Marijuana has Long-term Effects on the Brains of Adolescents


After alcohol, marijuana is the most widely used illegal drug in the United States (I mean seriously, who hasn’t smoked up at least once? According to Pew Research Center, half of the country) But pot laws are rapidly changing in many parts of the country and soon it may be as ubiquitous as alcohol. Four states in the US have legalized marijuana for recreational use and 23 total states have some form of legal marijuana use (including D.C.). While the health effects of alcohol have been well studied and are significant (some 88,000 deaths/year, the third highest cause of preventable death in the US, according to the CDC and NIAAA), little is known how this shifting trend in marijuana use will affect the country. Another important trend is the amount of THC (Δ-9-tetrohydrocannabinol, the chemical that is primarily responsible for the psychoactive effects of marijuana) in marijuana strains has been steadily increasing over the past few decades [1, 2]. The big question that researchers are asking themselves is if legal marijuana use drastically increases, what are the long-term personal and public health consequences of marijuana use? Of course, this is a huge question with many complexities.

Significantly, Marijuana is the also the most widely used illegal substance amongst youths. Adolescence (ages 12-17) is an extremely critical period for brain development [3, 4] yet the effects of marijuana on the brains of kids have not been thoroughly studied. A recent paper out of Dr. Steven R. Laviolette’s laboratory at the University of Ontario sought to answer this question: what happens to brains of adolescent and adult rats that have been exposed to THC?

Renard et al. 2016 abstract

Why was the research done? What is the hypothesis?

 There have been a number of studies published that suggest there might be an association between prolonged marijuana use (especially of high-potency strains) and schizophrenic-like or psychotic-like symptoms [5, 6] although there is disagreement in the scientific community on the evidence [7, 8] (I may write a blog post discussing this issue in the future). It is has even been suggested that youths that smoke marijuana are more at risk for psychotic symptoms as adults [9, 10]. The author’s sought to test this directly by injecting adolescent and adult rats with THC for a number of days, waiting a period of time after the injections, then measuring the long-term effects on the rats. The team hypothesized THC would have induced long-term changes in the brains of adolescent but not adults rats, and subsequent changes in psychotic-like behavior.

How was it done?

Adolescent and adult rats were injected with THC twice daily for 11 days. The dose of THC administered was increased (escalating dose) to account for any tolerance that may occur. As an important control, separate groups of adolescent and adult rats were injected with vehicle (the solution that THC was dissolved in but minus the THC itself). Following a 30-day abstinence period after the last injection, THC-adolescent, control-adolescent, THC-adult, and control-adult rat groups were subjected to number of behavioral and molecular tests to see what effect the drug had on the animals. I need to point out that the 30-day abstinence period is significant in the rat life-span. This is enough time for the adolescent rats to become adults so what the scientists are primarily studying is the long-term effects of THC on adolescents vs adults in adulthood.

In the behavioral neuroscience field, we have devised another of tests to measure various aspects of animal behavior. Obviously we can’t inject humans with THC and see what happens so we have to use rodents and identify behaviors that approximate a similar behavior in humans. Of course, rodent behavior is no where near as complex as humans but rats are remarkably sophisticated animals (ask anyone living in New York) and scientists have developed a number of ways to measure things from motivation to social behavior to anxiety to depression.

In this experiment, a social test was used, two different types of anxiety tests and a motor activity test. The tests measured effects on motivation, exploratory-behavior (another indicator of how motivated rats are), social interaction, and anxiety.

The scientists also measured the activity of dopamine-releasing neurons in the living animal using a technique called in vivo electrophysiology. Recall from my post I am Neuron! that when activated, brain cells (called neurons) conduct an electrical current that results in the release of neurotransmitters onto another neuron. This electrical current is called an action potential and we can measure this by inserting a special probe into the those neurons in the animals brain (the probe measures electrical currents). Therefore, with in vivo electrophysiology we can measure every time a neuron fires (i.e. an action potential is generated) in a specific part of the brain. Using this technique, the scientists measured dopamine neurons in an important region of the brain called the VTA and how often these neurons fire in THC vs control rats. Check out this video for more details on in vivo electrophysiology.

Finally, brains from animals were dissected and a number of protein molecules were studied using a common technique in molecular biology called a Western blot (or known as an immunoblot). A Western blot takes advantage of antibodies that are able to recognize and stick to one specific type of protein. Therefore, this assay can tell you two main things 1) if your protein of interest is present in your sample and 2) approximately how much of your protein there is compared to other samples. In this paper, tissue from a specific brain region is used and the protein is analyzed by Western blots in order to comparing quantities of proteins between the different experimental groups. Of course, the limitation of a Western blot is if you have a good antibody for your protein of interest. Luckily there are many biotech companies such as Cell Signaling that specialize in making and testing reliable antibodies. The scientists used the Western blots to study many proteins in a region of the brain called the prefrontal cortex (PFC), which is believed to be important in self-control and other high-function brain processes. Check out this video for more details on Western Blots.

What did they find?

THC-adolescent rats exhibited deficits in numerous behavioral experiments compared to controls while THC-adult rats did not appear to have any behavioral changes.

*Recall that these experiments were conducted 30 days after the last THC dose so the author’s show that these are long-term effects of THC on the brain of adolescent rats.

In the social activity test, rats showed little interest in interacting with a stranger rat (normal rats are usually curious about the novel stranger). THC-adolescents also did not walk around or explore a new cage as much. In the two different anxiety tests, THC-rats appeared to have be more anxious (demonstrated more anxiety-like behavior).

In the electrophysiology experiment, VTA DA neurons fired more frequently for some reason in THC-adolescents compared to the other groups.

Finally, numerous protein changes in the PFC were observed in a number of important signaling pathways such as Wnt and mTOR pathways. Interestingly, THC-adolescents vs THC-adults seemed to have opposite effects on this proteins.

Limitations to the study?

  1.  The behavioral changes observed were statistically significant (meaning, most likely a real effect and not some kind of fluke of random chance) but were modest changes in some of the tests performed. Would the changes last beyond the 30 days post injection in this study?
  2. There are impressive arrays of behavioral tests that rats can perform to measure numerous aspects of cognition (for example, memory and learning) but none of these experiments were performed. A far greater range of behavioral experiments would have made this study more compelling.
  3. While the electrophysiology and Western blot data are intriguing, the author’s performed no experiments to determine if these changes are responsible for the difference in behavior (association vs causation). These changes could merely be an incidental change and have nothing to do with the behaviors studies.
  4. The doses that the mice were injected with, while based on a previous study, are somewhat arbitrary. Would the changes be more pronounced or less pronounced with higher/lower doses or a shorter/longer dosing regimen?
  5. Only male rats were studied. Would the same behavioral and molecular changes occur in female rats?

What does it mean?

Based on the behavioral and molecular data presented, this data paper suggests that adolescent rats (but not adults) exposed to THC have long-lasting changes in the brain. The author’s argue that these effects recapitulate schizophrenia-like symptoms but I am not entirely convinced. Also, THC given to rats is not the same thing as marijuana smoked by human teenagers. So it’s important to keep in mind that this is one study. In science, we never draw grand conclusions about anything based on one study. Nevertheless, several other reports have corroborated these findings (see this review paper for a summary of many of them [11]). Indeed, it does seem that marijuana use can cause long-term deficiencies in human and rodent brains. The results of this paper are certainly intriguing and, if true, a whole host of stricter regulations on marijuana use in states that have legalized it may need to put in place to help curb increasing marijuana abuse amongst youths.


  1. Cascini F, et al. Increasing delta-9-tetrahydrocannabinol (Delta-9-THC) content in herbal cannabis over time: systematic review and meta-analysis. Current drug abuse reviews. 2012;5(1):32-40.
  1. Mehmedic Z, et al. Potency trends of Delta9-THC and other cannabinoids in confiscated cannabis preparations from 1993 to 2008. Journal of forensic sciences. 2010;55(5):1209-17.
  1. Keshavan MS, et al. Changes in the adolescent brain and the pathophysiology of psychotic disorders. The lancet Psychiatry. 2014;1(7):549-58.
  1. Spear LP. The adolescent brain and age-related behavioral manifestations. Neuroscience and biobehavioral reviews. 2000;24(4):417-63.
  1. Arseneault L, et al. Causal association between cannabis and psychosis: examination of the evidence. The British journal of psychiatry : the journal of mental science. 2004;184:110-7.
  1. Di Forti M, et al. Daily use, especially of high-potency cannabis, drives the earlier onset of psychosis in cannabis users. Schizophrenia bulletin. 2014;40(6):1509-17.
  1. Moore TH, et al. Cannabis use and risk of psychotic or affective mental health outcomes: a systematic review. Lancet. 2007;370(9584):319-28.
  1. Gage SH, et al. Association Between Cannabis and Psychosis: Epidemiologic Evidence. Biological psychiatry. 2015.
  1. Rubino T, Parolaro D. Long lasting consequences of cannabis exposure in adolescence. Molecular and cellular endocrinology. 2008;286(1-2 Suppl 1):S108-13.
  1. Stefanis NC, et al. Early adolescent cannabis exposure and positive and negative dimensions of psychosis. Addiction. 2004;99(10):1333-41.
  1. Renard J, et al. Long-term consequences of adolescent cannabinoid exposure in adult psychopathology. Frontiers in neuroscience. 2014;8:361.

