Neuroscience of Mindfulness: Sugar, Drugs, & Dopamine – Mindfulness, MD

Neuroscience of Mindfulness: Sugar, Drugs, & Dopamine

MACAROONS Photo Credit: via

Let’s imagine that you were to give up sugary sweets for a month like I recently did as part of a requirement for a nutrition class. The first few days might be relatively easy because you are still galvanized by the novelty of your commitment, but as the days fold themselves into weeks, your resolve will likely begin to waver. Maybe after a week, the completion of dinner prompts your mind to develop a sugary itch, imagining various potential items for dessert. Maybe during the second week, the caramels at work seem to be winking at you each time you walk past their candy jar-home, inviting you to unleash their sugary goodness on your parched taste buds. Finally, week four arrives; you hop in the car and speed off to your favorite ice cream parlor, indulging in the sultry sweet flavor of your preferred variety.

Today we will be studying why sugar, as well as many other substances, has such a hold on our mind and body. In particular we will learn about our endogenous (native to our body) stimulus-reward learning system. That is, the system that allows us to learn the link between a given stimulus (e.g. a caramel candy) and the reward that it provides (e.g. gustatory pleasure).

To understand our stimulus-reward learning system we will begin by viewing the system as it functions naturally, and then we will examine the system under the aberrant influence of substance abuse and addiction. I began the article by using the example of sugar withdrawal and craving because sugar turns out to cause the same stimulation of endogenous opioid and dopamine receptors that some substances of abuse do. Additionally, many of the neural adaptations to repeated sugar binges are also seen in chronic substance abuse. Thus, your candy bar may seem morally and ethically distinct from an illicit drug, but to your brain the difference is really only one of magnitude. (Avena, Rada, & Hoebel, 2008)

Neuroscience is progressing at such a rapid pace that by placing information in writing today I am essentially guaranteeing some degree of inaccuracy tomorrow.

I hope to buffer this danger by drawing from a multitude of research material as well as by utilizing a certain degree of creative license.

Those individuals who have read my previous Neuroscience of Mindfulness posts will know that I use nicknames to indicate the role of a particular neuroanatomical structure (for example, the medial prefrontal cortex mPFC/“Emotional Sensor”). These nicknames are meant to be both accurate and purposefully vague. Accurate in that the nickname attempts to summarize a central role of the neuroanatomical structure in the brain and vague because any given structure has many functions and any given function has many more structures that participate in it.

Thus, I hope that by maintaining a degree of ambiguity, these structure-nickname pairs will serve to familiarize readers with scientifically esoteric nomenclature while retaining the capacity to absorb evolving scientific knowledge.

With this disclaimer in mind let us now turn to the stimulus-reward learning system. For simplicity’s sake, some structures will be omitted while others will be oversimplified. I will do my best to include a reference to these omissions so that the interested reader can learn more if desired.

To begin our discussion of reward we must start with the two most basic units of the brain: neurons and glial cells. The brain is made up of approximately equal parts neuron and glial cell. Glial cells provide support for, and participate in, the general maintenance of the nearly 86 billion neurons that make up the information processing networks of the brain. We will study the neuron in great detail over the ensuing paragraphs because these key cells generate the chemical and electrical signals that produce our cognitive and emotional experience. (Azevedo et al., 2009)

NEURON By BruceBlaus (Own work) [],

Neurons consist of multiple dendrites, a cell body, and an axon. Neurons “talk” to one another through electrical and chemical signals. Neuronal transmission begins with a depolarization that triggers an action potential, a sort of biological electrical current. The action potential travels down the axon and causes the release of neurotransmitters stored in vesicles in the axon terminal. These neurotransmitters diffuse across the synaptic space between the axon terminal of one neuron and the dendrites of another, binding to receptors on the post-synaptic neuron (there are some exceptions to this axon to dendrite synapse formation that we will not consider).

The post-synaptic neuron will either depolarize and fire an action potential of its own or be inhibited into silence depending upon the sum excitatory and inhibitory qualities of the neurotransmitters bound to its various receptors. (Paxinos & Mai, 2004)

Neurotransmitters are biological substances that come in many different forms. For our purposes we will be focusing primarily on the neurotransmitters key to the central nervous system (the brain and spinal cord): the amines, amino acids, and peptides.

ACTION POTENTIAL By OpenStax College [],

Neurons have a resting electrical potential of about -70 millivolts (mV). Neurotransmitters bind to specific ion channels and secondary messenger receptors on post-synaptic neurons, inducing a net change in the resting electrical potential. If this change moves the neuron towards 0 mV (more positive) it is referred to as a depolarization, while a change in the negative direction is known as a hyperpolarization. If a neuron is sufficiently depolarized, an action potential will be triggered. Hyperpolarized neurons are much more difficult to depolarize, thus hyperpolarization inhibits action potentials. (Baynes & Dominiczak, 2014)

Neurotransmitters are broadly referred to as excitatory (tending to cause depolarization) or inhibitory (tending to cause hyperpolarization). The net excitatory and inhibitory neurotransmitters influence on a post-synaptic neuron determines whether or not an action potential is triggered.

