Christopher T Smith.com
  • Home
  • About Me
  • Leadership
  • Reflections
  • Career Development Research
  • Neuroscience Research
  • Published Research
  • Press
  • Presentations
  • Job Search Resources
  • Funding Resources
  • Subscribe to Newsletter
  • Contact

Reflections Blog

Wanting, Liking, & Dopamine’s Role in Addiction

11/17/2020

0 Comments

 
Neuroscience

This piece originally appeared on my Life Apps Brain & Behavior Blog on October 5, 2020.
​It has been expanded on here. 
Picture
Drug addiction is a huge problem across the world, leading to large societal costs in terms of lost productivity and healthcare expenses. In the United States (US), specifically, the National Institute on Drug Abuse (NIDA) has compiled a variety of statistics illustrating the scope of the addiction problem. Economically, the estimated annual cost of all drugs of abuse (including alcohol and tobacco) is $740 billion. Drug abuse is also a prominent problem with over 11% of those over age 12 in the US reporting using illicit drugs in the past month. Alcohol and tobacco abuse is also prevalent with nearly 6% of US adults estimated to have an alcohol use disorder (where alcohol negatively interferes with their life) and 14% of US adults report currently smoking cigarettes. 
Drugs of abuse are powerfully addictive because they “hijack” biological processes put in place to ensure we continue to pursue behaviors that promote our survival. The primary biological process all drugs of abuse have in common is that their initial use results in an increase in the signaling chemical dopamine in the brain (albeit via different mechanisms based on the drug used). 
Picture
Given these data, it is not surprising that in popular culture dopamine is thought of as the “reward” signal in the brain. But what exactly does that mean?
Does dopamine=reward? 
What is a reward signal in the context of biology and the brain anyway?

Reward is a complex construct (for more see this excellent overview) but one reasonable definition is that reward refers to the fact that certain environmental stimuli have the ability to elicit approach responses, especially under biologically-based “need” conditions. Put another way: Stimuli that are desirable as a result of a biological need are “rewarding”.
​Food is rewarding when we are hungry, water when we are thirsty. 
​

Our brains are primed to learn about reward, specifically to learn what stimuli and actions in our environment will lead to obtaining outcomes that are necessary for survival - a process known as reinforcement learning. We learn certain behaviors are rewarding as they lead to us obtaining things we need to continue living.
Reinforcement learning in its most basic form involves associating a stimulus with a response that then leads to a reward. This type of learning is done by virtually all animals. For example, a lab rat can learn that when a light comes on and it presses a particular lever in a specific environment it receives a food pellet. 

It learns light + press = reward via the following constituent parts: 

Light = stimulus
Press specific lever after light = response
Food pellet = reward
And once this learned stimulus-response association is made, the stimulus itself can be perceived as “rewarding” in a process known as incentive salience (more on this later). 
Picture
Reinforcement Learning, Reward, & Addiction
Stimulus-response learning drives most of the behaviors we think of as “drug addiction” in people. When one is addicted to a drug of abuse, stimuli associated with the use of the drug (think, one’s neighborhood bar or a friend you routinely smoke with when together) can themselves drive drug use behavior. This is true even when the actual use of the drug is no longer “pleasurable” for the addicted individual. In fact, most drug addicted individuals do not find the use of their addicted drugs “pleasurable” any more. 

