Where is catastrophe in my brain?

September 18th, 2011

People argue constantly about the role of specific brain changes in affecting human behavior. As you probably know if you’re a frequent A3 reader, I’m a big believer in the notion that just like every other physical aspect of our “selves,” biological changes in our brain function brought about by genetics, experience, or other influences have a huge effect on how we think.

Apparently, researchers just found at least one aspect of brain function that can make us exaggerate our perception of our own negative responding.

The story here is pretty compelling -

In rats, a specific neurotransmitter system, called NPS (or neuro-peptide S) has been implicated in anxious responding and fear. Later research in humans revealed that a specific variation in one of the genes that plays a role in this system, NPSR1T (the T version of the neuro-peptide S receptor subtype 1), is associated with panic disorder.

The most recent piece of the puzzle, published in the journal Molecular Psychiatry, has revealed that humans that carry 1 copy of this variation have significantly stronger evaluations of their own negative responses to a standard fear-conditioning experiment. Essentially they “catastrophized” their own reaction to an experimental fear-associated signal. Also, this catastrophe registered in a very specific part of their brain called the rostral dorsomedial prefrontal cortex (dmPFC), an area that supports the explicit, conscious appraisal of threat stimuli (see picture on the left).

One of the most interesting pieces in my opinion is this – These individuals had no elevation in their physiological fear responses either in skin response, heart rate, or the brain areas known to be associated with them.

Apparently, just because you believe that something is worst than someone else doesn’t mean that your body responds to it that way. Pretty cool!

Citations:

K A Raczka, N Gartmann, M-L Mechias, A Reif, C Büchel, J Deckert and R Kalisch (2010). A brain area for catastrophizing. Molecular Psychiatry 2010 15: 1045.

K A Raczka, N Gartmann, M-L Mechias, A Reif, C Büchel, J Deckert and R Kalisch (2010). A neuropeptide S receptor variant associated with overinterpretation of fear reactions: a potential neurogenetic basis for catastrophizing. Molecular Psychiatry 2010 15: 1067-1074.

Posted in:  Education Tags: 2010, Brain, brain function, dmPFC, fear, molecular, molecular psychitary, psychiatry

Men and women are not the same: Sex differences in addiction research

September 11th, 2011

You may not have realized it, but men and women are different. Really.

Though the statement may seem like the most unnecessary, obvious, expression since the dawn of time, it’s surprising how rarely the importance of these differences comes up when we talk about addiction. Still, there’s little doubt that if our hormones, brain development, and even our reaction the to exact same stories aren’t the same, the way we react to drugs, or to addiction treatment, are likely gender specific as well. In fact, while men are almost twice as likely to meet criteria for addiction, women seem to move from casual use to addiction more quickly. Let’s explore some addiction research findings that may tell us why.

Social stress, drug use, and addiction

If you’ve gone through high-school, you know that boys and girls have different sort of social interactions. Women develop tightly knit cliques that aim to protect them from being fully ostracized while keeping out those who may cause trouble within the fold.

Indeed, when researchers compared cocaine using men and women, they found much greater neural activation in the drug-seeking brain regions of women during social stress (things like exclusion, being put down, and such) than were found for men or for women who didn’t use drugs. Similar findings have been reported for a neuroprotective hormone called DHEAS, which was found to be lower in women and in cocaine addicts, signaling their increased vulnerability to stress-induced immune problems. It’s hard to tell which came first, but social stress “triggered” these women’s systems a lot more than it did men. And the differences change behaviors too – Research in monkeys found that while male monkeys used more cocaine if they were “losers” (lower on the social ladder), female monkeys who were “leaders” were found to use more cocaine when given a chance.

Obviously, social standing and events mean different things, and bring about different reactions to drugs, for men and women.

Drug use, the brain, and gender

Not only do men and women act differently when it comes to drugs, but differences have been found in the specific brain changes associated with drug exposure between the sexes!

Research in rats has shown that brain changes following prenatal (before birth) exposure to cocaine are different between males and females and that they interact with exposure to social stimulation. In humans, researchers found differences in brain volume, and its association with early trauma, emotional, and physical, neglect between boys and girls at risk for substance abuse problems. Other work found that the prenatal cocaine exposure was more greatly associated with memory problems in women than men.