SYNAPSE By Nrets at en.wikipedia [GFDL or ],

To ensure that the synapse does not become overrun with neurotransmitters, pre-synaptic neurons have reuptake pumps that pump free neurotransmitters back into the axon terminal to be recycled. One such reuptake pump known as the dopamine transporter (DAT) will become important in later discussions. There are also enzymes in the synapse and the axon terminals that breakdown unused neurotransmitters, thereby inactivating them. (Baynes & Dominiczak, 2014)

The main excitatory neurotransmitter in the brain is the amino acid glutamate. While the main inhibitory neurotransmitter is another amino acid known as gamma-amino butyric acid, or GABA for short. (Paxinos & Mai, 2004)

Unfortunately for scientists, many neurotransmitters do not fit neatly into an excitatory or inhibitory classification system. One such classification-averse neurotransmitter (technically a neuromodulator) is an amine known as dopamine. As a point of interest, other neurotransmitters in the amine family include such well-known chemicals as acetylcholine, norepinephrine, epinephrine, and serotonin. But before we turn to the dopaminergic star of today’s show, we have to quickly mention one final group of neurotransmitters: the peptides. In particular, we will look briefly at the neuropeptides endorphin and enkephalin.

Endorphin and enkephalin are part of our endogenous opioid system. Endogenous opioids are inhibitory neurotransmitters that are integral to our pain modulation pathways as well as the euphoric experience associated with opiate abuse.

Opioids have a wide range of effects in the brain. Despite their inhibitory nature, opioid receptors often act to inhibit an inhibitor, an action known as disinhibition. Opioid disinhibition actually activates a neuron further on down the transmission chain. The exact details are less important than the basic knowledge of the pain-relieving and subjective euphoria-causing properties of endogenous opioids. (McMahon, Koltzenburg, Tracey, & Turk, 2013)

Now let’s return to dopamine. The monoamine dopamine is an important neurotransmitter involved in such wide-ranging systems as movement, emotion, reward, and learning. Dopamine binds to post-synaptic neurons at two different receptor sites: D1-like receptors and D2-like receptors. Both families of receptors act through a slow second-messenger pathway involving cyclic adenosine monophosphate (cAMP). D1-like pathways increase cAMP while D2-like pathways decrease cAMP. cAMP itself has a complex mechanism of action that we will not examine today. For our purposes, we will learn about dopamine by examining its effects on a larger scale. (Stern, Rosenbaum, Fava, Biederman, & Rauch, 2008)

DOPAMINE By Cacycle (Own work) [, or Public domain],

There remains a longstanding misconception that dopamine is a so-called “pleasure molecule,” producing the experience of pleasure associated with the consumption of stimuli such as food, sex, or drugs. In fact, dopamine acts at a more basic level by indicating the incentive salience of a stimulus (McClure, Daw, & Montague, 2003).

Incentive salience refers to the want we feel towards a particular stimulus. A want for a stimulus is distinct from the pleasure (reward) gained from obtaining said stimulus. Wants motivate an organism to use the “action-selection” networks in the brain to deploy the behavior needed to acquire the stimulus. The pleasure that we enjoy after obtaining and experiencing the stimulus is a product of a highly diverse set of neuroanatomical structures that are beyond the scope of today’s article. (Schultz, 2002)

Rather than producing pleasure, dopamine functions as a “motivating” neurotransmitter in the brain. It is released in amounts proportional to the value of a given stimulus. We will thus nickname dopamine (DA) “Motivation.”

DA/“Motivation” makes quantitative distinctions between stimuli rather than qualitative ones. That is to say that if an apple and an orange are equally valued by an individual, then the amount of dopamine released in response to the consumption of either fruit will be the same despite the qualitative differences in taste profiles. Dopamine’s role in behavior and learning will hopefully be clarified when we turn to the larger dopaminergic pathways in the brain later in this article. (McClure et al., 2003)

Aberrant DA/“Motivation” systems have long been hypothesized to play a role in psychotic illnesses. Psychosis is a broad term referring to a syndrome that often consists of, among other symptoms, hallucinations and delusions. Patients with schizophrenia, bipolar disorder, major depressive disorder, and many other psychiatric disorders can all manifest the symptomatology of psychosis. With our new knowledge of the role that DA/“Motivation” plays in the brain we can briefly examine the proposed mechanisms behind psychosis.

Psychosis is often treated with a class of drugs known as antipsychotics. Antipsychotics were first discovered in the 1950s and treat psychosis by, among other mechanisms, blocking the D2 receptor (a receptor for DA/“Motivation” found in the brain). Psychotic illnesses are hypothesized to be precipitated by an overactivity in the DA/“Motivation” system (among many other causative factors). Thus, D2 receptor-blocking antipsychotics are thought to relieve psychotic symptomatology by mitigating this abnormal activity.

Let’s examine the role of DA/“Motivation” in delusions, one of the many symptoms that make up the psychotic syndrome. Delusions are beliefs that are firmly held despite contradictory evidence from objective reality. For example, a common delusion involves a patient’s belief that an unidentified nefarious character is following them. Let’s study this delusion with our knowledge of DA/“Motivation” physiology in mind.