Personality-targeted Interventions Can Reduce Alcohol and Marijuana Use Among Adolescents


Let me state the obvious: alcohol and marijuana are the two most widely used drugs of abuse in the United States. According to the annual National Survey on Drug Use and Health (NSDUH), (the most comprehensive survey of drug use and abuse in the United States conducted by the Substance Abuse and Mental Health Services Administration (SAMHSA)) as of 2013, 86.8% of the population aged 18 or older have reported having consumed alcohol during their lifetime with over 16.6 million adults diagnosed with alcohol abuse disorder.

Of course, we all know the prevalence and extent of underage drinking, and the damage alcohol has on the developing brain has been heavily researched, not to mention all the significant secondary problems associated with alcohol abuse (car crashes, sexual assault on college campuses, falling off of balconies… ).

But here’s some numbers anyways: as of 2013, 8.7 million youths aged 12-20 reported past month alcohol use, a shockingly high number for an age group this is not legally allowed to drink alcohol…

Similarly, marijuana, which is still illegal in the vast majority of the US, is nearly as ubiquitous. According to the NSDUH 2013 survey, 19.8 million adults aged 18 or older reported past month marijuana use.

And with marijuana legalization in Colorado and Washington, a significant concern raised by many is that abuse of the drug among youths will dramatically increase even higher than it is now. The research supporting the damage marijuana can inflict on brain development is also significant.

But what if the risk of use of alcohol and marijuana by youths could be reduced? What if a teacher could be given the tools to not only identify certain risky personality traits in their students but also use that knowledge to help those at-risk students from trying and using drugs such as alcohol and marijuana? A series of studies coming out of the laboratory of Dr. Patricia A Conrod of King’s College London report having done exactly that.

SFN 2015 LogoI had the pleasure of seeing Dr. Conrod speak at the recent Society for Neuroscience Conference as part of a satellite meeting jointly organized by the National Institute on Drug Abuse (NIDA) and National Institute on Alcohol Abuse and Alcoholism (NIAAA). Dr. Conrod presented a compelling story spanning over a decade of her and her colleague’s work, in which certain personality traits amongst high risk youths, can actually be used to predict drug abuse amongst those kids. Dr. Conrod argues that by identifying different risk factors in different adolescents, a specific behavioral intervention can be designed to help reduce alcohol drinking and marijuana use in these youths. And who is best to administer such an intervention? Teachers and counselors, of course: educators that spend a great deal of time interacting with students and are in the best position to help them.

The Teacher-Delivered Personality Targeted Interventions For Substance Misuse Trial, also known as the Adventure Trial, was conducted in London during 2008-2009 and the results were first published in 2010.

This ambitious study recruited 2,643 students (between 13 and 14 years old) from 21 secondary schools in London (20 of the 21 schools were state-funded schools). Importantly, this study was a cluster-randomized control trial, which means the schools were randomly assigned to two groups: one group received the intervention while the other did not. The researchers identified four personality traits in high-risk (HR) youths that increase the risk of engaging in substance abuse. The four traits are:

  1. Anxiety sensitivity,
  2. Hopelessness
  3. Impulsivity
  4. Sensation seeking.

A specific intervention based on cognitive behavioral therapy (CBT) and motivational enhancement therapy (MET) was developed to target each of these personality traits. Teacher, mentors, counselors, and educational specialists in each school that were recruited for the study were trained in the specific interventions. In general, CBT is an approach used in psychotherapy to change negative or harmful thoughts or the patient’s relationship to these thoughts, which in turn can change the patient’s behavior. CBT has been effective in a treating a number of mental disorders such anxiety, personality disorders, and depression. MET is an approach used to augment a patient’s motivation in achieving a goal and has mostly been employed in treating alcohol abuse.

The CBT and MET interventions in this study were designed to target one of the four personality traits (for example, anxiety reduction) and were administered in two 90-minute group sessions. The specific lesson plans for these interventions were not reported in the studies but included workbooks and such activities as goal-setting exercises and CBT therapies to help students to dissect their own personal experiences through identifying and dealing with negative/harmful thoughts and how those thoughts can result in negative behaviors. Interestingly, alcohol and drug use were only a minor focus of the interventions.

The success of the interventions was determined through self-reporting. The student’s completed the Reckless Behavior Questionnaire (RBQ), which is based on a six-point scale (“never” to “daily or almost daily”) to report substance use. Obviously due to the sensitive nature of these questionnaires and need for honesty by the students, measures were taken to ensure accuracy in the self-reporting, such as strong emphasis on the anonymity and confidentiality of the reports and inclusion of several “sham” items designed to gauge accuracy of reporting over time. Surveys were completed every 6-months for 24-months (two years) which is a sufficient time frame to assess the effect of the interventions.

Most importantly, schools were blinded to which group they were placed in and teachers and students not involved in the study were not aware of the trial occurring at the school. The students involved were unaware of the real purpose and scope of the study. These factors are important to consider because it held eliminate secondary effects and helps support the direct efficacy of the interventions themselves.

The results were impressive: reduced frequency and quantity of drinking occurred in the high-risk students that received the intervention compared to the control students that did not. While HR students were overall more likely to report drinking than low-risk (LR) students, the HR students saw a significant effect of the personality-targeted interventions on drinking behavior.

Conrod et al.2013 abstract

A study of this size is incredibly complex and the statistics involved are equally complex. The author’s analyzed the data in a number of ways and published the results in several papers. A recent study modeled the data over time (the 24-months in which the surveys were collected) and used these models to predict the odds that the students would engage in risky drinking behavior. The authors reported a 29% reduction in odds of frequency of drinking by HR students receiving the interventions and a 43% reduction in odds of binge drinking  when compared to HR students not receiving the interventions.

Interestingly, the authors report a mild herd-effect in the LR students. Meaning that they believe the intervention slowed the onset of drinking in the LR students possibly due to the interactions between the HR student’s receiving the interventions and LR students. However, additional studies will need to be done in order to confirm this result.

Recall that the Reckless Behavior Questionnaire (RBQ) was utilized in this study to quantify drug-taking behavior. While the study was specifically designed to measure effects on alcohol, the RBQ also included questions about marijuana. So the authors reanalyzed their data and specifically looked at effects of the interventions on marijuana use.

Mahu et al. 2015

The found that the sensation seeking personality sub-type of HR students that received an intervention had a 75% reduction in marijuana use compared to the sensation seeking HR students that did not receive the intervention. However, unlike the findings found on alcohol use, the study was not able to detect any effect on marijuana use for the HR students in general. Nevertheless, the data suggest that the teacher/counselor administered interventions are effective at reduce marijuana use as well.

While you may be unconvinced by the modest reduction in drinking and marijuana frequency reported in these studies and may be skeptical of the long-term effect on drug use in these kids, keep in mind that the teachers and counselors that administered these interventions received only 2 or 3 days of training and the interventions themselves were very brief, only two 90-minute sessions. What I find remarkable is that such a brief, targeted program can have ANY effects at all. And most importantly, the effects well outlasted the course of the interventions for the full two-years of the follow-up interviews.

These targeted interventions have four main advantages:

  1. Administered in a real-world setting by teachers and counselors
  2. Brief (only two 90-minute group sessions)
  3. Cheap (the cost of training and materials for the group sessions)
  4. Effective!

The scope of this intervention needs to be tested on a much larger cohort of students in a larger variety of neighborhoods but it is extremely promising nonetheless. Also, it would be interesting to breakdown these data by race, socioeconomic status, and gender, all of which may impact the effectiveness of the treatments and was not considered in this analysis. Finally, how would you implement these interventions on a wide scale? I eagerly look forward to additional work on these topics.

Thanks for reading 🙂

See these other articles in Time and on King’s College for less detailed discussions of these studies.