Sex (gender) and drugs – the takeaway

So, men and women are not the same. Not a big surprise I know, but the specific ways in which the two sexes react to the intake of drugs and the differences in their responses to stress that may motivate them to use at different times can become important factors to consider both in prevention AND in addiction treatment setting. For instance, it seems that we’d want to look at the possibility that drug prevention efforts should look at social-standing among adolescents when determining might need the most attention. Also, if exposure to drugs affects the brain differently in the different sexes because of differences in the concentration of protective hormones, it’s possible that the specific aspects of treatment that require focus might be different too.

Some food for thought…

Posted in:  Education Tags: addiction, boys girls, Brain, brain changes, cocaine, different, Drugs, men, men women, neuroprotective, social, social stress, stress, trauma, treatment, women

Biology, environment, or psychology? Which is most important in addiction?

August 2nd, 2011

I get asked this question a lot, both by people who are fully committed to the biological (or brain) model of addiction and ones who thinks it’s crap and that it’s all about psychology, experience, and motivation.

The thing is that it is absolutely impossible to separate the influence of the brain, environment, and psychology since they all intertwine and interact to deliver the final condition… I was reading an article about marketing in the new Internet age yesterday and it included a joke that I thought was relevant, so I’ll steal it. Instead of focusing on addiction, this joke centered on the question of which part of the body is most important? Maybe it’ll do a good job of explaining why asking the question of which of the above is most important is to some extent useless.

So – The brain, blood, lungs, and Legs were all fighting each other on the question of which of them was most important in the human body. Along came the anus and argued for its own place as The King of all that is human. The first four all laughed in its face, thinking the idea that the anus is King a funny joke. In protest, the anus shut down, a little upset at being made fun of. Three days later the rest of the body sent a notice that the anus has won the debate and begged it to get back to business.

You see, the brain runs the body, upon which it relies for everything and together those two interact with the environment in ways that alter them both. Then you place thousands and millions of people together in the environment and they interact to create a psychological reality that affects everything else that’s already there. It’s completely impossible to separate the parts sice they all rely on each other and are affected by the others.

This is why behavioral interventions, medical interventions, and environmental conditions have all been shown to affect the probability of addiction developing and of addiction ceasing. They all contribute so they all have the power to affect it, though the mix is probably different in different people based on their own experiences, biology, etc…

Make sense?

Posted in:  Education Tags: addiction, anus, body, Brain, environment, intervention, interventions, question

Teen learning exaggerates rewards – Bad decisions and brain development

May 3rd, 2011

Teens tend to make some seriously stupid decision (including teen drinking and driving), at least when compared to younger kids and older adults. We’ve all heard that brain development during that part of life plays a role in this but the question is: What exactly about brain development makes teens more risky?

There are a number of options – 1) Teens could have less control over all aspects of their behavior as their prefrontal cortex finishes developing, 2) Teens may be over-sensitive to rewards, putting too much emphasis on the positive value of stimuli they’re exposed to, or 3) Teens might just be less sensitive to the negative consequences of their action, which lets them take risks others just wouldn’t.

A somewhat recent study coming out of UCLA (and I just have to congratulate my colleague Jessica Cohen for getting a 1st author Nature paper!) suggests that at least to some extent, oversensitivity to positive reward-signals may be the answer and brain development has a lot to do with it. Read the rest of this entry »

Posted in:  Education Tags: Brain, brain development, consequences, decision, drinking driving, good, reward, teen drinking, teens, UCLA

Loss, but not absence, of control – How choice and addiction are related

January 3rd, 2011

In a recent post the notion that “loss of control” is an addiction myth was raised by our new author, Christopher Russell, a thoughtful graduate student studying substance abuse in the U.K. Though I obviously personally believe in control- and choice-relevant neurological mechanisms playing a part in addiction, this conversation is a common one both within and outside of the substance abuse field. Therefore, I welcome the discussion onto our pages. I’d like to start out by reviewing some of the more abstract differences between my view and the one expressed by Christopher and follow those with some evidence to support my view and refute the evidence brought forth by him.