Imagine that a patient suffering from psychosis sees a few different men wearing white shirts throughout the course of a day. An individual who is not suffering from a psychotic illness might shrug this occurrence off as reflecting the popularity of white shirts, but a patient suffering from psychosis is not as biologically fortunate. The patient has an overactivity of DA/“Motivation” that identifies not only objectively significant but also insignificant stimuli as being highly important. Thus, the patient suffering from a psychotic illness ascribes a high level of salience to the white-shirted entities. (Kapur, 2003)

WHITE SHIRT Photo Credit: via

With the white-shirted individuals firmly tagged with the DA/“Motivation” importance signal, the patient’s cortex must construct a believable story to explain why these white-shirted folks are so important. Out of this explanatory process may arise the conviction that the seemingly separate white-shirted individuals were, in actuality, the same person. Furthermore, the cortex may reason that the patient keeps seeing this same individual because they are following the patient.

Let’s come back to the brain’s endogenous stimulus-reward learning system and investigate a little further.

Two areas in the brain that contain a very high density of DA/“Motivation”-releasing neurons are the substantia nigra and the ventral tegmental area. There are three major DA/“Motivation” tracts that originate from these two areas: the nigrostriatal tract, the mesolimbic tract, and the mesocortical tract. A fourth pathway that we will ignore connects the hypothalamus/“Cruise Control” to the pituitary gland and is known as the tubero-infundibular tract. Of these four tracts, we will be primarily concerned with the mesolimbic and mesocortical tracts. (Kaufman & Milstein, 2012)

Each tract is named for its origin and destination; i.e. the nigro-striatal tract originates in the substantia nigra and projects to the striatum (basal ganglia/“Pattern Generator”). Thus, the 2 tracts of primary interest for today’s discussion have the same meso (meaning “middle”) origin, indicating that their mutual origin is in the region of the midbrain known as the ventral tegmental area (VTA).   If we describe DA as the “Motivation” of the brain, then we will refer to the VTA as the “Motivator” because of its role in the production and release of DA/“Motivation.”

We will consider the mesolimbic and mesocortical pathways together because the brain is so interconnected as to render complete intellectual dichotomization of any two networks a nearly impossible and extremely confusing task.

As touched on in previous paragraphs, the VTA/“Motivator” contains an abundance of DA/“Motivation”-releasing neurons. When these neurons depolarize, action potentials travel upwards along axons that project to various parts of the brain. When action potentials arrive at the axon terminals they cause the release of DA/“Motivation” from pre-synaptic vesicles into the synapse. DA/“Motivation” diffuses across the synapse and binds to receptors on the post-synaptic neuronal receptors.

We will simplify the pathway by treating it as bidirectional and interconnected so as to avoid the complications inherent in parsing out various fiber projections. Additionally, we will omit structures that are not required for our subsequent discussion. I have chosen to simplify the discussion because I have found that the level of intellectual clarity is often inversely related to the level of detail; and for the non-neuroscientist, clarity is paramount.

Of the VTA/“Motivator’s” projections we will consider three primary destinations. The first VTA/“Motivator” destination that we will consider is the projection to a structure known as the nucleus accumbens. The nucleus accumbens are paired nuclei found in the basal forebrain and are a central part of a group of structures integral to reward known collectively as the ventral striatum. (Haines, 2012)

The nucleus accumbens is theorized to connect a given stimulus to the reward associated with its consumption or performance. Thus, the nucleus accumbens provides our ability to learn that the caramel is connected to the pleasurable experience of eating it. We will nickname the nucleus accumbens (NAcc) the “Connector.” (Sescousse, Caldú, Segura, & Dreher, 2013)

Next up, we see that the VTA/“Motivator” projects to the amygdala/“Emoter.” We have discussed the amygdala/“Emoter” many times in previous articles, always focusing on the role it plays in negative emotion. As with most things, the closer one looks at the amygdala/“Emoter” the more complex it becomes.

The amygdala/“Emoter” turns out to be involved in both negative and positive emotions. The activity of the amygdala/“Emoter” is not correlated with the type of emotion, but it is instead correlated with the intensity of the emotion. The amygdala/“Emoter” shows increased activity in relation to the salience (intensity) not the valence (emotional quality) of an emotion. This means that sadness (valence) is not associated with greater activation of the amygdala/“Emoter” than happiness; only the intensity of the respective emotions predicts the degree of amygdala/“Emoter” activation. In other words, the amygdala/“Emoter” paints in all colors of emotion, only varying the weight of its brush stroke based on intensity. (Sescousse et al., 2013)

The last projection of the VTA/“Motivator” that we will consider is to the ventromedial prefrontal cortex and the orbitofrontal cortex. The ventromedial prefrontal cortex is a subdivision of the medial prefrontal cortex (mPFC/“Emotional Sensor”) that has played such a central role in many of my previous articles. The orbitofrontal cortex is a portion of the prefrontal cortex that is found on the underside of the frontal lobes, directly above the orbits (eye sockets).