Also see these related studies from Conrod’s group:

Castellanos-Ryan N, Conrod PJ, Vester JBK, Strain E,, Galanter M, Conrod PJ. Personality and substance misuse: evidence for a four-factor model of vulnerability. In: Vester JBK, Strain E, Galanter M, Conrod PJ, eds. Drug Abuse and Addiction in Medical Illness. Vols 1 and 2. New York, NY: Humana/Spring Press; 2012.

Conrod PJ, Pihl RO, Stewart SH, Dongier M. Validation of a system of classifying female substance abusers on the basis of personality and motivational risk factors for substance abuse. Psychol Addict Behav. 2000;14(3):243-256.

Conrod PJ, Stewart SH, Comeau N, Maclean AM. Efficacy of cognitive behavioral interventions targeting personality risk factors for youth alcohol misuse. J Clin Child Adolesc Psychol. 2006;35(4):550-563.

Conrod PJ, Castellanos-Ryan N, Strang J. Brief, personality-targeted coping skills interventions and survival as a non-drug user over a 2-year period during adolescence. Arch Gen Psychiatry. 2010;67(1):85-93.

O’Leary-Barrett M, Mackie CJ, Castellanos-Ryan N, Al-Khudhairy N, Conrod PJ. Personality-targeted interventions delay uptake of drinking and decrease risk of alcohol-related problems when delivered by teachers. J AmAcad Child Adol Psychiatry. 2010;49(9):954-963.

Important Considerations in Optogenetics Behavioral Experiments

Image credit NSF, Inbal Goshen, Karl Deisseroth.
Image credit NSF, Inbal Goshen, Karl Deisseroth.

The third and final part of my three part guest blog series on Optogenetics has been published on the Addgene blog. Addgene is a nonprofit organization dedicated to making it easier for scientists to share plasmids and I’m thrilled to be able to contribute to their blog! This post covers the running behavioral experiments utilizing optogenetics.

Check it out!


The Materials Science of Optogenetics Experiments


The second part of my three part guest blog series on Optogenetics has been published on the Addgene blog. Addgene is a nonprofit organization dedicated to making it easier for scientists to share plasmids and I’m thrilled to be able to contribute to their blog! This post covers the material science aspects of running optogenetic experiments.

Check it out!

The Formation of New Memories in the Human Brain

Image of the structure of the mouse Hippocampus (Image courtesy of
Image of the structure of the mouse Hippocampus (Image courtesy of

How are new memories created?

This is a fascinating question in neuroscience and at the very core of what makes us human. After all, our entire concept of ourselves is defined by our memories and without them, are we even ourselves? This is a pretty lofty philosophical discussion… but today we’re only interested in the neuroscience of memory.

In specific, what happens to individual neurons in the human brain when a new memory is created and recalled?

Researchers at the University of California-Los Angeles performed a study in humans that has shed some light on this important question. Published recently in the journal Neuron, the novelty of the study involved recording how many times a neuron would fire during a specially designed memory test. In other words, the scientists were able to monitor what happened to individual neurons in a human being as a new memory was being created!

Title Ison et al. 2015

This article is open access (able to downloaded and distributed for free). The article can be found here or download the pdf.

Before I go into what the researchers found, let’s see how it was done.

The subjects in the study were patients being treated for epilepsy. As part of their clinical diagnosis, they had been implanted with an electrode, a tool used to measure neuronal activity or in other words, the electrode measures how often a neuron fires. The fact these patients already had an electrode inserted into the brain for clinical reasons made it convenient for the researchers to conduct this study.

Left Temporal Lobe (
Left Temporal Lobe (

The brain region in which the electrode was implanted is called the medial temporal lobe (MTL). The image to the right is of the left human temporal lobe. The medial region of the temporal lobe is located more towards the center of the brain.

Human Hippocampus (
Human Hippocampus (

One specific region of the MTL, the hippocampus, is believed to be the primary brain region where memories are “stored”. Specifically, previous studies in animals and humans have suggested that the MTL and hippocampus are very important to encoding episodic memory. Episodic memory involves memories about specific events or places. In this study, the example of episodic memory being used is remembering seeing a person at a particular place. Another example: the game Simon™ can be considered a test of your brain’s ability to rapidly create and recall short-term episodic memories!

Simon game memory

*Note: Episodic memory is considered one of the main bifurcations of declarative memory, or memories that can be consciously recalled. The other type of declarative memory is semantic memory, which are memories of non-physical/tangible things, like facts.

To test the episodic memory of remembering a person at a particular place, images were presented to the patients while the neurons were being recorded. There were 5 different tasks (all completed within 25-30min). See Figure 1 below from the paper.

Figure 1: Experimental Design
Figure 1: Experimental Design

First, a pre-screening was done in which the patients was shown many random images of people and places. The activity of multiple neurons was recorded and the data was quickly analyzed then 3-8 pairs of images were compiled. In each pair, 1 image was “preferred” or “P” image, meaning the neurons being recorded fired when the “P” image was shown. The second image was “non-preferred” or “NP” image, meaning the neurons did not respond to it when it was shown.

The first task is the “Screening” test. Each “P” and “NP” image was shown individually and the neurons response to each was recorded. As you would expect, the neuron would fire heavily to the “P” image and not very much to the “NP” image.

The second task was the “learning task” in which a composite image of each of the “P” and “NP” image pairs was made. The person in the “P” image was digitally extracted and placed in front of the landmark in the “NP” image. After the composite images were shown, the individual images were shown again.

For example, in one image pair for one patient, the “P” image was a member of the patient’s family while the “NP” image was the Eiffel Tower (for this example, see Figure 2). The composite image in the “learning” task was the family member in front of the Eiffel Tower. Another example of a “P” image was Clint Eastwood and the “NP” image was the Hollywood sign. The composite image would therefore be Clint Eastwood in front of the Hollywood sign. (However, in some image pairs the “P” image was a place and “NP” image was a person).

The third task was “assessing learning”. The image of just the person in the composite image was shown and the patient had to pick out the correct landmark he/she was paired with. For example, the picture of the family member was shown and the patient would have to pick out the Eiffel Tower image.

The fourth task was the “recall” task. The landmark image was shown and the patient had to remember and say the person it was paired with. For example, the Eiffel Tower was shown and the patient had to say the family member’s name.

Finally, the fifth task was a “re-screening” in which each individual image was shown again so the neuron’s activity could be compared to the Task 1, pre-learning.

The activity of multiple neurons were recorded for each image for each of the tasks. The data was then analyzed in number of different ways and the activity of different neurons was reported.

And what was found?

Figure 2: Response of Neruons in the Hippocampus from One Patient
Figure 2: Response of Neurons in the Hippocampus from a Patient

Let’s go back to the family member/Eiffel tower example. The researchers were able to show that a neuron in the hippocampus responded heavily to the picture of the family member (“P” image) but not to the Eiffel Tower (“NP” image). After showing the composite image, the neuron now responded to the Eiffel Tower too in addition to the family member! (The neuron also fired a comparable amount to the individual family member image as the composite image).

As you can see in Figure 2, each little red or blue line indicates when a neuron fired. For example, in Task 1 you can clearly see more firing (more lines) to the “P” image than the “NP” image. You can see that after Task 2, the neuron responds to either the “P” or “NP” image (especially obvious in the Task 5). The middle graph indicates the firing rate of the neurons to the “NP” image and it clearly shows increased firing rate of the neuron after learning (AL) compared to before learning (BL). It may look small, but the scientists calculated a 230% increase in firing rate of the neuron to “NP” image after the learning/memory task took place!

What does this mean? It means that a new episodic memory has been created and a single neuron is now firing in a new pattern in order to help encode the new memory!

This was confirmed the other way around too. In another patient, the “P” neuron was the White House and the “NP” image was beach volleyball player Kerry Walsh. The neuron that was being recorded fired a lot when the image of the White House was shown but not so much for the Kerri Walsh image. Then the composite image was shown and the learning/recall tasks were performed. The neuron was shown to fire to both the White House image AND the Kerry Walsh image! The neuron was responding to the new association memory that was created!

Keep in mind these are just two examples. The scientists actually recorded from ~600 neurons in several different brain regions besides the hippocampus but they only used about 50 of them that responded to visual presentation of the “P” image, either a person or a landmark (the identification of visually responsive neurons was crucial part of the experiment). Remarkably, when the firing rates of all these neurons was averaged before and after the memory/learning tasks, a similar finding to the above examples was found: the neuron now responded to the “NP” image after the composite was shown!

Many other statistical analyses of the data was done to prove this was not just a fluke of one or two neurons but was consistent observation amongst all the neurons studied but I won’t go into those details now.