Addiction concetualization – Philosophical and logical differences and misinterpretations

One of the first issues I take with the argument against control as a major factor in addiction is the interpretation of the phrase “loss of control” as meaning absence, rather than a reduction, in control over addiction. Clearly though, one of the definitions of loss is a “decrease in amount, magnitude, or degree” (from Merriam-Webster.com) and not the destruction of something. Science is an exercise in probabilities so when scientists say “loss”, they mean a decrease and not a complete absence in the same way that findings showing that smoking causes cancer do not mean that if an individual smokes they will inevitably develop cancerous tumors. Similarly, the word “can’t” colloquially means having a low probability of success and not the complete inability to succeed. Intervention that improve the probability of quit (like bupropion or quitlines for smoking) success are therefore said to cause improvements in the capacity for quitting.

Next, Christopher wants scientists to identify the source of “will” in the brain but I suggest that “will” itself is simply a term he has given a behavioral outcome – the ability to make a choice that falls in line with expectations. In actuality, “will” is more commonly used as a reference to motivation, which while measurable, isn’t really the aspect of addiction involved in cognitive control. Instead, what we’re talking about is “capacity” to make a choice. The issue is a significant, not semantic one, since the argument most neuroscientists make about substance abuse is that addicts suffer a reduced capacity to make appropriate behavioral choices, especially as they pertain to engaging in the addictive behavior of interest. If someone is attempting to get into a car but repeatedly fails, we say they can’t get in the car (capacity), not that they don’t want to (will). Saying that they simply “don’t” get in the car doesn’t get at either capacity or will but instead is simply descriptive. I don’t believe that science is, or should be, merely descriptive but instead that it allows us to form conclusions based on available information.

That there is a segment of individuals who develop compulsive behavioral patterns tied to alcohol and drug use and who attempt to stop but fail is, to my mind, evidence that those individuals have a difficulty (capacity) in ceasing their drug use. Their motivation (will) to quit is an aspect that has been shown to be associated with their probability of success but the two are by no means synonymous. It is important to note, and understand, that the attribution for the performance should not fall squarely on the shoulders of the individuals. We humans are so prone to making that mistake that it has a name, “The fundamental attribution error,” and indeed, individuals who show compulsive, addictive, behavior do so because of neuropharmacological, environmental, and social reasons in addition to the complex interactions between them all. But no one is disputing that and in fact, the article used by Christopher to point out the notion of a “tipping point” in addiction directly points out that fact in the next paragraph (Page 4), which he chose not to reference or acknowledge.

“Of course, addiction is not that simple. Addiction is not just a brain disease. It is a brain disease for which the social contexts in which it has both developed and is expressed are critically important… The implications are obvious. If we understand addiction as a prototypical psychobiological illness, with critical biological, behavioral, and social-context components, our treatment strategies must include biological, behavioral, and social-context elements.” (Lashner, 1997)

Lastly, Christopher’s philosophical musings are interesting, but they seem to stray away from trying to find an explanation for behavior and instead simply deconstruct evidence. In a personal communication I explained that while most addiction researchers understand that addiction, like most other mental health disorders is composed of a continuum of control ranging from absolute control over behavior to no control whatsoever (with most people fitting somewhere in the middle and few if any at the extreme ends), categorization is a necessary evil of clinical treatment. The same is true for every quantitative measure from height (Dwarfism is sometimes defined as adults who are shorter than 4’10″) to weight (BMI greater than 30 kg/m²). I think it’s equally as tough to argue that someone with a BMI of 29.5 is distinctly different from an individual with a BMI of 30 as it is to argue that there is no utility in the classification. Well, the same applies for addiction, although Christopher apparently categorically objects to classification and believes it has no utility or justification.

Now for the evidence – “Choice” and “control” are not the same as “will”

Some people quit, even without help – Christopher and a number of the people he cites in support (Peele, Alexander), suggest that because some people do stop using that it can’t be said that there is a problem with any individuals’ capacity to stop. The problem with that argument is that it supposes that everyone is the same, a fact that is simply not true. As an example I would like to suggest that we compare cognitive control with physical control and use Huntington’s Disease (HD or Huntington’s Chorea) as an example.