The ventromedial prefrontal cortex is involved in mental reasoning about the self and others while the orbitofrontal cortex is involved in evaluating potential costs or benefits of a decision (Barbey, Krueger, & Grafman, 2009). For the purposes of today’s discussion we will use the mPFC/“Emotional Sensor” as an umbrella term to refer to the ventromedial prefrontal cortex and the orbitofrontal cortex. While not entirely anatomically or functionally accurate, the orbitofrontal cortex does involve the medial portion of the prefrontal cortex, and so our anatomical indiscretion may be forgiven.

DA/”MOTIVATION STIMULUS-REWARD LEARNING PATHWAY By Cacycle (Own work) [, or Public domain],

In summary, the VTA/“Motivator” projects DA/“Motivation”-releasing axon terminals to the NAcc/“Connector,” the amygdala/“Emoter,” and the mPFC/“Emotional Sensor.”

Now that we have summarized the DA/“Motivation” stimulus-reward learning system, let’s examine the set of structures involved in generating and remembering our experience of a given stimulus. We will refer to these structures collectively as forming an “Experiencing Network.”

The Experiencing Network begins with our perception of the environment courtesy of our sense organs (eyes, ears, nose, mouth, and touch-sensitive nerve endings). Our sense organs provide us with our ability to see, hear, smell, taste, and touch the objects that make up our external environment. A sixth sense is generated by our ability to imagine and mentally construct ideas, environments, and scenarios based on previous experience. These six senses are the portal to our outside world.

The experience of our inside world is provided by a structure known as the insula/“Internal Sensor” (among others). The insula/“Internal Sensor” allows us to sense our internal bodily states (e.g. the sensation of our heart beat, breathing, or grumbling stomach). Importantly, this information is sensed at a preconscious level and preempts our cognitive elaboration. Internal bodily states are often experienced as an emotional “feel” because of this preconscious nature. When we’re anxious, part of the reason that we know we are anxious is that our insula/“Internal Sensor” has provided us with the preconscious experience of a tightened stomach, racing heart, and thirst for air. (Sescousse et al., 2013)

LATERAL VIEW OF THE BRAIN

The raw, sensate informational packets gathered from our external and internal environments are passed along to the cortex, which makes up the outer layer of the brain and is involved in information processing. The cortex then constructs a meaningful “story” of our experience from the raw sensory data. Cortical structures involved in this interpretation and production of our conscious experience include structures that we have previously discussed such as the mPFC/“Emotional Sensor,” the somatosensory cortex/“External Sensor,” as well as many other structures that we have not.

The mPFC/“Emotional Sensor” is the primary interpretative structure that we will consider today. The mPFC/“Emotional Sensor” produces our conscious experience of the emotional and factual components of a situation based on the sensory and emotional information it receives. Our sense organs provide the details of the setting, stimulus, and reward while the preconscious bodily sensations from the insula/“Internal Sensor” are interpreted as an emotional “feel” by the mPFC/“Emotional Sensor.” The amygdala/“Emoter” adds a final sprinkle of emotional flavor to the now conscious experience. Whether it is a dash of raw joy or a hint of primal fear, the amygdala/“Emoter” makes sure that the mPFC/“Emotional Sensor” is aware of the intensity of the emotional milieu.

MEDIAL BRAIN

This cognitive narrative is simultaneously recorded into memory by the hippocampus (HCMP/“Memorizer”) and the amygdala/“Emoter.” We have discussed the HCMP/“Memorizer” and its role in generating memories in previous articles. We will briefly revisit how the amygdala/“Emoter” and the HCMP/“Memorizer” work together to form memories.

If a memory were a painting, then the HCMP/“Memorizer” would sketch the black and white outline of the event while the amygdala/“Emoter” would color the remembered experience with an emotional brush. Thanks to the HCMP/“Memorizer” and the amygdala/“Emoter,” our memories are full of emotional and contextual detail of the remembered past event.

As we can see, the DA/“Motivation” stimulus-reward learning system intersects at many points along our Experiencing Network. These intersections are key to understanding how we learn about stimuli and rewards.

Before we complete the picture we need to add one more layer to the DA/“Motivation” stimulus-reward learning system. At this point you may be wondering, “What exactly triggers the release of DA/“Motivation?” There is a two-part answer to this critical question.

First, we need to understand the difference between tonic and phasic activity. A tonic process is one in which there is a constant, low-level of activity. While a phasic process consists of intermittent peaks and valleys, often triggered in response to a certain stimulus. If a tonic process were like a ball rolling slowly down a never-ending hill, then a phasic process would be like a ball being intermittently kicked along a field by a recurring stimulus.

The VTA/“Motivator” is normally tonically active, meaning that it always produces a baseline low-level of DA/“Motivation” discharge. While tonic activity of the DA/“Motivation” system is required for survival, it turns out that phasic (intermittent) DA/“Motivation” activity is necessary for the learning of stimulus-reward pairings.