But what’s going on here? Are the neurons that respond to the “P” stimulus now directly responding to the “NP” image or is more indirect, some other neuron is responding to the “NP” which in turn signals to the “P” neuron to increase in firing? The authors performed some interesting analyses that both of these mechanisms may apply but for different neurons.

Finally, were all the recorded neurons that were engaged in encoding the new episodic memory located in the hippocampus? The answer is no. Responsive neurons were identified in several brain regions besides the hippocampus including the entorhinal cortex and the amygdala. But most of the responsive cells were located within the parahippocampal cortex, a region of the cortex that surrounds the hippocampus, thus not surprising it is very involved in encoding a new memory.

In conclusion, the scientists were able to observe for the first time the creation of a new memory in the human brain at the level of a single neuron. This is an important development but such a detailed analysis has never before been done in humans and, most importantly, in real time. Meaning, the experiment was able to observe the actual inception of a new memory at the neuronal level.

However, one major limitation is that the activity of these neurons were not studied in the long term so it’s unknown if the rapid change in activity is a short-term response to the association of the two images or if it really represents a long-term memory. The authors acknowledge this limitation but the problem is really in the difficulty of doing such studies in humans. It’s not really ethical to leave an electrode in someone’s brain just so that you can test them every week!

But what does all of this mean? The authors do suggest that the work may help to resolve a debate that has been going in on the psychology field since the 40s. Do associations form gradually or rapidly? These results strongly suggest new neurons rapidly respond to encode the new memory formation.

But how will these results shape the neuroscience of memory? The answer is I don’t know and no one does. Thus is the rich tapestry of neuroscience, another thread weaved by the continuing work of scientists all over the world  in order to understand what it is that makes us human: our brains.

Optogenetics in the New Yorker

Optogenetics1Excellent new article on optogenetics in The New Yorker. Optogenetics is a powerful, cutting-edge tool developed by Karl Deisseroth’s lab (profiled in the article) and is one of most significant advances in neuroscience research in decades. I recently spent two months learning the technique and we will be implementing it in the lab I work in at Rockefeller University. Optogenetics allows researchers to turn specific neurons “on” and “off” and see how those neurons are directly involved in a particular behavior. The article does a great job of profiling Deisseroth himself and explaining a little bit of the history of optogenetics and other developments in the Deisseroth lab. Enjoy!



The Scientist’s Toolbox: Techniques in Addiction Research, Part 2

Lab Mice IMG_4102

When a news article starts with the headline “A new study finds…” do you know what that means? The article is (allegedly) referring to a peer-reviewed scientific research paper. Research papers are the heart of the scientific research field and are a report of a series of experiments conducted by a scientist or team of scientists. In a future post, I’ll do a break down what a paper looks like but for now all you need to know is that the heart of the paper is the data. The data are the pieces of information that scientists have acquired from their experiments and are reporting in the scientific paper.

But how do scientists generate data?

This is one of the crucial questions in the scientific field because it refers to experimental design: 1) what is the question the scientists wishes to answer, 2) which experiments does the scientist need to design in order to answer those questions and 3) what are the different techniques and tools needed in those experiments?

This is my second post in series of posts I’m doing to show how scientists actually collect data and the various experimental techniques and tools we have at our disposal. Right now I’m only talking about neuroscience and techniques specific to the addiction field but may discuss more general biological tools and experimental techniques in the future.

In my last post in this series, I discussed the locomotor activity test (also known as the open field test), intravenous self-administration, and microdialysis. Today, I’ll discuss a behavioral technique that’s an alternative to self-administration: conditioned place preference.

 Conditioned Place Preference

Recall our discussion on self-administration. It’s a powerful technique that allows animals to administer drugs to themselves. The technique also has the potential to model initiation of drug taking, maintenance/escalation in drug taking, and even relapse-like behaviors. However, there is one major flaw with this technique. It is extremely difficult and very time consuming! After all, a mouse jugular vein is really small, which makes doing the surgeries not a trivial exercise…

Is there an easier way to study addiction that doesn’t require surgery? Thankfully, there is! Conditioned place preference (CPP) is another model to test whether animals find a drug of abuse pleasurable/rewarding or not pleasurable/aversive.

The technique is based on a Pavlovian or classical conditioning mechanism. Perhaps you’ve heard of the famous Russian scientist Ivan Pavlov? In a series of very famous experiments, he was able to cause dogs to salivate anytime he rang a bell (or any neutral stimulus for that matter). Like most famous discoveries, he wasn’t trying to do this but through careful observations he uncovered one of the basic mechanisms that underlies learning.

Figure 1: Classical Conditioning (
Figure 1: Classical Conditioning

Pavlov’s conditioning experiment was done by presenting the dogs with an unconditioned stimulus, that is to say something that will cause a response in the animal no matter what, which is called an unconditioned response. In Pavlov’s case, he would present the dog with the unconditioned stimulus of food, which would cause the unconditioned response of salivating (Figure 1). Through careful observation, he was able to identify that dogs would salivate even before he put the food in front of them, sometimes just the site of the food dish was enough to cause the dogs to salivate. He followed up on this intriguing observation.

While the food is the unconditioned stimulus, the food dish or scientist bringing the food served as a neutral stimulus that normally would have no effect on the dogs ability to salivate. Pavlov tested if he could induce this salivating effect with other neutral stimuli. A neutral stimulus that normally has no effect on the animal, called a conditioned stimulus, would become associated with the unconditioned stimulus to produce a response (the conditioned response). In Pavlov’s experiments, the conditioned stimulus (food), when paired with the unconditioned stimulus (bell), would then produce a conditioned response (salivating).

Now let’s see how Pavlov’s conditioning experiment was actually done. If he rang the bell before the conditioning (the conditioned stimulus), it would have no effect. The dogs don’t really care about the noise from the bell because it is not associated with anything in the dog’s brains. But every time the food (unconditioned stimulus) is presented to the dogs, Pavlov would ring the bell (conditioned stimulus). Now the ringing of the bell became associated in the dog’s brain with the presence of the food.

Finally, after the conditioning sessions, Pavlov would ring the bell and would remarkably cause the dogs to salivate (conditioned stimulus)! They had learned to associate the sound of the bell with the presence of the food. Just to clarify, the dogs are not “choosing” to associate the bell with food. This type of conditioning is hard wired into the brain itself—forming these type of associations is one of the things that brain does best. In fact, classical conditioning is a basic mechanism in many types of learning. To this day, Pavlov’s work remains some of the foundational experiments in the biological basis of learning.

Here’s a video I found on YouTube that summarizes everything that you just read:


The taking of a psychoactive drug can actually have a similar type of classical conditioning effect. Think about it this way, a drug is never taken in a vacuum,it is always taken in a particular context. A drug may be frequently taken in a particular location, or under particular circumstances, or even with certain people.

I’m a former cigarette smoker and this is an example of conditioning that I personally experienced. Every time I got in the car I would light up a cigarette. After months and years of smoking, I caused a classical condition effect in myself. The cigarette (unconditioned stimulus) produces that “nicotine high” and relaxing feeling that smokers crave (unconditioned response). However, driving in a car (conditioned stimulu) normally does not cause that feeling. But every time I would need to drive someplace I would smoke. Eventually, simply being in the car would cause a craving for a cigarette! The conditioned stimulus of driving became associated with the unconditioned stimulus of smoking to produce the conditioned response of nicotine craving every time I go into the car.

Classical conditioning is exactly how conditioned place preference works. In the laboratory, we can use this basic mechanism to force mice to experience a conditioned response when placed in a distinctive chamber. The mouse will even seek out that chamber and spend time in it because they know that they received a “good feeling” anytime they were in the chamber before.

This is what the chamber looks like.

CPP Chamber (© Derek Simon 2014)
CPP Apparatus (© Derek Simon 2015)

It consists of three connected boxes: a central grey one with normal flooring, a white-walled one on the left with a mesh grating as the floor, and a black-walled one on the right with steel bars on the floor. There are special trap doors (white knobs in the picture below) that can be opened or closed so that a mouse is allowed to either explore the whole apparatus or be confined to one of the chambers. When the mouse is being conditioned, the trap doors are closed and the mouse stays in only one chamber the whole time.

CPP Apparatus (© Derek Simon 2014)
CPP Apparatus (© Derek Simon 2015)

A CPP experiment consists of four main steps: 1) the pre-test day, 2) the conditioning sessions (multiple of these), 3) the post-test day, and 4) data analysis. (See Figure 2 below).

Step 1: A mouse in placed in the central grey chamber and it is allowed to explore the entire apparatus all it wants want. Both the white and black chambers represent a conditioned stimulus because right now, they have no association with anything in the mouse’s brain. The time spent in each chamber is recorded.