This is because addiction is known to progress from a binge/intoxication stage of use to a withdrawal/negative affect stage and finally to a preoccupation/anticipation stage which can then reactivate drug use. Thus, drugs are initially used because they are pleasurable but over time this shifts and individuals use drugs of abuse to relieve negative withdrawal effects and not for pleasure. And, as mentioned above, drug use can be triggered by stimuli that were associated with drug use that promote preoccupation with using the drug even in individuals trying to stop or limit their use. ​
Why does this happen? How can a drug that starts out as pleasurable lead to negative feelings of withdrawal when not used? Well, the brain is very adaptive and quickly modifies the biological environment such that there is less disturbance in dopamine (and other chemical) signaling after drug use. So, while drugs of abuse initially result in a large release of dopamine, this effect moderates with continued use. This change in responsivity to drugs of abuse is tolerance and explains why those addicted to drugs of abuse need to take larger and larger quantities to achieve the same effect. In fact, the continued use of addictive drugs results in notable changes in the brain dopamine system (see figure at right) which promotes a strong biological dependence on them. 
Picture
Continued drug use physically changes the brain's dopamine system, which can affect drug abusers' mood & behavior.
While these findings help us understand how the dopamine system acts in response to addictive drugs, we have yet to examine how the initial dopamine release to drugs of abuse maps onto “reward” and may promote continued early use that ultimately leads to addiction. ​
Does dopamine signal “reward”?
Much research has shown that dopamine does not signal “reward” (or to be more technical, pleasure) per se but rather is used in learning the various predictors of reinforcement in the environment - reinforcement learning. 

This concept of dopamine signaling reinforcement learning was most famously demonstrated by the work of Wolfram Schultz, a professor at the University of Cambridge in the UK, who recorded the firing of dopamine-producing neurons (cells) in the brain of primates receiving reinforcing juice rewards. 
​

Initially, these neurons fire to unexpected reward (juice) delivery. If a cue (tone or light) perfectly predicts the juice delivery (say 5 seconds before juice delivery), over repeated trials, Schultz found that the dopamine neurons fired in the presence of the cue (or, in psychological speech, conditioned stimulus) and not the reward. And when a reward is not followed by a stimulus previously paired with it, there is an observable dopamine “dip” locked to the time when the reward was expected to occur. See figure, below, from Schultz et al., 1997, illustrating reward prediction signaling in dopamine neurons.
Picture
Reward prediction error responses at the time of reward (right) and reward-predicting visual stimuli (left in bottom two graphs). The dopamine neuron is activated by the unpredicted reward eliciting a positive reward prediction error (blue, + error, top), shows no response to the fully predicted reward eliciting no prediction error (0 error, middle), and is depressed by the omission of predicted reward eliciting a negative prediction error (- error, bottom). From Figure 2 in Schultz, 2016 and reproduced from Schultz et al., 1997. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4826767/
This work can be distilled to the following conclusion: 
Dopamine signals predictors of rewards and not rewards themselves. 
Follow-up studies have also shown the amazing ability for dopamine-producing neurons to encode reward prediction in a scaled manner (stronger dopamine response to higher probability predictors of reward) and has resulted in perhaps the most well-accepted computational model for a biological process: the temporal difference model for reinforcement learning. ​
Wanting vs Liking and Dopamine’s Role in Perpetuating Addiction
This concept of dopamine as a reward predictor has been extended to a hypothesis around the role of incentive salience in dopamine release and how this process can lead to craving or wanting behaviors in those addicted to drugs of abuse. 

