn only when rewards are immediate and

frequent (Sagvolden et al., 2005). For the purposes of this review their differences are not


important. The focus is that both theories are in agreement that immediate rewards are preferred,

and that reinforcement learning is impaired, in ADHD.

It is hypothesized that individuals with ADHD are unable to properly associate rewards

with outcomes, thus affecting reward learning (Johansen, Aase, Meyer, & Sagvolden, 2002).

Indeed, studies appear to demonstrate that patients with ADHD are impaired on reinforcement

learning tasks and unable to establish these associations (Frank, Santamaria, O’Reilly, &

Willcutt, 2007; Luman, Goos, & Oosterlaan, 2009). With ADHD, strong and salient reinforcers

are needed to guide behaviour, as typical ones are not sufficient (Johansen et al., 2002). As such,

both children and adults with ADHD seem to be biased towards small, immediate rewards rather

than large, delayed rewards (Tripp & Alsop, 2001; Schweitzer & Sulzer-Azaroff, 1995; Solanto

et al., 2001; Sonuga-Barke, Taylor, Sembi, & Smith, 1992; Sonuga-Barke, Williams, Hall, &

Saxton, 1996). The inability to delay gratification results in impulsive behaviour, a symptom

prevalent throughout the lifespan.

There is also diminished neural reward processing in ADHD. FMRI studies have

revealed that, in adults with ADHD, there is hypoactivity in the ventral striatum during the

reward anticipation phase, followed by hyperactivation in the same region when reward is being

received (Scheres, Millham, Knutson, & Castellanos, 2007; Hoogman et al., 2013; Kappel et al.,

2014; Umemento, Lukie, Kerns, Müller, & Holroyd, 2014; Furukawa al., 2014; von Rhein et al.,

2015). This might be a result of an inability to establish an association between reward-

predicting cues and reward reception, leading to a consistently increased RPE response in

affected adults (von Rhein et al., 2015).

The reward learning hypothesis is popular in theories of ADHD. There appears to be

evidence supporting the inability to predict upcoming reward, which is seen as a consequence of


dopamine deficiency. However, studies cited earlier in this paper have demonstrated that

dopamine is not necessary for reward learning and associations can be made in individuals with

dopamine deficiencies (Cannon & Palmiter, 2003). For example, although the ability to predict a

reward seems to be characteristic of ADHD, the ability to learn something is rewarding is not an

issue. Although individuals with ADHD prefer short, immediate rewards, they have learned what

rewards are and do seek them out. As well, it is well known that humans in general prefer

immediate to delayed rewards, but that this is more extreme in individuals with ADHD who

cannot delay gratification for a larger reward. The issue does not seem to be that reward learning

cannot occur properly, but that there is a lack of goal-directed behaviour that could explain why

individuals with ADHD act impulsively (Cannon & Bseikri, 2004). If lack of goal-directed

behaviour leads to impulsivity, it could also account for the affinity towards immediate rewards.

Although promising, reward learning does not appear to properly illustrate dopamine’s role in

ADHD.

ADHD and Incentive Salience

Few studies in the ADHD literature have been conducted with the explicit intent of

examining incentive salience. Most studies appear to treat motivational deficits as a consequence

of dysfunctional reward learning, whereby the theoretical inability to experience to predict

reward results in a lack of motivation (Volkow et al., 2011; Fosco, Hawk, Rosch, & Bubnik,

2015). However, this review has outlined how incentive attribution to cues is an idea equally

favoured by the literature, and in experimental contexts, a lack of dopamine has been found to

reduce motivation (Cannon & Palmiter, 2003; Cannon & Bseikri, 2004; Cagniard et al., 2006).

Though there is a place for reward learning in theories of ADHD, there is value in

considering it within the larger context of motivation. The incentive salience literature states that,


without motivation, hedonic value and reward learning alone are not sufficient explanations for

the function of dopamine activation. Studies suggest that dopamine deficits cause motivation

deficits, which in turn cause inattention (Volkow et al., 2011). This is supported by evidence that

inattention is at its worst in ADHD patients when tasks are repetitive and uninteresting, which by

nature are those that have low intrinsic motivation (Volkow et al., 2011). As well, motivational

incentives provided to individuals with ADHD in cognitive tasks improve stimulus salience and

increase inhibitory control by allocating a greater amount of attentional resources (Groom et al.,

2010). Similarly, when provided with incentives, executive function in ADHD patients is

significantly improved, though not normalized (Dovis, Van der Oord, Wiers, & Prins, 2012). The

failure to achieve normalized levels may be because externally induced motivation is not enough

to attribute incentive and requires dopamine to facilitate the association. Nonetheless, though

little research has currently been conducted specifically regarding it, some results are consistent

with the perspective of incentive salience.