Step 2: Now the mouse receives an injection of drug (or saline as a control substance) and then is placed in either the white or black chamber. The mouse is forced to stay in the chamber for the entire session (usually 15-30min). That way the features of the chamber (wall color and floor texture) become associated the unconditioned stimulus of the drug. One conditioning session occurs a day for several days.

Step 3: The test day. Now the trap doors are raised and the animal is allowed to explore all three chambers again. If the experiment worked, the mouse will spend most of its time in the chamber that it received the drug injections! In other words, the mouse was conditioned to expect the drug in either the white or black chamber and, given the choice, prefers to spend time in that chamber in anticipation of the drug.

Step 4: Analysis. The time spent in the drug or saline-paired chamber on the test day is subtracted from the time spent in that chamber on the pre-test day. This difference in time is considered the quantitative measure of a successful conditioning session.

This figure summarizes a CPP experiment:

Figure 2: Diagram of a CPP Experiment (© Derek Simon 2015)
Figure 2: Diagram of a CPP Experiment (© Derek Simon 2015)

If an animal likes a drug and finds it pleasurable and rewarding, it will spend a lot of time in the conditioning chamber (see the graph). If the mouse hates the drug, it will not spend time in the conditioning chamber. By using this setup, we can test how different drugs and doses of drugs, and other types of experimental manipulations can effect how a the mouse perceives the drug.

If we were to compare self-administration to CPP, a conditioned response in the CPP experiment would be a similar measure as self-administration of a drug. Both experiments reveal that the animal likes the drug and wants to take it.

And as with self-administration, many variations on the basic setup exist but I’ll spare you those details for now…

Thanks for reading!

Stress and Addiction Part 3: Molecular Changes

Stress-BrainThis is part three on my series of posts looking at Stress and Addiction. To recap: we’ve seen that, in laboratory studies, stress increases susceptibility to drug addiction. Stress not only increases the self-administration of drugs in adult rats but stress during an early age can have a long-lasting effect on drug-taking behavior. Today, we’ll wrap up by looking at some molecular changes that might help to explain why this effect exists. I’ll conclude by addressing some questions that might have occurred during the course of this discussion.

Paper #1 Sorg 1991. Title

The first paper is examining the effects of stress and cocaine on dopamine. Dopamine is a very important neurotransmitter. All drugs of abuse cause increases in dopamine in an important region of the brain called the mesolimbic pathway. I will discuss this system in detail in the next post but for now don’t worry about the details. All you need to know is that drugs can increase dopamine.

Dopamine levels can be measured directly in the brain using the technique microdialysis (I discuss this technique in more detail in my post The Scientist’s Toolbox: Techniques in Addiction). In this first paper, the scientists use a type of stress called foot-shock stress. It is very similar to tail-pinch stress (see Part 1). The animals are placed on a grid that is connected to an electrical supply. The scientists administer a small amount of electric current to the grid, which gives the animals feet a little shock and stresses them out.

Figure 1.
Figure 1.

The microdialysis technique was used on rats that underwent foot shock stress in order to measure dopamine levels (in a region of the brain called the striatum) after the stress test. As you can see in the top graph of Figure 1, foot shock stress causes an immediate increase in the amount of dopamine released and this eventually returns to normal. The different symbols mean different stress intensity with the most intense stress represented as black squares. Interestingly, as you can see in the lower graph of Figure 1, a more intense foot shock (ie a more intense stress) causes more dopamine to be released.

Remember that I said that cocaine also causes dopamine release? So maybe stress makes cocaine feel better because it works together with cocaine to create a larger release in dopamine than cocaine would by itself. Next, the investigators decided to test this idea.

Sorg 1991. Figure 2
Figure 2.

In this experiment, mice were exposed to a weak foot-shock stress then given an injection of cocaine and the amount of dopamine released was measured. Figure 2 shows much more dopamine was released in the striatum in rats that received cocaine + stress (black squares) compared to cocaine + no stress (white squares) or just stress by itself (black circles). Perhaps the hypothesis that stress makes cocaine more pleasurable because its boosts dopamine released might be true?

Paper #2

Zhou 1996. Title

Recall from Part 1, that stress activates the HPA axis, which results in release of the stress hormone cortisol (corticosterone in rats and mice). But do drugs of abuse also activate the HPA axis? This next paper—done in lab that I work in—takes a look at this question.

Figure 1.
Figure 1.

Cocaine was given to rats under a number of different conditions. In the first experiment, cocaine effects on the HPA axis were examined in the short term (acute cocaine use). Rats were injected with either saline for two days, cocaine for 1 day, cocaine for 1 day and saline for 1 day, or cocaine for 2 days. After the injections, blood was drawn from the animals and the corticosterone in the serum was measured.

*Technical notes: 1) Serum is the liquid part of blood and it does not contain the red blood cells and clotting proteins. Serum is often used when measuring hormones in the blood. 2) Corticosterone can be measured multiple ways but this experiment used something called a radioimmunoassay (RIA). I’ll save the explanation of it for a future Scientist’s Toolbox post.

As you can see in Figure 1, immediately after the rats receive cocaine (either 1 day or 2 days) corticosterone increases. This means that cocaine has resulted in activation of the HPA axis. Interestingly, the animals received 1 day of cocaine and 1 day of saline did not show high corticosterone levels which means that the levels have returned to normal after the cocaine.

But what happens with repeated cocaine use (chronic cocaine use)? Addiction develops because of chronic use of the drug so are any changes occurring after many days of cocaine use?

Figure 2.
Figure 2.

Interestingly, in Figure 2, corticosterone is high after 3 days of cocaine but after 14 days of cocaine corticosterone levels are much lower! What’s going on here? What these data suggest is that 14 days of cocaine use has caused a change in the HPA axis activity. The cocaine has activated the HPA axis so frequently the axis has compensated for this over activation. The activity of the HPA axis response has been blunted because of the repeated cocaine use.

This one small example of how drugs can cause long lasting molecular adaptations and changes in the brain. Perhaps this is why stress helps to make someone more vulnerable to addiction, because changes occur both at the level of dopamine release (paper #1) and in HPA axis activity (paper #2). Both drugs and stress have similar molecular effects that may work together! I’d like to very briefly discuss one more paper that combines both of these concepts.

Paper #3

Boyson 2014. Title

This paper is complicated but I’m just going to present a small amount of the data. The key points you need to know is that the scientists are using social stress (see Part 1) in this paper for two key experiments 1) self-administration to measure cocaine taking behavior and 2) microdialysis to measure dopamine release. However, they also inject a chemical compound directly into the rat’s brain that blocks HPA axis activity. This chemical acts at the starting point in the HPA axis: the activity of CRF is blocked (the chemical name is abbreviated as CP). Let’s see what happens in this experiment!

*Technical notes: 1) the drug actually prevents the action of CRF interacting with its receptor. Chemicals that do this are called antagonists. Therefore, the scientists are injecting a CRF Receptor antagonist into the rat brains. 2) as a control, an inactive solution is also injected into some animals. This is called artificial cerebral spinal fluid (aCSF). For the drug studies, the correct comparision is CP vs aCSF.

Figure 1.
Figure 1.

Like we saw in other papers, stress increases self-administration (Figure 1, black circles) compared to no stress (white triangles). However, when you give the CP at a high dose (light grey circles) compared to a low dose (dark grey circles) it reduces the self-administration! This means that blocking HPA axis activity reduces the effects of the stress on the cocaine self-administration. Cool!

Figure 2.
Figure 2.

Next, they did a very similar experiment but only this time measure the interaction between stress, cocaine, and the CRF antagonist on dopamine release. The results are presented in Figure 2. Animals that were stressed and than given a dose of cocaine but not the CP (stress + cocaine + aCSF, black circles) released a large amount of dopamine compared to animals that were only given the cocaine injection (white triangles), which is consistent with findings from Paper #1. Amazingly animals that were stressed and then given cocaine + the anti-HPA axis drug CP showed reduced amounts of dopamine released at bot a low dose of CP (dark grey circles) and high dose (light grey circles). These experiments show that the effect of stress on cocaine taking behavior might be because the stress activates the HPA axis which causes more dopamine to be released.

*Technical note: I described this experiments very briefly but they are extremely technically challenging and probably required months of hard work just to make the two little graphs!


Finally, if we summarize the papers from Part 1, 2 and 3 we can come up with a little mechanism to help explain the different results from the different papers. Based on the data, stress can contribute to the vulnerability of becoming an addict because it activates the HPA axis and increase the dopamine released, which may cause the drug to feel better to a person and make them want to take more of it. There may be a synergy between stress and drugs that changes brain function so that addictive drugs feel more addictive.