Unfortunately, here is where the picture gets a little murky (or murkier). Common sense would suggest that our DA/“Motivation” stimulus-reward learning system would respond proportionally to the inherent value of a given reward. Regrettably, this logical assumption is incorrect. Instead, the degree of activation of the DA/“Motivation” stimulus-reward learning system is determined by something called “prediction error” (McClure et al., 2003). Prediction error refers to the difference between the expected value and the actual value of a predicted stimulus-generated reward (McMahon et al., 2013).

This means that the degree of phasic (intermittent) activation of the DA/“Motivation” stimulus-reward learning system depends on the novelty of a reward and not on the inherent quality of it.

Let’s look at an example to clarify this key concept.

DA/”MOTIVATION” STIMULUS-REWARD LEARNING PATHWAY

Imagine that you have a favorite bakery that makes the most unbelievable scone (my personal favorite member of the pastry family). The first time you found this bakery the expected value (reward) of the scone (stimulus) you purchased was low because you expected just another run of the mill scone. But when you took your first bite and the sweet, buttery flavor greeted your unprepared taste buds, the actual value of the scone was revealed to far exceed the expected value. Thus, your first encounter with your new favorite bakery’s scone produced a large prediction error and a proportionally large phasic activation of the VTA/“Motivator” and the DA/“Motivation” stimulus-reward learning system.

As an evolutionary side note, the DA/“Motivation” stimulus-reward learning system evolved so that our ancestors could learn novel associations swiftly. The first time your ancestor found a red berry that was sweet instead of the bitter he or she expected, the VTA/“Motivator” inundated the brain with DA/“Motivation” to make sure red berry = delicious calorie source. Once the association was learned, DA/“Motivation” could back off (courtesy of an equilibration between expected and actual reward value), allowing the memory and cortical systems to take over the knowledge of the arboreal treat.

SCONE Photo Credit: via

Returning now to your favorite pastry shop, let’s imagine that a few months have passed and your dedication to this wonderful bakery has provided you with many experiences of the magical scone. Now when you order your scone, the expected value of the pastry is high and roughly equals the actual value when you take a bite. As a result, the prediction error is extremely small, and the resultant phasic release of DA/“Motivation” is proportionally small, or even absent altogether. (McClure et al., 2003)

This example is somewhat complicated by the intrinsic DA/“Motivation”-stimulating capacity of sugar, but for our purposes we will ignore this (Avena et al., 2008). Also we should note that your continued enjoyment of your sugary scone despite the lack of phasic DA/“Motivation” release is made possible by your sense organs, cognitive networks, and endogenous opioid system. We must remember that DA/“Motivation” is not the pleasure neurotransmitter perpetuated in popular culture.

Let’s examine one final wrinkle before we exhaust our discussion of the now legendary scone. Maybe the head baker is on vacation and you purchase a substandard scone made by an unworthy apprentice. Now your expected value is higher than the actual value of the scone and the prediction error is negative. Not only does your VTA/“Motivator” fail to release a phasic dose of DA/“Motivation,” but also your baseline tonic DA/“Motivation” activity actually transiently decreases. If this tonic dip below baseline occurs too many times in response to bad scones you will learn a new aversion to the once celebrated bakery.

Let’s review this scenario and include all of the structures we have discussed so far.

The sights, sounds, and smells of the bakery likely dominated your perception the first time you walked through its doors. All of this raw data regarding the bakery environment gathered by your internal and external sensory structures was then arranged into an intelligible, conscious story by the mPFC/“Emotional Sensor.” And as time passed, the HCMP/“Memorizer” and amygdala/“Emoter” continually recorded your experience into memory.

The first time you tasted your soon-to-be favorite scone, the large prediction error triggered an equally large release of DA/“Motivation” from your VTA/“Motivator.” The DA/“Motivation” impacted three important structures within the DA/“Motivation” stimulus-reward learning system. The DA/“Motivation” release in the NAcc/“Connector” connected the scone, the ongoing black and white memory of the bakery environment, and the rewarding consummatory experience. The VTA/“Motivator’s” axonal projections then arrived at the amygdala/“Emoter,” spilling DA/“Motivation” into the synapse and coloring the affective component of the HCMP/“Memorizer”-generated memory as highly salient.

As you ate your scone, your insula/“Internal Sensor” generated wonderful bodily undertones of the consummatory experience that were dutifully passed along to your mPFC/“Emotional Sensor.” The mPFC/“Emotional Sensor” gathered all of the aforementioned data points to create your seemless conscious experience of the bakery and the heavenly scone. Finally this conscious experience was marked as extremely salient by the final projection from the VTA/ “Motivator” and the DA/“Motivation” stimulus-reward learning system to the mPFC/“Emotional Sensor” itself.

EXPERIENCING NETWORK WITH ACCOMPANYING MEMORY FORMATION

Thus, through a concert of networks and structures, the new bakery was learned to connect to the reward of this heavenly sconal experience.

Now that we have completed our review of the more or less “natural” reward of a scrumptious pastry, let’s turn to the pathological reward associated with substance abuse.