An amazing amount of work on this topic from Kent Berridge at the University of Michigan has demonstrated dopamine release is not associated with liking in the sense of a hedonic, pleasurable response but rather dopamine motivates behavior and affects how hard animals are willing to work for rewards (“wanting”). 
Picture
Picture
The processes of reinforcement learning described above naturally occur but the extra boost of dopamine release associated with taking an addictive drug further strengthens stimulus-response associations. Cues or stimuli that predict drug use can then themselves become “rewarding” and trigger wanting/craving responses in the brain as it anticipates drug use. And via other dopamine-related processes, drug use behaviors can become habitual, being guided by stimuli and the environment more than one’s active choice to use drugs. ​
While many may conflate liking with wanting and the role of “reward” in all of this, the implications around the role dopamine plays in these processes are critical, especially if one is working to develop treatments to combat drug addiction. Compulsive drug use despite negative consequences is what results in addictive drugs negatively interfering in someone’s life NOT the pleasure drug use provides. So, a better understanding of what processes mediate wanting and craving for drugs of abuse is essential as we seek to combat drug addiction. 
Picture
Dopamine release in three regions of the brain - the vmPFC, VS, and insula - was found to correlate with wanting more d-amphetamine. From Smith et al., 2016 https://pubmed.ncbi.nlm.nih.gov/27174408/
My own work has sought to understand how the release of dopamine after oral d-amphetamine administration in healthy human subjects affects the brain. We found that dopamine release correlates with participants “wanting more” (NOT “liking”) d-amphetamine in three core brain regions often associated with reward and drug-related effects: ventral striatum (VS), ventromedial prefrontal cortex (vmPFC), and insula (see image at left).
​The VS is a 
core brain hub of reward valuation along with the vmPFC. Others have also found a relationship between VS dopamine release and “wanting”. The insula is a region of the brain often associated with drug craving/wanting and, in fact, damage to this part of the brain results in a loss of craving for cigarettes in smokers. Future efforts to modulate these craving-related systems and their associated dopamine signals through interventions such as transcranial magnetic stimulation may ultimately help drug-addicted individuals effectively stop their problematic drug use. 
We are just beginning to understand the neurobiological bases of drug addictive processes but continued research into them promises the development of better treatments in the future. ​​
Concluding Thoughts
Hopefully this piece has illustrated the complex role dopamine plays in signaling reward. Research that has emerged over the last few decades using sophisticated techniques to measure brain signaling in animals and humans has implicated dopamine in reinforcement learning processes and, by extensive the incentive salience of cues associated with rewards. The role of dopamine in signaling what stimuli predict reward is hijacked and pushed into overdrive by drugs of abuse that themselves release dopamine. Thus, after repeated pairings of stimuli and drug rewards, the brain adapts to respond powerfully to drug-related stimuli and cues, prompting craving in addicted individuals. 

Not everyone is as susceptible to these dopamine-mediated learning processes, though. How individual differences in biology ultimately map onto risk for drug addiction is a matter of intense interest in the field of neuroscience but is beyond the scope of this current post. For the time being, I encourage you to explore the references below for more on the complex and nuanced role dopamine plays in reward and learning processes.   ​
References:
  • A Neural Substrate of Prediction and Reward
  • Neurobiology of addiction: A neurocircuitry analysis
  • Liking, Wanting and the Incentive-Sensitization Theory of Addiction
  • Pleasure Systems in the Brain
  • Learning, Reward, and Decision Making
  • Neural mechanisms underlying the vulnerability to develop compulsive drug-seeking habits and addiction
  • Dopaminergic Mechanisms in Actions and Habits
  • Imaging genetics and the neurobiological basis of individual differences in vulnerability to addiction
0 Comments

Stress & the Brain: How genetics affects whether you are more likely to wilt under pressure

6/18/2020

0 Comments

 
​Neuroscience
​
Adapted from a post appearing as part of my new
Brain & Behavior blog on LifeApps.
Don’t stress. Stop stressing out. Relieve your stress.
Is stress always a bad thing?
Is there any truth to the fact that some people thrive under stress? Actually, yes.
Stress & the Brain
First, when we are under stress, a variety of biological processes are taking place. Here, I am going to focus on a particular role stress can play in the brain. Under psychological stress the amygdala activates stress pathways in the brain and the hypothalamus and brainstem release high amounts of norepinephrine and dopamine. While these chemicals have a range of effects on the brain, I want to focus this discussion on how they impact the prefrontal cortex (PFC). 