You probably noticed I used the word “may” many times and this is because our proposed mechanism requires a lot more testing. In fact, we barely even scratched the surface with this discussion! There are literally hundreds more papers looking at many other details just on stress and addiction. Hopefully this post and the previous two can give you a little appreciation for the difficultly in learning anything about how addiction really works and what specific changes occur in the brain from drug use! Science is a challenging and time-consuming pursuit but also totally worth it!

To wrap up our discussion on stress and addiction, I’ll address some questions/criticisms that you might have with the research papers in this and previous two posts.

Q & A

Some questions about the research you might have and my answers:

Q: Only the psychostimulants cocaine and amphetamine were looked at in these papers. Does stress have the same effects on other drugs of abuse?

A: Yes. The effect of stress is the same with nearly all drugs of abuse tested including the opioid morphine and heroin, alcohol, and nicotine. The neural machinery that is responsible for enhancing the addictive powers of drugs is common to all drugs of abuse.

Q: Only the initial stages of drug taking were looked at in these papers. That is to say, the role of stress was only discussed in the initiation of addiction. How does this translate into progression to full blown addiction?

A: The effect of stress is consistent regardless of where you are on the addiction continuum: stress enhances the reinforcing properties of drugs of abuse. That is to say, stress makes the pleasurable feeling from drugs more pleasurable. However, in humans, you will never get as clear of an effect (that means, easily testable) as you will in laboratory animals. Humans experience many different types of stress throughout a single day and the specific effect of stress on drug taking depends on the type/length/frequency of the stress and other environmental factors. Nevertheless, in controlled clinical studies, changes in HPA axis function as a result of drug use have been widely reported. A feed-forward mechanism exists in which stress promotes drug taking and then drug effects the stress response so that the next stressor has a greater effect on drug taking, etc.

Q: Can stress trigger relapse?

A: Yes, this is one of the most well studied effects of stress on drug taking: stress can trigger drug cravings in abstinent individuals. In the laboratory, an animal can be taught to lose its self-administration behavior by switching the drug to a neutral substance like saline. Therefore, when the animal nose pokes it does not get drug and eventually it doesn’t nose poke at all. This is called extinction. Amazingly, if you stress an animal with foot-shocks or some other phase and then test it’s self-administration behavior the animal will go back to lever pressing again!

Thanks again for reading! If you stuck through all three of Stress and Addiction posts please comment or email me. I would love to know!

Next time: Doping on Dopamine.

The Science of Stress and Addiction: A Mini-review of the Research, Part 1


Why does one person become an addict and another person does not?

The vulnerability/susceptibility to addiction is one of the most important questions in the addiction field and also one of most difficult to answer. Is it genetics, the environment, or the addictive power of the drug itself? Spoiler alert: the answer is all three! But rather than trying to explain the answer in mere blog post (which is impossible), I think it’s better to tackle different aspects of the question in multiple posts (well, I probably could do it in one but I’m scientist: I would be a doing a disservice to you and to myself if I didn’t do a thorough job). This is the first post in this series.

Over the years, a lot of research has been done that has been able to show that stress can contribute to why one person becomes an addict and why another person does not. But how do we know that stress is important? And what is “stress” anyways? Let’s get our information straight from the horse’s mouth so to speak: a review of a few research papers that look at this question.

What is Stress?

Stress is one of those terms that is used often but may not be well understood. At one point or another we’ve all described our day as “stressful” and we all understand what this means but just take a moment and try to describe what “stressful” means in words that apply to ALL “stressful” situations. It’s tough, right? That’s because stress can mean any number of things in a number of different contexts.

In biology, we have a specific definition of stress: a response (usually immediate and automatic) to an environmental condition or factor, a stimulus, or other type of challenge. The body has several systems in place that mediate the stress response. For example, you probably have heard of “fight-or-flight”, which is one of the body’s stress responses.

The Hypothalamic-Pituitary-Adrenal (HPA) Axis
The Hypothalamic-Pituitary-Adrenal (HPA) Axis

Another of the key components of the body’s response to stress is the activation of the hypothalamic-pituitary-adrenal (HPA) axis. See the diagram. The HPA axis is hormonal system that involves chemical communications between several organs.

  • First, something happens that requires the body to respond to it, this could be sudden change in temperature, or an attack by an aggressor, or some other challenge. This factor is called a stressor.
  • Second, the stressor causes the hypothalamus, a region of the brain that controls many of the body’s functions, to release a small protein molecule called corticotropin releasing factor or hormone (CRF or CRH)
  • Third, CRF acts on the anterior pituitary gland, a small organ that secretes many different hormones. CRF stimulates the pituitary to release another small protein called adrenocorticotropic hormone (ACTH). ACTH then enters the blood stream.
  • Fourth, ACTH travel through the bloodstream until it finds its way to the adrenal glands, small organs that are located on top of the kidneys.
  • Finally, ACTH causes the adrenal gland to release cortisol (corticosterone in rodents), the “stress hormone.” Cortisol has many effects on many different organs throughout the body. Cortisol can also act on the hypothalamus and the pituitary gland themselves in order to inhibit their release and turn the HPA axis “off” until the next stressor. This is called a negative feedback loop.

Note: This is of course, a simplified model and there is a whole field of research devoted to working out the precise molecular mechanisms that regulate the HPA axis and how it responds to many different kinds of stressors.

Stress plays an important role in addiction. Stressors can make a drug seem more appetizing or even make it even feel better (more pleasurable). Anecdotally, after a stressful day, did you ever feel like you really needed a drink? Or, for the current and/or former smokers, how a cigarette was especially satisfying after a particularly jarring event? There’s a neurobiological reason for that feeling!

How do we know stress is important in addiction?

We are going to examine a few research papers that span over two decades (this discussion will be split over two posts). Each paper will reveal a little piece of the puzzle about why stress makes drugs more addictive. However, a Google Scholar search for “stress and addiction” gives you 527,000 hits! Basically, I chose these ones because they are easy to explain and, more or less, fit together in a sequence. Also, they all use one or more of the techniques that I described in my last post: The Scientist’s Toolbox: Techniques in Addiction Research, Part 1. I encourage you to read it before proceeding.

As we go through, try to keep the question we are trying to answer at the back or your mind: Does exposure to stress make it easier to become an addict and, if so, how does it do this? But this is a big question so it’s broken down into little pieces that each paper will try to answer. By the end of the second post, all the little pieces should add up to the bigger story.

Paper #1

Piazza 1990. Title
Paper #1

Both of the papers we’ll go over today look at what effect stress has on the behaviors of rats exposed to psychostimulants, either amphetamine or cocaine.

As I described in The Scientist’s Toolbox, psychostimulants cause an animal to move around more, and subsequent doses, over a period of a few days, increase that movement. Recall that this phenomenon is called locomotor sensitization.

Figure 1: Behavioral sensitization to amphetamine. Locomotor activity test (left panel) and self-administration (right panel).
Figure 1: Behavioral sensitization to amphetamine. Locomotor activity test (left panel) and self-administration (right panel).

In the first paper, rats are given 4 injections of amphetamine, one injection of amphetamine every three days and, sure enough, after the fourth injection exhibit greater locomotor activity; these rats are exhibiting locomotor sensitization to amphetamines. These results are shown in the left panel of Figure 1: black circles (4th dose of amphetamine) vs white circles (1st dose). Similarly, rats were given the same regimen of injections and 24hrs after the fourth injection self-administration of amphetamine was tested. As show in the right panel of Figure 1, only animals that were previously exposed to amphetamine (black circles) compared to saline-exposed rats (white triangles) self-administered amphetamine (nose-poked in order to receive drug infusions).

For the next experiment, there are two groups of rats: one group is exposed to stress and other is not. The type of stressor used in these experiments is called tail-pinch and it is exactly what it sounds like: a device is set to deliver a quick squeeze to the rat’s tail. This causes just a mild amount of pain and is very unexpected to the animals, thus it “stresses them out”. This means, as shown in other studies, that tail-pinch activates the HPA axis (increased cortisol secretion). In this experiment, no apparatus is used so instead the rats are placed in a bowl one at a time and then the scientist pinches the tail using forceps (tweezers).

Figure 2: Impact of stress on the behavioral effects of amphetamine. Locomotor activity (left panel) and self-administration (right panel).
Figure 2: Impact of stress on the behavioral effects of amphetamine. Locomotor activity (left panel) and self-administration (right panel).