Medicinal and recreational substance use has been around for at least 9 millennia (McGovern et al., 2004). We sometimes conceive of substance use as being a modern phenomenon, but humans have been exploiting their neurobiology and augmenting their stimulus-reward learning system for many thousands of years. However, it is only recently that we have been able to describe the mechanisms of the various substances with which our species partakes.

Substances of abuse have many different mechanisms for creating the “high” associated with their use. This high is made possible by the substance’s activity at the neuronal level.

America’s favorite drug, alcohol, potentiates the inhibitory amino acid neurotransmitter GABA by binding to the GABA receptor. This increased inhibition produces an anxiety-relieving effect similar in sensation and mechanism to benzodiazepines such as Ativan, Xanax, or Valium.  Alcohol does not limit its action to the GABA receptor.  Alcohol is hypothesized to stimulate opioid systems, inhibit glutamate pathways, and affect a wide-range of sites throughout the brain.

Opiates, derived from the opium plant, are perhaps the oldest family of non-alcoholic drugs known to man. The opiate family includes drugs such as heroin, Oxycontin, and Vicodin to name a few (Vicodin also contains acetaminophen, the active ingredient in Tylenol). Opiates of abuse bind to the opioid μ-receptor, which through a net inhibitory process produces a subjective experience of euphoria, pain relief, and drowsiness. Unfortunately, inhibition of pain and anxiety are not opiates’ only effects; they also inhibit breathing at higher doses, making opiates very dangerous in overdose.

Marijuana contains many psychoactive chemicals, but the primary chemical, δ-9-tetrahydrocannabinol (THC) acts on cannabinoid (CB) receptors. CB receptors normally allow the binding of the endogenous chemical anandamide. When THC binds to the CB receptor, the second messenger cAMP is reduced and this in turn decreases the general excitability of the brain. This inhibitory action of THC at CB receptors produces the euphoric and anxiety-reducing effects of marijuana use.

Stimulants include drugs like amphetamines and cocaine. Both drugs act at the DA/“Motivation” transporter (DAT). But each drug has its own unique effect on DAT. DAT normally functions as a reuptake pump to remove unused DA/“Motivation” from the synapse. Cocaine blocks DAT (along with serotonin and norepinephrine reuptake transporters), stopping the reuptake of DA/“Motivation” and causing a build up of DA/“Motivation” in the synapse. Amphetamines are structurally similar to DA/“Motivation” so they trick DAT into taking them up into the pre-synaptic axon terminal while simultaneously making DAT “leaky” and thus amenable to the bidirectional movement of DA/“Motivation” (normally DA/“Motivation” only moves in to the axon terminal through DAT). Once inside, amphetamines displace DA/“Motivation” from their pre-synaptic vesicles. The combination of a now leaky DAT and the displacement of endogenous DA/“Motivation” lead to the release of DA/“Motivation” into the synapse through DAT. Thus, both cocaine and amphetamines cause a net increase in DA/“Motivation” (along with norepinephrine and serotonin) through different mechanisms of action. (Haines, 2012)

Despite their disparate mechanisms of primary action, all addictive drugs increase the release of DA/“Motivation.” Alcohol, opiates, and marijuana may act on remote receptors, but these initial actions cause the inhibition of normal inhibitory control (disinhibition) of the VTA/“Motivator,” thus increasing its release of DA/“Motivation.” In fact, researchers believe that for a substance to be addictive it must activate the DA/“Motivation” system. (Cecil, 2012)

Let’s use amphetamines as a prototypical substance of abuse to investigate why exogenous substances are so different from natural stimulus-reward pairs.

The first time an individual consumes amphetamines the series of rewarding events he or she experiences is very similar to our experience with the scone, with one additional layer that we will turn to shortly.

The actual value likely far exceeded the expected value the first time our hypothetical individual used amphetamines, and so the prediction error was quite large. This large prediction error translated into a large flood of DA/“Motivation” from the VTA/“Motivator” into the NAcc/“Connector” and amygdala/“Emoter.”

The sense organs generated the raw data of the external drug-taking experience while the insula/“Internal Sensor” added its own bodily flavor of the internal experience. These unrefined informational packets were then delivered to the mPFC/“Emotional Sensor” along with the affective component of the experience courtesy of the amygdala/“Emoter.” The mPFC/“Emotional Sensor” organized all of these informational packets into an orderly conscious experience of the high, attaching a large degree of salience to the experience thanks to the healthy dose of DA/“Motivation” from the VTA/“Motivator” delivered to the mPFC/“Emotional Sensor.” Simultaneously the conscious experience was recorded into memory in full color by the amygdala/“Emoter” and HCMP/“Memorizer.”

This may seem very familiar from our bakery discussion in earlier paragraphs. Unfortunately, we cannot stop here. In addition to this “natural” cascade of stimulus-reward learning, amphetamines play a nasty trick on the brain.

Amphetamines act directly on the VTA/“Motivator” (among other places) to directly release large amounts of DA/“Motivation.” Thus, not only do amphetamines stimulate the “natural” side of reward learning through prediction error, but they also adulterate the system and make it impervious to the natural prediction error decay.