A potential issue with the current ADHD literature is its commitment to the reward

learning theory. Though it is an elegant and well-composed theory, it is not the only hypothesis

that can explain the symptoms of ADHD. Regardless, the idea of deficient reward learning is

significant in the ADHD literature and other avenues have yet to be explored. Another related

problem is that the idea of reinforcement learning, which is hypothesized to be deficient in

ADHD as a result of dopamine deficiency, has not been critically appraised in its relation to

behaviour. For example, the basic assumption every theory of ADHD makes is that the failure to

predict reward is what leads to the inability to delay gratification, thus leading to impulsivity.

However, the reward learning hypothesis does not provide a robust mechanism that explains

behavioural outcomes; it is simply feedback. What is more logical is considering motivation in


its capacity to guide relevant behaviour, a component that is diminished when dopamine is

deficient (Cannon & Bseikri, 2004). In ADHD, rewards are still rewarding, but the chronically

low levels of dopamine theoretically are not sufficient for the assignment of incentive to cues.

Since dopamine activation has been found to shift from predictive cues towards motivational

cues (Tindell et al., 2005), this pattern of shifting activation would not be occurring anyway due

to the insufficient dopamine levels that are characteristic of ADHD, and so this distinction could

easily be overlooked. As such, it could be mistakenly inferred that the failure to predict reward is

the issue, rather than the inability to attribute motivation to cues. Thus, the theoretical lack of

incentive salience is a distinction that could be easily overlooked. As well, though impulsivity

can be seen as a way to induce stimulation in the individual, it can also be viewed as a

consequence of lacking goal-directed behaviour, which is hypothetically influenced by

motivation attribution through incentive salience. When there is a lack of goal-direction, all

behaviours are equally salient, potentially resulting in impulsive behaviours since they are all

equally appealing. All told, there appears to be an arguably stronger case for dysfunctional

incentive salience as an approach to examining ADHD symptoms, but it is an idea that has not

yet been embraced by the clinical literature.

Methylphenidate (MP) is a dopamine agonist commonly used to treat ADHD. It binds to

dopamine transporters and inhibits dopamine reuptake, thus increasing synaptic dopamine

density (Biederman & Faraone, 2005). Its efficacy has been commonly attributed with

facilitating reinforcement learning in accordance with the reward learning hypothesis, but it has

also been studied in the context of incentive salience with interesting results. In food-deprived

subjects, when MP preceded food stimulation without consumption, subjects reported increased

desire for food and feelings of hunger (Volkow et al., 2002). The MP amplified dopamine


activation in the dorsal striatum, which lead to an increase in motivational characteristics, known

as “wanting” (Volkow et al., 2002). Although it can be argued that increasing dopaminergic

concentration would reinstate reinforcement learning, the incentive salience literature suggests

that the increase in dopamine would restore incentive salience, and subsequently, motivational

deficits. This is a nuance that could be easily overlooked if one is not approaching the issue from

the perspective of incentive salience.

The majority of studies in ADHD literature have focused on reward learning. Currently,

there are few studies that have examined dopamine activation exclusively from the incentive

salience perspective. Of the studies that do make mention of motivation, they do not seem to

make the association that dopamine deficits lead to motivation deficits. Acknowledging that

dopamine deficiency impairs motivation, which arguably plays a larger role than predictive cues,

would broaden the understanding of ADHD.

Addictions

Addictions are another type of disorder of dopamine. Neural reward mechanisms are

abnormally plastic, implicating a role for mesolimbic dopamine in the formation of addictions

(Beaulieu & Gainetdinov, 2011). Though plasticity in neural mechanisms is adaptive, since it

allows the human brain to adjust to changing environments, it proves to be problematic in the

context of addictive drugs. The traditional hedonic value perspective would postulate that the

reason drugs are consumed in excess is because they stimulate dopaminergic pathways and lead

to feelings of pleasure. This is now known to be an out-dated view given the progression of the

dopamine literature. The reward learning and incentive salience hypotheses, however, have

considerable influence within the addictions literature and will be discussed here.


Addictions and Reward Learning

According to the reward learning hypothesis, addictions are the result of the inability to

predict reward (Keiflin & Janak, 2015). As mentioned earlier in this review, when an unexpected

reward is encountered, there appears to be an increase in dopamine activation (Schultz, Dayan, &

Montague, 1997). With natural rewards, such as food, the learning stops once the reward can

successfully be predicted by a cue (Schultz, Dayan, & Montague, 1997); there is stability in the

learned value. However, it has been proposed that neuroadaptations occur as a result of repeated

exposure to addictive drugs, which increase dopaminergic neuron firing via excitation and also

block dopamine transporters (for a review, see Sulzer, 2011). It is proposed that when a learning

signal is made through positive RPE, indicating that a reward was greater than expected, the

value of the state leading to the reward is increased (Redish, 2004). To elaborate, the physical

state the individual was in that lead to the receipt of the reward is conceptualized in such a way

that a value can be assigned to it, and thus the individual values of various physical states can be

compared relative to each other. These values assigned to each state are modified, either

negatively or positively, as a result of the RPE associated with the particular reward. With

natural rewards, there is an upper limit to the value that they can assign to any given state,

because natural rewards do not alter the dopaminergic transmission (Montague, Hyman, &