HD patients suffer mental dementia but the physical symptoms of the disease, an inability to control their physical movement resulting in flailing limbs often referred to as the Huntington Dance, are almost always the first noticeable symptoms. Nevertheless, HD sufferers experience a number of debilitating symptoms that originate in brain dysfunction (specifically destruction of striatum neurons, the substantia nigra, and hippocampus) and that alter their ability (capacity) to control their movements and affect their memory and executive function leading to problems in planning and higher order thought processes. So, while it is true that most people can control their arm movements, here is an example of individuals who progressively become worse and worse at doing so due to a neurophramacological disorder. There is currently no cure for HD but some medications that help treat it no doubt restore some of the capacity of these patients to control their movements. If a cure is found it would be difficult to say, as Christopher suggests of addiction, that the cure does not affect the capacity of HD patients to control what they once could not. I chose HD for its physiological set of symptoms but a similar example could easily be constructed for schizophrenia and a number of other mental health disorders (including ADHD and addiction). Importantly, cognitive control is a function of brain activity, activity that can become compromised as the set of experiment I will discuss next show.

An experiment conducted at UCLA (1) has shown that cocaine administrations reduced animals’ ability to change their behavior when environmental conditions called for it. Even more meaningful was the finding that once animals are exposed to daily doses of drugs, the way their learning systems function is altered even when the drugs themselves are no longer on board and even when the learning has nothing to do with drugs per se.

In the experiment, conducted by Dr. David Jentsch and colleagues, monkeys were given either a single dose (less than the equivalent of a tenth of a gram for a 150lb human) or repeated doses (1/8 to 1/4 of a gram equivalent once daily for 14 days) of cocaine. The task involved learning an initial association between the location of food in one of three boxes and then learning that the location of the food has changed. We call this task reversal learning since animals have to unlearn an established relationship to learn a new one.

Obviously, the animals want the food, and so the appropriate response once the location is changed is to stop picking the old location and move on to the new one that now holds the coveted food. This sort of thing happens all the time in life and indeed, during addiction it seems that people have trouble adjusting their behavior when taking drugs is no longer rewarding and is, in fact, even troublesome (as in leading to jail, family breakups, etc.).

In the experiment, animals exposed to cocaine had trouble (when compared to control animals that got an injection of saline water) learning to reverse their selection when tested 20 minutes after getting the drug, which is not surprising but still an example of how drug administration can causally affect an individual’s ability to make appropriate choices. As pointed above, the most interesting finding had to do with the animals that got a dose of cocaine every day for 14 days. Even after a full week of being off the drug, these animals showed an interesting effect that persisted for a month – while their ability to learn that initial food-box association, they had significant trouble changing their selection once the conditions changed. Remember, this effect was present with no cocaine in their system and with learning conditions that had nothing whatsoever to do with cocaine.

If that’s not direct evidence that having drugs in your system can alter the way your brain makes choices, I don’t know what is.

Another study conducted by Calu and colleagues with rats found similar (or even more pronounced) reversal learning problems after training the animals to take cocaine for themselves, clarifying that it is the taking of cocaine and not the method that causes the impairments.

Another entire set of studies has shown that stimuli (also known as cues or triggers) that have become associated with drugs can bring back long-forgotten drug-seeking behavior once they are reintroduced. This was shown in that Calu paper I mentioned above and in so many other articles that it would be wasteful to go through all the evidence here. Importantly, this evidence shows that drug associated cues direct behavior towards drug seeking in a way that biases behavior regardless of any underlying will. My own research has shown that animals who respond greatly to drugs (nicotine in our case) likely learn to integrate more of these triggers than animals who show a reduced response, indicating once again that these animals bias  their behavioral selection towards drug-seeking more than usual. While we have more studies to conduct, we believe that genetic differences relevant to dopamine and possibly other neurotransmitters important for learning (like Glutamate) are responsible for this effect.