The PFC is the most frontal part of the brain, sitting above our eyes. This part of the brain has seen rapid evolutionary development and is much larger in primates, including humans, than other mammals. The PFC plays a major role in planning, higher-order thinking, problem solving, and simulating/anticipating the results of actions we may or may not undertake. 
Picture
The prefrontal cortex (PFC) is the most recently evolved portion of the brain, sitting above the eyes.
The PFC is also important in cognitive control, which can be thought of as “staying on task” despite the presence of potential distractors. When you need to concentrate really hard on a complex math problem on a test, your PFC is highly engaged. A key function this brain region must undertake, then, is maintaining relevant, important information over a long enough time period for you to act on it...think holding on to the intermediate product of a mathematical formula while the next piece of information is being added (12 times 2 is 24, plus 6 is 30, and divide by three, equals 10). 

The neurotransmitters dopamine and norepinephrine play key roles in maintaining this critical information (a concept known as working memory) in the PFC. 
Picture
Molecular structure of the neurotransmitter dopamine.
Picture
Molecular structure of the neurotransmitter norepinephrine.
Dopamine, Norepinephrine, & the Prefrontal Cortex
To summarize an incredible amount of work by the likes of Amy Arnsten at Yale University and others (see also), dopamine is thought to be important in repressing the “noise” (distractions) in PFC brain circuits while norepinephrine is believed to enhance the “signal”. 

The effects of these two neurotransmitters on the PFC and ultimately behavior are nonlinear. In fact, there is much evidence that the effects of these chemicals on the brain follow an inverted-U relationship where too little or too much dopamine or norepinephrine in the PFC leads to sub/supra-optimal functioning of this area of the brain. Thus, an intermediate level of these chemicals is best for optimal PFC function. 
Stress increases the levels of dopamine and norepinephrine in the brain.
The inverted-U model for dopamine and norepinephrine effects on the PFC is important given the fact that stress increases the level of both of these chemicals in this area of the brain.
​
So, the optimal balance of dopamine and norepinephrine may be thrown off under stress. 


But, this isn’t the complete story.
Biological Differences in PFC Dopamine Signalling 
What we also know from a great deal of research is that there are biological differences in neurotransmitter signaling in the brain. More is known about how dopamine signaling varies across individuals based on their genetic variation (and see; and also), which I will focus on for the remainder of this piece.
Picture
A single nucleotide polymorphism (SNP) in the COMT gene results in a change in the amino acid structure (valine to methionine, Val to Met) of the COMT enzyme. This change results in a COMT enzyme with lower activity (act) that then breaks down dopamine (DA) and other catecholamines less efficiently. The result is higher levels of DA in the PFC.
Genetic Variation in COMT Affects PFC Dopamine Levels 
I will focus specifically on an interesting genetic variant in the COMT gene. What is COMT? It is an enzyme that helps to break down dopamine, as well as other chemicals with similar molecular structures, and regulate its level in the body and brain. A single nucleotide polymorphism (SNP) in the COMT gene (G->A DNA substitution resulting in a Val->Met amino acid variation in the protein; and denoted as the Val158Met COMT variant) results in a differential stability of the COMT enzyme, allowing it to more or less efficiently breakdown dopamine. And while COMT breaks down a variety of catecholamines, including norepinephrine, epinephrine, and dopamine, it plays a majority role in regulating dopamine levels in the PFC. Those with the COMT Val polymorphism have higher enzymatic activity and therefore lower levels of tonic PFC dopamine. In contrast, the COMT Met polymorphism results in lower COMT activity and therefore higher levels of tonic PFC dopamine. 
Picture
Schematic illustrating how variation in COMT ultimately affects dopamine (DA) signaling in the PFC.
Interestingly, this particular COMT SNP has recently evolved in humans and both polymorphisms (Val & Met) are quite common in the human population. This suggests both versions of the COMT SNP had a useful purpose, evolutionarily. One popular hypothesis for the common occurrence of these COMT variants is the Worrier vs Warrior explanation. 