Cohen, 2004). Eventually, according to the reward learning hypothesis, the natural reward can

become predicted by a cue because it is stable and consistent (Redish, 2004; Montague, Hyman,

& Cohen, 2004). With addictive drugs, as a result of the ability to cause neuroadaptations, the

value of the state leading to drug receipt increases each time the drug is consumed without

apparent upper bounds, eventually surpassing the value of the states leading to natural rewards

(Redish, 2004). Since the likelihood of engaging in a state depends on its relative value when


compared to other states, an individual is then more likely to engage in a physical state that leads

to drug receipt (Redish, 2004). As well, there seems to be evidence of double dopaminergic

activation in response to both drug-seeking and drug-taking behaviours in rats previously

exposed to cocaine, leading to increased levels of extracellular dopamine in the NAcc (Phillips,

Stuber, Heien, Wrightman, & Carelli, 2003). In this way, dopamine activation at the time of

cocaine receipt implies that although the reward was somewhat predicted by dopamine release at

the cue, it was a greater reward than expected. As a result of addictive drugs’ direct influence on

dopamine transmission, rewards cannot be fully predicted, creating the appearance of a greater

reward at each occurrence (Montague, Hyman, & Cohen, 2004). Thus, this may be how the value

of physical states leading to drug reward increases in a seemingly unbounded fashion. In this

way, the neuropharmacological effects of drugs on dopaminergic activation drive the individual

into a non-optimal state where they act irrationally to obtain drug rewards (Redish, 2004;

Montague, Hyman, & Cohen, 2004). Thus, this can possibly be explained by sensitization of

reinforcing properties by the addictive drug, inducing RPE whenever the predictive cue and the

drug itself are encountered (Keiflin & Janak, 2015).

Reward learning views addiction as a byproduct of abnormal learning, induced by

addictive drugs’ ability to physically alter dopaminergic systems. This results in uncharacteristic

learning patterns, by which predictive cues cannot be properly established and every encounter

with the drug is met with a positive RPE. In this way, an addiction spirals out of control and

creates a sense of unprecedented reward with every interaction.

Addictions and Incentive Salience

The critique of the reward learning perspective of addiction is embedded in the incentive

salience approach. Within the general incentive salience hypothesis, associative learning is a


component, but is separable from motivation (Berridge & Robinson, 1998; Berridge, 2007).

Incentive salience proposes that it is incentive sensitization that leads to drug addiction,

characterized as increased “wanting” for the drug reward (Robinson & Berridge, 1993; Robinson

& Berridge, 2003). This is similar to the sensitization of reinforcing properties proposed by the

reward learning theory, but is distinct in that it focuses on the neural sensitizing underlying

intense feelings of “wanting” that lead to craving. Incentive salience argues that feelings of

pleasure, and predictions of pleasure, are not sufficient to motivate behaviour and nor do they

instil feelings of “wanting” (Robinson & Berridge, 1993). As demonstrated before, dopamine

does not appear to be necessary in the learning of associations (Cannon & Palmiter, 2003) and so

reward learning would not be influential enough to guide behavioural action.

According to incentive sensitization, drugs enhance mesolimbic dopamine transmission,

which has been demonstrated empirically (for a review, see Sulzer, 2011). While this

neuroadaptation was theorized to induce abnormal reward learning, in the incentive sensitization

context it is thought to cause hypersensitization to drugs and drug-related stimuli by virtue of

excess dopamine. In normal incentive salience, motivation is associated with some stimulus,

which leads to a motivated behaviour directed at obtaining some reward. In the case of drug

addiction, excessive salience is attributed to drugs and drug-related stimuli, meaning

malfunctioning incentive salience turns “wanting” into intense craving over time (Robinson &

Berridge, 1993). As such, the individual is motivated by the cues to obtain the drug.