Each animal in the stress group is exposed to 1min of tail pinch, 4times/day for 15days. This represents a chronic stress. The non-stress group rats are also placed in the bowl but no tail-pinch is applied. This is important to make sure that simply being handled or being put in the bowl is not having an effect. This non-stress group is an essential part of the experiment because it allows us to compare the effects of the stress test to animals that did not receive the test. It is called a control group. Controls are necessary for every experiment so that the scientist can make a useful comparison and allows him/her to interpret the experimental results.

Back to the experiment: 24hrs after the last tail pinch, both groups of animals are give an injection of amphetamine and their locomotor activity is measured. As you can see in the left panel of Figure 2, amphetamine caused greater movement in the animals that were stressed (black triangles) compared to the non-stressed control group (white triangles). This means, the ability of amphetamine to affect the animal’s movement was enhanced by stress.

In the second part of this experiment, the same stress exposure procedure is done but then the animals undergo a self-administration experiment (if you’re interested in the details, the catheter surgeries are completed before the stress exposure is started). As shown in the right panel of Figure 2, the stress group (black triangles) successfully acquired self-administration, meaning they gradually self-administered more and more amphetamine every day of the experiment. This behavior is similar to how human addiction begins, escalation in the amount of drug taken each time. Interestingly, the non-stress control group (white triangles) self-administered amphetamine for the first two days but gradually stopped and didn’t really seem interested in receiving the drug by day 5.

Figure 3: Comparison of prior exposure to drug (sensitization) to stress: impact on the behavioral effects of amphetamine. Locomotor activity (left panel) and self-administration (right panel).
Figure 3: Comparison of prior exposure to drug (sensitization) to stress: impact on the behavioral effects of amphetamine. Locomotor activity (left panel) and self-administration (right panel).

In Figure 3 the authors of this study compared the effect of prior exposure (sensitization) to stress for both the locomotor and self-administration experiments. They did this by dividing the experimental data by the control data (this is called normalization). There appears to be no difference between prior exposure and stress on locomotor activity and self-administration.

The authors conclude that stress is as potent as prior exposure to enhance the properties of the drug; stress exposure may be a significant factor why some people become addicted while others do not.

So very cool, it looks like stress can cause rats to want to self-administer more amphetamine and enhance the physical effects of the drug. Many other studies have found similar effects of stress. Let’s take a look at one paper that uses a different stress and a different drug.

Paper #2

Paper #2
Paper #2

In this study, the drug studied is the psychostimulant cocaine and the stressor is social stress. There are many variations of the procedure used for social stress but many are similar. In this paper, the rat to be stressed (the intruder) is placed in the home cage of a different rat (the aggressor). Because rats are territorial, this provokes the aggressor to attack the intruder. The intruder is left in the aggressor’s cage until it is bitten 10 times by the aggressor. The intruder rat is then placed in a mesh cage and put back in the home cage of the aggressor for a period of time. This way the intruder can still see and smell its attacker but can’t be physically attacked. This is repeated for several days. Social stress has been shown to be a very potent stressor, probably more so than tail pinch.

Note: The other study looked only at males but this study is interested in both males and females but for what we are interested in, this is a minor detail.

Haney 1995. Fig 1
Figure 1: Corticosterone levels in a novel environment in stresses and un-stressed male and female rats

First, activity of the HPA axis is measured by looking at corticosterone levels (this it the rodent equivalent of cortisol) when exposed to a novel environment (a novel environment is itself a type of mild stress). As you can see in Figure 1, rats that were previously exposed to social stress (black symbols) released higher amounts of coricosterone when placed in the novel environment compared to their unstressed counterparts (white symbols). This means the social stress has resulted in activation of the rat’s stress response, the HPA axis. Interestingly, female rats seemed to have a greater stress response overall.

Figure 2: The effect of social stress on cocaine self-administration.
Figure 2: The effect of social stress on cocaine self-administration.

Next, the effect of social stress on self-administration of cocaine is tested. As we saw with tail pinch stress and amphetamine, social stress caused an enhanced acquisition of cocaine self-administration whereas unstressed animals did not acquire cocaine self-administration. These data are presented in Figure 2, stressed rats (black symbols) and unstressed rats (white symbols).

In this paper, the authors also conclude that social stress—and activation of the HPA axis—makes it easier for a rat to acquire to cocaine self-administration; stress makes the rat want to self-administer cocaine.

 To summarize: these studies have found that two different types of stress have a similar effect on two different kinds of drugs. The first study found that tail-pinch stress increases the amount of locomotor activity induced by amphetamine. This stress also increases the amount of drug that the animals will self-administer. The second paper found that a different kind of stress, social stress, caused an activation of the HPA axis and had the same effect on cocaine self-administration: animals exposed to stress acquired self-administration behavior.

Based on the self-administration data, we conclude that stress caused the drugs to have a greater reinforcing effect. This is measure of the amount of pleasure the animals get from the drug. Therefore, we interpret that the stress made the drugs more pleasurable to the animals because they wanted to self-administer more drug.

However, there are some caveats that need to be briefly discussed. Both of these studies only looked at short term self-administration experiments (5 days) and both used relatively low doses. Many studies have found the rats and mice will self-administer cocaine and amphetamine regardless of whether they were exposed to stress or not. Nevertheless, these two papers are examples of how exposure to stress can cause a drug to be more addictive (technically, more reinforcing).

Next, we’ll look at some more stress studies that try to identify the molecular mechanisms—what stress is actually doing to the brain—of stress and addiction.

If you made it this far, thanks so much for sticking with it!

Just as a last thought: both of these are old papers, from the 90s and both are not very extensive (compared to today). This may sound incredible but it’s just an example of how difficult and time consuming science really is!

Thanks for reading  🙂

The Scientist’s Toolbox: Techniques in Addiction Research, Part 1

Lab Mice IMG_4102
(Image © Derek Simon 2015)

One of the most important questions that every scientist learns to ask is “How do you know that…?” As scientists, we are trained to be skeptical. When we consider a bit of research done by a colleague, before we are inclined to believe the data,  we need to be sure that they conducted the right experiments and that those experiments were done correctly. This doesn’t mean that scientists are stubborn or closed-minded. The reality is quite the opposite. Scientists are ready to incorporate new ideas and new results but first we need to know that the data are real. That’s what being a skeptic is all about: reserving judgment until you know all the facts.

The question “How do you know that..?” is one of the intellectual tools we use when considering whether or not data are real or not. This question has two parts: 1) how do you measure the thing that you interested in and 2) how do you know the effect you are seeing is actually based on what you think it is? What type of comparisons do you need to make in order to test the effect you’re interested in?

The first point of the question relies on special tools, equipment/technology, and experimental setups that are used to take measurements. For example, if you want to know how much a mouse likes taking a drug, then you need a way to measure how much drug it takes and how often it takes the drug (more on this in a bit). Today, I’ll go over a few of the tools that we use in addiction research.

The second part is more important (and more difficult to explain) but is really at the heart of the scientific method. It is all about experimental design and making sure you make the proper comparisons and analyses. I won’t discuss these details any more right now but will save this discussion for a future post.

Instead, let’s take a look at a few of the tools a scientist studying drug addiction has in his/her toolbox.

Locomotor Activity Test

The psychostimulants amphetamine and cocaine act in very similar ways and have very similar effects on the brain. We know that stimulants sort of “amp you up” or make you feel like you have more energy. Think of how you feel after drinking too much coffee. And what do you do when you have more energy? You tend to move around more (maybe you feel a little twitchy/antsy after too much of that coffee…). The same thing happens to mice and rats.

Locomotor Activity Test Chamber with a mouse. Image from UC-Davis Mind Institute (
Locomotor Activity Test Chamber with a mouse. Image from UC-Davis Mind Institute (

We can measure the amount of movement using a locomotor activity test. This test uses a special piece of equipment that uses light beams and a light-sensitive detector. Whenever the animal moves around the test box, the light beams are broken and the detector records that information. One way to analyze the data is by simply plotting beam-breaks (photo-cell counts are the same thing) that occur over the time of the test period. This way you have a measure of how much the animal moves around in a certain amount of time (more beam-breaks/time unit equals greater movement). A more sophisticated analysis of this same data can actually give you information on where in the box the animal spends its time. Does is just pace back and forth in a small area of the box or does it explore the entire chamber? This type of exploratory behavior data is valuable information and can be useful to other fields that may or may not study drug addiction. The general test for this exploratory behavioral analysis, regardless of speed of the movement caused by drugs, is the open field test.


Multiple test boxes with a computer that collects the data. Image from Douglas Mental Health Institute (
Multiple test boxes with a computer that collects the data. Image from Douglas Mental Health Institute (

An interesting phenomenon has been identified with psychostimulants. If you give an animal an injection of cocaine it will move around more compared to regular animals. But if you give it another dose of cocaine the next day it will move around even more than it did on the first day. This is called locomotor sensitization and is an important property of psychostimulants like amphetamine and cocaine.