Several studies (see comprehensive review here) have demonstrated that individuals with the Met version of the COMT enzyme perform well in cognitively demanding tasks but have an enhanced vulnerability to stress (worrier); they wilt under pressure. 
In contrast, individuals with the Val version of COMT have better stress resiliency (warrior). 
Picture
Picture
Stress elevates the level of catecholamines like dopamine (DA) in the PFC, resulting in a shift in where individuals with the ValVal or MetMet COMT polymorphism find themselves on the inverted-U function between PFC DA and task performance, where intermediate DA associates with optimal performance. While an individual with the MetMet polymorphism may (under certain conditions) be in the optimal range of PFC DA and task performance under normal conditions, stress pushes their DA levels into supra-optimal levels, degrading task performance. In contrast, stress-induced increases in DA may help shift those with the ValVal polymorphism closer to optimal DA levels and thus improve task performance. 
This is thought to be due to the fact Val individuals have lower tonic dopamine and that the dopamine boost that occurs under stress moves these individuals toward a more optimal level of dopamine for performing cognitively demanding tasks. To further support these points, a large study in Taiwan has shown ValVal (remember, humans have two copies of each gene, one from Mom & one from Dad) individuals perform better on a stressful, standardized test administered to 10th graders across the country each year. 

And it’s not just an effect on dopamine the Val158Met COMT polymorphism provides. Research has shown that ValVal individuals show lower physiological stress reactivity than MetMet individuals. 

Taken together, these data suggest that individuals with two copies of the Met allele will generally perform poorer under stressful conditions than those with two copies of the Val allele while those with a copy of each allele will fall somewhere in between.
Is your genotype destiny? 
Should those individuals with the Met polymorphism in their COMT gene resign themselves to doing poorly on big standardized tests; wilting under pressure? 

​The short answer? No. The long answer? We are more than our genetics.

First, our genetics interact with other aspects of our biology to ultimately produce behavior. My own research has shown that COMT genotype interacts with age to affect Now vs Later decision making. We interpreted this in context of the inverted-U relationship between dopamine and PFC function as dopamine levels are known to decline with age. So, a particular genetic setup that leads to supra-optimal dopamine levels when one is young may result in more optimal levels as one ages and dopamine “falls” down the curve toward more optimal levels. 
Picture
Dopamine levels naturally decline with age. Thus, where one's COMT genetics positions them in terms of optimal PFC function will shift over the lifespan with ValVal individuals in the above example falling out of the optimal dopamine range while those with the MetMet polymorphism may fall down into a more optimal intermediate level of PFC dopamine.
Note, that what level of PFC dopamine is "optimal" for various cognitive tasks will differ based on a variety of environmental factors. Thus, the COMT ValVal polymorphism may be more optimal in some situations and MetMet more optimal in others. 

Biology is just one part of the equation. 
​The Importance of Mindset
Mindset, or how an individual reacts to the biological changes that accompany stress, is also critical.    

It has been shown that taking a stress-is-enhancing mindset leads to better affective and cognitive outcomes than a stress-is-debilitating mindset.  
COMT genetic variation has been shown to mediate the effect of a stress-is-enhancing mindset manipulation on affect and cognition such that those with two copies of the Met allele were more responsive to the manipulation than those with two copies of the Val allele. MetMet individuals can more easily develop a stress-is-enhancing mindset.

And while your COMT genetics may affect how well mindset manipulations work, anyone can take steps to re-frame their stressful experiences in such a way as to see stress as more of a benefit than a detriment. For example, treat your stress as something you learn from rather than dwelling on the negative aspects.
Final Thoughts
In closing, genetic variation in dopamine signaling plays a role in how we perform under cognitively demanding tasks. Evolutionarily speaking, it made sense for some people to perform well under pressure (Val warriors) while others performed better under baseline, unstressed conditions (Met worriers). We should embrace the genetic diversity inherent in this and other behaviors but also realize biology is only one determinant of behavior. Our mindset and how we frame the effect of stress on us is also critical and, in fact, has biological effects on our stress response. 

The data presented here reflect a theme common in the brain and human behavior: behavior is modulated by both our biology and environment. Behavior is complicated and so to understand it, we need to look beyond merely our genes, proteins, and cells. Especially when it comes to human behavior, our environment and experiences affect our biology and behavior.