While we can’t do these kinds of experiments with people (research approval committee’s just won’t let you give drugs to people who haven’t done them before), there is quite a bit of evidence showing an association between trouble in reversal learning and chronic drug use in humans (see citation 3 for example) as well as research showing very different brain activity among addicted individuals to drug-associated versus non-drug cues (like seeing a crack pipe versus a building). All this evidence suggests that drug users are different in the way they learn generally, and more specifically about drugs, than individuals not addicted to drugs. When it comes to genetics, we know quite a bit about the  association between substance abuse and specific genes, especially when it comes to dopamine function. As expected, genetic variation in dopamine receptor subtypes important in learning about rewards (D4 and D2) has been revealed to exist between addicts and non addicts. Without getting into the techniques and analysis methods involved in these genetic studies, their sheer number and the relationship between substance abuse and other impulse disorders points to a direct relationship between drug use disorders (and possibly other addictive disorders) and a reduced capacity to exert behavioral control. Less capacity for control is what researchers have found sets addict apart from non-addicts.

Summary, conclusions, and final thoughts

In closing, there are undoubtedly imperfections about the ways we diagnose addiction. It would probably be nice if we could figure out a way to incorporate what we know about the continuous nature of the disorder with the need for clinical delineation of who requires addiction treatment and who doesn’t. Addiction researchers are far from the only ones who wonder about this question though (the same issues are relevant for schizophrenia, depression, and nearly every mental health disorder) and I am certain that better and better solutions will emerge.

However, the discussion of stigma in this context needs to allow us to discuss the reality of addiction without having to resort to blaming and counter-blaming. If I describe the Toyota Prius as being slow but incredibly efficient I am no more stigmatizing than if I describe a Ferrari as being incredibly fact but wasteful in terms of fuel. The same applies, or should apply, to health and mental health diagnoses – Just because an individual is less able to exert cognitive control over impulses should not by definition call into question their standing as a human being. We are complex machines and by improving our understanding of the nuts and bolts that make us function we can only, in my opinion, improve our ability to make the best use of our capabilities while understanding our relative strengths and weaknesses. Any other way of looking at it seems to me to be either wishful (I can do anything if I want it badly enough) or defeatist (I will never be anything because I’m not good at X) and neither seem like good options to me.

Citations:

1) Jentsch, Olausson, De La Garza, and Tylor (2002): Impairments of Reversal Learning and Response Perseveration after Repeated, Intermittent Cocaine Administrations to Monkeys. Neuropsychopharmacology, Volume 26, Issue 2, Pages 183-190

2) Calu et al (2007) Withdrawal from cocaine self-administration produces long-lasting deficits in orbitofrontal-dependent reversal learning in rats. Learning & Memory, 14, 325-328.

3) Some evidence in humans from Trevor Robbins’ group: Reversal deficits in current chronic cocaine users.

Posted in:  Education Tags: addiction, addictive, ADHD, Brain, capacity, cocaine, cognitive control, compulsive, control, depression, dopamine, drug, drug use, genetic differences, glutamate, hd, hippocampus, huntington's disease, learning, mental health, mental health disorders, motivation, obesity, peele, reversal learning, schizophrenia, science, striatum, substance abuse, substnatia nigra, treatment, triggers, UCLA, will

Is marijuana addictive? You can bet your heroin on that!

November 25th, 2010

This is the ultimate question for many people. In fact, when discussing addiction, it is rare that the addiction potential for marijuana doesn’t come up.

Some basic points about marijuana:

The active ingredient in marijuana, THC, binds to cannabinoid receptors in the brain (CB1 and CB2). Since it is a partial agonist, it activates these receptors, though not to their full capacity. The fact that cannabinoid receptors modulate mood, sleep, and appetite to some extent is the reason behind many of marijuana’s effects.

But how is marijuana addictive? What’s the link to heroin?

What most people don’t know is that there is quite a bit of interaction between the cannabinoid receptor system (especially CB1 receptors) and the opioid receptor system in the brain. In fact, research has shown that without the activation of the µ opioid receptor, THC is no longer rewarding.

If the fact that marijuana activates the same receptor system as opiates (like heroin, morphine, oxycontin, etc.) surprises you, you should read on.

The opioid system in turn activates the dopamine reward pathway I’ve discussed in numerous other posts (look here for a start). This is the mechanisms that is assumed to underlie the rewarding, and many of the addictive, properties of essentially all drugs of abuse.

But we’re not done!