Irrationality and compulsivity can also be explained by incentive sensitization. Drug

addicts seek drugs they do not like along with those that they do like, providing evidence for

general “wanting” of drugs (Fischman & Foltin, 1992). Also, an addict may have the intention to

avoid drugs, but cue-triggered “wanting” could result in overriding their goals and acting


compulsively to obtain the drug (Elster, 1999). As well, irrationality exists in the form of craving

that is independent of pleasure and more characteristic of “wanting”. This is demonstrated in the

way that addicts continue to use drugs despite diminishing pleasurable experience (Lambert,

McLeod, & Schenk, 2006). Individuals who were heavy or dependent cocaine users reported

higher levels of “wanting” than “liking” for cocaine, relative to experimental users (Lambert,

McLeod, & Schenk, 2006). Those who had been previously exposed to drugs at a younger age,

and thus had been using drugs for longer, showed the lowest “liking” scores for cocaine but were

the group with the highest cocaine dependence and lifetime use (Lambert, McLeod, & Schenk,

2006). This suggests that, although pleasurable feelings associated with drug consumption fades,

the effects of motivation continue to drive the individual to act to acquire addictive drugs. As

such, feeling a sense of reward fades and is not enough to account for the continued feelings of

craving, which appears to have a basis in incentive sensitization.

In the incentive salience approach, each interaction with a drug increases the amount of

incentive associated with drug-related cues, leading to excessive “wanting” which becomes an

intense craving over time. The addition of incentive into the framework of addiction provides a

role for dopamine in attributing motivation to carry out drug-seeking and consuming behaviours,

independent of hedonic value and reward learning.

Conclusion

This review has considered the state of the dopamine signalling literature as it pertains to

the hypotheses of hedonic value, reward learning, and incentive salience. It has been

demonstrated that reward learning and incentive salience are the two strongest contenders in

terms of their popularity in the literature. However, it is arguable that the incentive salience


hypothesis is the most likely explanation. This is because the reward learning hypothesis offers

associative learning as the mechanism by which action is influenced to obtain a reward, but

countless studies have demonstrated that motivation seems to be a necessary component. The

incentive salience hypothesis takes advantage of hedonic value of stimuli and applies associative

learning to attribute motivation to cues in order to guide behaviour.

Recent research has suggested that mesolimbic, mesocortical, and nigrostriatal dopamine

pathways respond not only to rewards, but rather to salient events in general (for a review, see

Horvitz, 2000). As well, another body of research has analyzed the diversity within dopamine

signals and hypothesizes that dopamine neurons come in various types that encode motivational

value and motivational salience, and that the types are mediated by an alerting signal (Bromberg-

Martin, Matsumoto, & Hikosaka, 2010). In this way, dopamine encodes value and salience in

order to guide adaptive behaviour. This larger framework of motivational control encompasses

hedonic value, reward learning, and incentive salience, but extends their function beyond reward,

assigning a larger role for dopamine. Logically speaking, dopamine is likely a neurotransmitter

with various functions, as elements of neural functioning are rarely divided neatly without

overlap. As such, it could be that each of the dopamine signalling theories is one component

within the broader context of dopamine’s role in motivational control.

Continuing to research the role of dopamine signalling is especially relevant in the

context of dopamine disorders. For example, MP is a dopamine agonist prescribed to treat

ADHD, and though it increases circulating levels of dopamine, there is only a general

understanding of the link between ADHD and dopamine because dopamine itself is not well

understood yet. A better understanding of the specific influence that dopamine signalling has on

the healthy brain allows for a more targeted, and perhaps more effective, therapeutic approach.


Similarly, with addictions research, it is valuable to understand how the neuroadaptations caused

by addictive drugs influence dopamine signalling, and more specifically, what information those

signals are conveying. Since the dopamine mechanisms are plastic, advanced knowledge could

be applied in a way to potentially reshape these mechanisms through therapeutic approaches to

help treat individuals with drug addictions. To better treat disorders of dopamine, it is necessary

to continue research into the specificities of dopamine signalling.

The dopamine literature has progressed significantly in recent years, particularly because

of the neuroimaging and single-cell recording technologies that have advanced and become

widely accessible. Understanding the role of dopamine signalling has become easier, but also

more nuanced. Of the three theories discussed in this review, the incentive salience hypothesis is

the most applicable in light of recent findings, particularly when compared to those that

emphasize a more general role for dopamine. Incentive salience is the idea that dopamine plays a

role in associating motivation with a rewarding stimulus; it could be argued that novel stimuli are

potentially interpreted as rewarding because of their ability to orient the individual to something

salient, and potentially physiologically relevant, in their environment.

In general, dopamine is a neurotransmitter of scientific importance. Its potential role in

integrating hedonic information, reward learning, and incentive salience into an adaptive

framework is significant. Further research into dopamine signalling can provide insight as to how

the human brain has learned to adapt to various evolutionary contexts, and what role dopamine

has played in facilitating adaptation. Further insight can also lead to more effective treatments of

dopamine disorders, which are an issue of modern relevance. Dopamine signalling research has

captivated the psychological sciences literature for decades, and will continue to lead to

incredible and elegant discoveries for years to come.


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Theories of Dopamine Signaling-A Litarature Review (Nadeem ...€¦ · THEORIES OF DOPAMINE SIGNALLING NADEEM, 2015 3 animals were given the dopamine precursor 3,4-dihydroxyphenylalanine