​None of these relationships are simple, which is what makes studying them so interesting.  
Further Reading:
Catechol-O-Methyltransferase moderates effect of stress mindset on affect and cognition

Changing Stress Mindset Through Stressjam: A Virtual Reality Game Using Biofeedback

Quantitative role of COMT in dopamine clearance in the prefrontal cortex of freely moving mice

The influence of Val158Met COMT on physiological stress responsivity

COMT genetic variation affects fear processing: psychophysiological evidence

The efficacy of stress reappraisal interventions on stress responsivity: A meta-analysis and systematic review of existing evidence

Rethinking stress: the role of mindsets in determining the stress response
​

The catechol-O-methyltransferase Val(158)Met polymorphism modulates fronto-cortical dopamine turnover in early Parkinson's disease: a PET study
​

Site-Specific Role of Catechol-O-Methyltransferase in Dopamine Overflow within Prefrontal Cortex and Dorsal Striatum
​

Older age may offset genetic influence on affect: The COMT polymorphism and affective well-being across the life span
0 Comments

Declining Dopamine: How aging affects a key modulator of reward processing and decision making

5/25/2019

0 Comments

 
Neuroscience
Picture
Dopamine is often referred to as the "reward" neurotransmitter, a chemical signal released to rewarding stimuli such as drugs of abuse. Its effect on motivation and reward is, however, more nuanced.
Prefrontal Cortical Dopamine and Cognition
In fact, dopamine signaling in an area of the brain known as the prefrontal cortex (PFC) is critical for a variety of cognitive functions, including attention and processes such as working memory. Interestingly, dopamine's function on cognition has proposed to be non-linear (inverted U shaped) with some optimal intermediate level of dopamine associated with better cognitive performance. My own work in collaboration with Charlotte Boettiger and Amanda Elton has used the inverted-U model of PFC dopamine's effect on cognition to explain differences in working memory and choice behavior seen in healthy adults. We have also shown evidence of U-shaped patterns in resting and task-related brain function.
Picture
The PFC, located in the front of the brain, regulates human decision making.
Picture
PFC dopamine's effects on cognition and choice behavior follows an inverted-U pattern. DA, dopamine
PFC dopamine is thought to vary based on genetics and sex. Thus, biological factors affect where individuals fall on the inverted-U. Additionally, stress is known to boost PFC dopamine (and other neurotransmitters) and an individual's biologically-based PFC dopamine levels may explain why some people perform better under stress (i.e., their basal PFC dopamine is sub-optimal but it boosted "up" the curve to optimal range with stress) then others (whose PFC dopamine levels may start out more in the optimal range but are then pushed into a supra-optimal level "down" the inverted-U curve). Genetic variation in one key PFC dopamine regulatory gene in particular (COMT) has led to the use of the term "warriors" and "worriers" to explain the function this natural variation in PFC dopamine plays in human behavior.
Dopamine Signaling Declines with Age
Dopaminergic signaling declines with age. A 2017 meta analysis led by Teresa Karrer has demonstrated declines in both the receptors that are the key target of dopamine signaling as well as the dopamine transporters important in the regulation of this signaling.
This decline has effects on a variety of decision making processes. It also has implications for the inverted-U model as natural declines of PFC dopamine with age would be expected to shift where individuals fall on the U-shaped curve.
Picture
The Val158Met COMT genetic polymorphism interacts with age to affect impulsive choice behavior, a process we believe is mediated by PFC dopamine (DA).
Dopamine's effects on cognition in particular and the fact that cognitive processes also decline with age (also see) that has lead to the correlative triad hypothesis. This hypothesis proposes that the decline of brain dopamine signaling explains much of the cognitive decline in aging.
Picture
Dopamine D2 receptor availability measured with PET imaging. From Castrellon et al., J Neurosci 2019
My own work with collaborators David Zald, Greg Samanez-Larkin, Kendra Seaman, and Linh Dang has confirmed these persistent declines in dopamine signaling across the brain, with the rate of decline varying in different areas of the brain.