Without the activation of the CB1 receptors, it seems that opiates, alcohol, nicotine, and perhaps stimulants (like methamphetamine) lose their rewarding properties. This would mean that drug reward depends much more heavily on the cannabinoid receptor system than had been previously thought. Since this is the main target for THC, it stands to reason that the same would go for marijuana.

So what?! Why is marijuana addictive?

Since there’s a close connection between the targets of THC and the addictive properties of many other drugs, it seems to me that arguing against an addictive potential for marijuana is silly.

Of course, some will read this as my saying that marijuana is always addictive and very dangerous. They would be wrong. My point is that marijuana can not be considered as having no potential for addiction.

As I’ve pointed out many times before, the proportion of drug users that become addicted, or dependent, on drugs is relatively small (10%-15%). This is true for almost all drugs – What I’m saying is that it is likely also true for marijuana (here is a discussion of physical versus psychological addiction and their bogus distinction).

Citation:

Ghozland, Matthes, Simonin, Filliol, L. Kieffer, and Maldonado (2002). Motivational Effects of Cannabinoids Are Mediated by μ-Opioid and κ-Opioid Receptors. Journal of Neuroscience, 22, 1146-1154.

Posted in:  Drugs, Education, Marijuana, Opiates, Tips Tags: about addiction, addiction, addiction research, addictive, addictive properties, Brain, canabinoid receptors, cannabinoid, cannabinoid receptor, CB1, cb1 receptor, cb1 recpetor, dopamine, drug abuse, Drugs, fact, heroin, is marijuana addictive, marijuana, marijuana addictive, neuroscience, opioid, pot, receptor, receptors, THC, weed

Gambling on marijuana use makes for bad decisions

November 12th, 2010

I just can’t seem to stay away from the marijuana debate, even given the recent defeat of Proposition 19 that aimed to legalize marijuana in California. This article is a short one, but speaks to some of the cognitive issues associated with marijuana use.

A study (see here) conducted by a Wake Forest University team (Including Doctor Linda Porrino) found that habitual marijuana smokers (those who smoked an average of twice a day for seven years) may be bad at detecting negative outcomes.

The experiment used fMRI scanning technology to examine the brain activity of smokers and controls during the Iowa Gambling Task, which uses four decks of cards. Two of the decks yield large, infrequent, rewards as well as losses. The other two decks yield small, more frequent rewards, and less losses. The first two are considered the “bad” decks, and the latter two the “good” decks, because selecting from the small-gain, small-loss, decks will result in more gain overall. The task is considered a pretty good, if complex, measure of risk-taking, decision making, and loss-discounting.

The take-home result from the study: Not only did marijuana smokers take longer to learn how to maximize their rewards, but their decision-making brain regions seemed to show lower overall responding during the task, meaning they were less active while performing the decisions. And as you can see from the graph on the left, while the controls were able to achieve overall gains, the same was not true for the long-term marijuana users even after 100 repetitions. It seems that marijuana smokers’ brains were not as efficient at detecting losses and responding to them. Maybe that’s why marijuana users are the first to claim that marijuana use has no negative outcomes associated with it…

As usual, it is important to note that since the participants in the study were not randomly assigned to long-term marijuana smoking, it’s impossible to know if these deficits are specifically caused by marijuana use or if they were pre-existing. Nevertheless, these results strongly suggest that individuals who engage in long-term use of marijuana are cognitively distinct from those who don’t. I think that plays into the argument that marijuana legalization would not increase use, because if that’s actually true, then there’s something different about individuals who choose to smoke weed and it is not the legal status that matters. I suspect that in actuality, people who currently choose to smoke marijuana long-term are in fact distinct, in some ways, from some of the people who would take up smoking the stuff if it became legal.

Citation:

Christopher T. Whitlowa, Anthony Liguoria, L. Brooke Livengooda, Stephanie L. Harta, Becky J. Mussat-Whitlowb, Corey M. Lamborna, Paul J. Laurientic and Linda J. Porrino (2004). Long-term heavy marijuana users make costly decisions on a gambling task. Drug and Alcohol Dependence, 76, 107-111.

Posted in:  Drugs, Education, Marijuana Tags: Brain, decision, decision making, fMRI, gambling, long term, loss, marijuana, marijuana use, marijuana user, marijuana users, reward, risk taking, smoker, task, weed