The DA/“Motivation”- producing effects of natural environmental rewards slowly decay as the expected value approaches the actual value just like with our scone. The more times we visit the bakery, the more accurate our predictions of value become, and before long there is no prediction error to generate a DA/“Motivation” release. But amphetamines, along with other addictive drugs, will continue to stimulate large amounts of DA/“Motivation” release every time they are consumed no matter how similar the expected and actual values become.

SUBSTANCE ABUSE & THE DA/”MOTIVATION” STIMULUS-REWARD LEARNING PATHWAY

In fact, even if the high is subjectively unpleasant, the DA/“Motivation”-stimulating properties of the drug will ensure that the experience is still recorded as rewarding. (Sescousse, 2013)

Further complicating the picture is the brain’s adaptation to the increased DA/“Motivation” levels caused by the amphetamine abuse. Over time the brain adapts by desensitizing the entire DA/“Motivation” stimulus-reward learning system, downregulating both the DA/“Motivation” receptor density as well as the production of DA/“Motivation.”

Thus, the amphetamine-adapted brain has a lower tonic level of DA/“Motivation” and prefers amphetamines to natural rewards. Previously reward-stimulating activities such as socializing with family and friends, exercise, and eating become secondary to the use of the addictive substance.

As we can see, substance abuse has a whole litany of negative biological, social, and emotional consequences. The journey from addiction to sobriety is one measured in large time intervals, and in the interest of concluding an already long article, we will skip ahead to the recovery process. The choice to begin the recovery process is very rarely based on a single event, and instead represents the summation of many small and large events. Also, recovery is rarely defined by a single, successful bid at sobriety. Instead, recovery is very often punctuated by multiple periods of abstinence and relapse that are variable in duration and intensity.

Hopefully now we can better appreciate the complexity of the recovery process with our new knowledge of the DA/“Motivation” stimulus-reward learning system. Despite the challenges of recovery, millions of patients enjoy a sustained sobriety as a result of a lot of hard work and support. And as the length of sobriety increases, the brain slowly heals itself (with most drugs of abuse).

I will often tell my patients that getting sober is easy; it’s recovery that is hard. I say this tongue-in-cheek because no part of giving up an addiction is easy, but the saying highlights a key issue. When a patient is in the process of sobering up from whatever substance he or she abused there are plenty of reminders as to why that person should get sober. These reminders come in the form of withdrawal symptoms.

Withdrawal is a clinical phenomenon that can be simplistically understood as the reverse of the substance-induced state. Euphoria is replaced by despair, increased appetite is replaced by nausea, and sedation is replaced by insomnia (to name a few of the common withdrawal symptoms). In the early stages of recover, the profoundly uncomfortable symptoms of withdrawal serve as a constant reminder of the dangers of substance abuse and motivate the patient to maintain sobriety.

The challenge for many patients comes when they start to feel better and enter the indefinite recovery stage. After the withdrawal symptoms have abated, all of the profoundly unpleasant sobriety motivators disperse and the patient is left with all of the old reasons why he or she might have used in the first place (i.e. anxiety, sadness, etc.). Additionally, all of the DA/“Motivation” stimulus-reward learning from previous drug abuse is still strongly wired into the neuronal architecture of the brain.

While the patient was still abusing a given substance, the DA/“Motivation” stimulus-reward learning pathway linked the environments, paraphernalia, and even friends (stimuli) to the substance-induced high (reward). Thus, just as the pastry aficionado learned to associate the fabled bakery with an amazing scone, so too does the patient with a history of substance abuse link the environments, paraphernalia, and friends he or she used with to an impending high. This strong DA/“Motivation” link produces the craving response that patients experience when they return to old environments or friends he or she used with.

Importantly, these triggers are gradually unlearned over time as a patient is exposed to various previously triggering stimuli without succumbing to the urge to use. Thus, the same biological system that so strongly linked drug abuse to reward can be rewired over time to support an abstinent brain.

Recovery is a process of redefinition and unflinching self-inquiry; it requires giving up a large part of the past and opening oneself up to an uncertain future. Old habits must be relinquished and both physical and social environments must be changed.

Despite the difficulties, if a patient is able to “get clean,” then time is a powerful ally in maintaining his or her sobriety. A patient’s chance of relapse decreases from a high of over 60% with only one year of sobriety to less than 15% with five years of sobriety (Dennis, Foss, & Scott, 2007). With each passing year, patients abandon old habits and learn new ways of coping with the stresses inherent to their internal and external environment that had previously drove them to abuse substances.

We have traveled our own long path from sugar addiction, to amphetamine abuse, and at long last, on to recovery. I hope that the neuroscience of reward has been an interesting view under the hood of our deepest desires and cravings. As always, it is my hope that by elucidating the biology of our brains we can gain the distance necessary to reclaim control of our faculties.

Instead of imagining sugar or drug addiction as a moral failing, it is my hope to reframe addiction as an unfortunate permutation of our biological stimulus-reward learning system. Because when we get our moral judgments out of the way and approach the problem logically, we can use the same biological system to free ourselves from the grips of reward addiction.