Rates of decline vary from ~10% per decade in the frontal cortex to <5% per decade in the striatum, areas of the brain associated with decision making (also see) and reward, respectively.
You can explore these data showing variations in age-related decline of brain dopamine via an online application created by my colleague, Kendra Seaman, here.
Aging, Dopamine, and Decision Making
While our own data does not unequivocally support the correlative triad hypothesis of dopamine, aging, and cognition, this does not mean dopamine changes with age don't impact some aspects of human behavior. Work from the Samanez-Larking group and others has shown older adults are more likely to choose skewed gambles than younger adults, are less sensitive to monetary losses, and decrease their selection of risky monetary choices with age. See two excellent review articles on some of this aging & neuroeconomics literature here and here.
Our group, in work led by Kendra Seaman, has also found evidence that different types of commodities (social interaction and health) may be more valuable to older adults immediately and with certainty than money.
Interestingly, the brain regions responsible for assigning value to potential rewards are consistently engaged across adulthood. Thus, older and younger adults are using similar brain mechanisms to assign value to rewards. It is possible, though, that changes in dopamine signaling in these key reward valuation brain areas (ventromedial PFC, ventral striatum) influences to amount of value assigned to rewards as we age.
Can we stop/reverse age-related declines in dopamine?
Interestingly, our research group, in work led by Linh Dang, has found evidence that the negative relationship between age and dopamine receptor availability in a particular portion of the brain associated with motivation and reward processing (the ventral striatum, VS) was weaker in individuals with a higher degree of physical activity (as assessed using a pedometer).
These data suggest that increased physical activity may slow age-related dopamine decline. The Parkinson's disease (a disorder associated with death of dopamine-producing neurons in the brain) literature is suggestive that physical activity can be beneficial. Whether exercise could work to slow or prevent dopamine decline in normal human aging remains to be empirically tested. 
Picture
Age-related decline in D2 receptor availability in VS is reduced in more active adults. From Dang et al., Neuroimage 2017
Picture
Picture
Summary & Future Directions
An increasingly aging human population makes it critical to understand how decision making processes may differ between younger and older adults. Natural, age-related declines in dopamine probably play a role in reward and choice behavior differences between young and older adults. Understanding the differences between choice behavior with aging will allow more effective interventions to be developed to assist older adults in their financial and healthcare choices (see also).
More work is needed to determine if particular approaches (from pharmacology to exercise) can be taken to optimize PFC dopamine levels and/or prevent age-related declines in dopamine signaling. 
0 Comments

    Author

    A neuroscientist by training, I now work to improve the career readiness of graduate students and postdoctoral scholars.

      Subscribe to Reflections Newsletter

    Subscribe to Newsletter

    Archives

    March 2021
    February 2021
    January 2021
    December 2020
    November 2020
    October 2020
    September 2020
    August 2020
    July 2020
    June 2020
    May 2020
    March 2020
    February 2020
    January 2020
    December 2019
    November 2019
    September 2019
    August 2019
    July 2019
    May 2019
    April 2019

    Categories

    All
    Academic Job Search
    Artificial Intelligence
    Career Development
    Career Exploration
    Data Science
    Future Of Work
    International Concerns
    Job Search
    Life Advice
    Neuroscience
    NIH BEST Blog Rewind
    Opinion
    Personalized Medicine
    PhD Career Pathways
    Scientific Workforce
    Welcome

    RSS Feed

Science

Career Development Research
​
Neuroscience Research


Publications

Writing

​Reflections Blog

Other Posts

Press, Resources, & Contact

Press                                                       Contact

Job Search Resources                Funding Resources

Subscribe to Reflections Newsletter 
© COPYRIGHT 2021. ALL RIGHTS RESERVED.