 

REFERENCES

Avena, N. M., Rada, P., & Hoebel, B. G. (2008). Evidence for sugar addiction: behavioral and neurochemical effects of intermittent, excessive sugar intake. Neuroscience & Biobehavioral Reviews, 32(1), 20-39.

Azevedo, F. A., Carvalho, L. R., Grinberg, L. T., Farfel, J. M., Ferretti, R. E., Leite, R. E., … & Herculano‐Houzel, S. (2009). Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled‐up primate brain. Journal of Comparative Neurology, 513(5), 532-541.

Baynes, J., & Dominiczak, M. H. (2014). Medical Biochemistry: with STUDENT CONSULT Online Access. Elsevier Health Sciences.

Barbey, A. K., Krueger, F., & Grafman, J. (2009). Structured event complexes in the medial prefrontal cortex support counterfactual representations for future planning. Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1521), 1291-1300.

Cauda, F., Cavanna, A. E., D’agata, F., Sacco, K., Duca, S., & Geminiani, G. C. (2011). Functional connectivity and coactivation of the nucleus accumbens: a combined functional connectivity and structure-based meta-analysis. Journal of cognitive neuroscience, 23(10), 2864-2877.

Cecil, R. L. F. (2012). Goldman’s Cecil Medicine, Expert Consult Premium Edition–Enhanced Online Features and Print, Single Volume, 24: Goldman’s Cecil Medicine (Vol. 2). L. Goldman, & A. I. Schafer (Eds.). Elsevier Health Sciences.

Dennis, M. L., Foss, M. A., & Scott, C. K. (2007). An eight-year perspective on the relationship between the duration of abstinence and other aspects of recovery. Evaluation Review, 31(6), 585-612.

Gussow, L. (2013). Toxicology Rounds: Opium, from Ancient Sumeria to Paracelsus to Kerouac. Emergency Medicine News, 35(4), 25.

Haines, D. E. (2012). Fundamental Neuroscience for Basic and Clinical Applications: with STUDENT CONSULT Online Access. Elsevier Health Sciences.

Hyman, S. E., Malenka, R. C., & Nestler, E. J. (2006). Neural mechanisms of addiction: the role of reward-related learning and memory. Annu. Rev. Neurosci., 29, 565-598.

Johnstone, E. C., Owens, D. C., & Lawrie, S. M. (2010). Companion to psychiatric studies. Elsevier Health Sciences.

Kapur, S. (2003). Psychosis as a state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia. American Journal of Psychiatry, 160(1), 13-23.

Kaufman, D. M., & Milstein, M. J. (2012). Kaufman’s Clinical Neurology for Psychiatrists. Elsevier Health Sciences.

Kober, H., Barrett, L. F., Joseph, J., Bliss-Moreau, E., Lindquist, K., & Wager, T. D. (2008). Functional grouping and cortical–subcortical interactions in emotion: A meta-analysis of neuroimaging studies. Neuroimage, 42(2), 998-1031.

Kühn, S., & Gallinat, J. (2012). The neural correlates of subjective pleasantness. Neuroimage, 61(1), 289-294.

McClure, S. M., Daw, N. D., & Montague, P. R. (2003). A computational substrate for incentive salience. Trends in neurosciences, 26(8), 423-428.

McGovern, P. E., Zhang, J., Tang, J., Zhang, Z., Hall, G. R., Moreau, R. A., … & Wang, C. (2004). Fermented beverages of pre-and proto-historic China. Proceedings of the National Academy of Sciences of the United States of America, 101(51), 17593-17598.

McMahon, S., Koltzenburg, M., Tracey, I., & Turk, D. C. (2013). Wall & Melzack’s Textbook of Pain: Expert Consult-Online. Elsevier Health Sciences.

Nolte, J. (2009). The human brain: An introduction to its functional anatomy. Elsevier Health Sciences.

Otto, M. W., O’Cleirigh, C. M., & Pollack, M. H. (2007). Attending to emotional cues for drug abuse: Bridging the gap between clinic and home behaviors.

Paxinos, G., & Mai, J. K. (2004). The human nervous system. Academic Press.

Phan, K. L., Wager, T., Taylor, S. F., & Liberzon, I. (2002). Functional neuroanatomy of emotion: a meta-analysis of emotion activation studies in PET and fMRI. Neuroimage, 16(2), 331-348.

Sescousse, G., Caldú, X., Segura, B., & Dreher, J. C. (2013). Processing of primary and secondary rewards: a quantitative meta-analysis and review of human functional neuroimaging studies. Neuroscience & Biobehavioral Reviews, 37(4), 681-696.

Schultz, W. (2002). Getting formal with dopamine and reward. Neuron, 36(2), 241-263.

Squire, L. R. (Ed.). (2013). Fundamental neuroscience. Academic Press.

Stern, T. A., Rosenbaum, J. F., Fava, M., Biederman, J., & Rauch, S. L. (2008). Massachusetts General Hospital comprehensive clinical psychiatry. Elsevier Health Sciences.

 

 

You may also like...

Leave a Reply