The graphs below are real data that I took from a figure from one of our lab’s papers so you can see what locomotor sensitization looks like.

Cocaine-induced locomotor sensitization. Unterwald EM et al. J. Pharmacol. Expt. Ther. 1994.
Cocaine-induced locomotor sensitization. (Unterwald EM et al. J. Pharmacol. Expt. Ther. 1994.)

It’s a little hard to read but there are two groups of animals: one that receives cocaine injections (the top line) and the other that receives saline injections (the bottom line). Saline is a saltwater solution that is a standard control solution that has no biological effects. Each data point represents an average of several animals from each group. The baseline graph shows the locomotor activity before injections (no differences). As you can see, at day 1 the cocaine animals are already moving more than the saline group. This increase in movement continues over the 14 days of the experiment, evidence of locomotor sensitization.

This video shows an analysis of locomotor activity using video tracking software instead of light-beam breaks.


Locomotor activity is all good and well but not all drugs of abuse cause locomotor sensitization. More directly related to addiction in humans, how do we even know if the animal likes the drug or wants to take the drug? Humans addicts crave the drug and compulsively use it, meaning the desire to do the of the drug overpowers the addict’s self-control. Is there a way we can study this type of drug-taking behavior in animals? The answer is yes!

Self-administration is a very versatile and powerful technique used throughout the addiction field. This technique allows the animal to control whenever it takes the drug and however much it wants. We can study many different aspect of drug taking using self-administration.

A diagram for a typical self-administration chamber. Image from Med Associates (
A diagram for a typical self-administration chamber. Image from Med Associates (


The basic idea is is simple: The rodent (mouse or rat) is placed in a chamber and presented with two levers. If the mouse the presses one lever (the active lever) it receives a dose of drug but if it presses the other lever (inactive lever) it does not. The self-administration sessions are run for a set period of time and the number of presses is recorded for each lever. Over the course of several days the animal steadily increases the amount of lever presses, thus the amount of drug it takes. Meaning the animal learns how to take drug and then takes more and more of it. Just like a human addict would do!

Alternatively, the mouse can poke its nose at a special hole that acts just like the active lever. I’ll use “lever press” and “nose poke” interchangeably because they essentially mean the same thing.

Here’s a little cartoon I found on YouTube of a rat that is self-administering nicotine.


Here’s another video that shows a real mouse self-administering a natural reward (meaning not a drug of abuse but food in this case).


There are several important variations to this basic idea that help scientists to not only make the experiments easier to control and data better/easier to analyze, but allow different aspects of drug taking to be studied.

For example if you are studying alcohol addiction, then when the mouse presses the lever a spout may appear that allows the animal to drink the alcohol (the inactive lever produces a bottle of water only). This is perfect for testing alcohol self-administration because both humans and mice drink alcohol. But what if you want to study heroin or cocaine self-administration? Humans (nor mice) drink or eat these drugs. So how does the drug get delivered to the mouse when it presses the lever?

The answer is intravenous self-administration. In this version, a small surgery is performed where a small tube (a cathether) is threaded into the jugular vein of the animal. This tube is fixed to the mouse back and attached to another tube that is part of the self-administration apparatus. This time when the mouse hits the lever, a dose of drug is pumped directly into its vein! See the diagram and videos above for more details.

Intravenous self-administration has several advantages.

  • As explained above, it allows us to deliver drugs to animals that won’t take them orally.
  • It allows the drug to act immediately on the animal because the drug is being delivered directly into the bloodstream.
  • It allows us to control the dose of the drug. When the mouse hits the lever (or nose pokes) it receives a fixed amount of drug that the scientist decides on ahead of time. That way we know how much total drug the mouse takes during a single self-administration session.
  • There is no variability in whether the animal is receiving the full dose or not. For example, if the lever press results in a food pellet, there is no guarantee the animal will eat the whole thing. But if you set the self-administration apparatus to deliver 0.5mg of heroin every time the lever is pressed, then there is no doubt if the full 0.5mg dose is delivered to mouse ever time.

Warning: not for the squeamish! This video shows you how to do the catheter implantation surgery on a mouse that will be used for intravenous self-administration!

Finally, best of all, self-ad can be used to address many different types of questions related to different stages in the addiction cycle. Here I briefly describe some of the more common experimental questions and applications that self-ad can help to address.

  • Initial use and escalation of use. How much will the animal take when it is first exposed to the drug? Will the animal reach a ceiling in the amount of drug it will take in a single session?
  • Maintenance of drug taking. One cool variation is you can make it more difficult for the animal to get the same dose of drug. This is called a progressive ratio self-administration. For example, the animal may need to press the lever 5 times before it receives a dose. You can keep increasing the number of presses during each session to see how hard the animal will work for a dose. One way this experiment can be interpreted is how badly does the animal want the drug? Some animals will press the lever many, many times just to get a small dose. This type of behavior is similar to the intense cravings that human addicts can experience.
  • Extinction and Relapse. You can run a special type of experiment where you run a self-administration experiment like normal and then change it so that the active lever no longer gives the animal a dose of drug. Eventually, the animal presses the lever less and less as it learns that it will no longer get the drug. This is called extinction of self-administration. This is like being in a rehab clinic where you are prevented from taking the drug. However, after the extinction sessions, if the scientist gives the animal another does of drug this will causes animal to start pressing the lever at high rates again. This a called reinstatement of self-administration and is model of relapse. What other types of conditions or factors can cause reinstatement (relapse behavior)? This situation is just like an abstinent cocaine addict who may not be craving cocaine but if he/she takes even a single hit, this can be sufficient for that person to sink back into full-blown addiction.

Let’s take a look at some real data. The graph below is from a paper from our group that looks at oxycodone self-administration in mice.

Oxycodone self-administration by adult and adolescent mice. (Zhang Y et al. Neuropsychopharmacol. 2009.)
Oxycodone self-administration by adult and adolescent mice. (Zhang Y et al. Neuropsychopharmacol. 2009.)


This study is interested in comparing oxycodone self-administration between adult mice and adolescent mice. As you can see, the number of nose pokes at the active hole (remember, same thing as a lever presses) increases during the course of the experiment (don’t worry about FR1 vs FR3) while the inactive hole is ignored, because it does not result in drug administration. Note that the nose pokes are plotted over the time of the administration sessions (2 hours) and that 9 sessions are run (one every day).


The types of experiments I’ve described so far are great ways of studies addictive behaviors but they don’t really tell you about what’s going on in the brain. These behavior experiments are useful in themselves but they are much more powerful if they can be combined with another type of experiment that gives you a window into what’s changing in the brain at the same time as the behaviors.

In my post Synapse to it, I described how neurotransmitters are released by the pre-synaptic neurons into the synaptic cleft so that they can act on receptors located on the post-synaptic neuron. Using microdialysis, you can sample the fluid that exists in the synaptic cleft and actually measure the amount of neurotransmitters being released!

This is an extremely difficult and very technically complicated technique and I will only go into the basics about it. First, the microdialysis probe is surgically placed into a region of the brain that you are interested in studying.

The microdialysis probe itself is like a very thin piece of tubing that allows the experimenter to flow fluid into it one side(inlet) and collect the fluid that flows out of the other side (outlet). At the tip of the probe (the part that’s actually inside the brain) is a special type of material that allows fluid from inside the brain to flow into the tubing (a semi-permeable membrane).

Schematic of a microdialysis probe. Image from Wikipedia.
Schematic of a microdialysis probe. Image from Wikipedia.

After the surgery, you run your behavioral experiment, and while you are doing that you start flowing fluid into the brain. The fluid that the microdialysis probe flows in is of a similar consistency to the fluid that exists naturally in the brain. As the fluid inside the probe moves through the tubing, it causes fluids in the brain to enter into the probe and through the tubing where it can be collected when it flows out of the tubing.

Let’s say you give an animal a drug that causes a neurotransmitter to be released in the brain region you are interested in. Then some of those released neurotransmitters will enter the microdialysis probe because some of the fluid that enters the probe is from the synaptic cleft.

You keep collecting fluid at different time points during your experiment. When the experiment is over, then you can use chemistry to determine what neurotransmitters are in the fluid you collected. Best of all, you can determine how much of those neurotransmitters you have! How you do actually use chemistry to do this is a very technical part of the procedure and is not important to this discussion.

And all that work gives you a nice graph of the neurotransmitters that are released at different times during your experiment.

Now for some real data. Below are figures from a paper that our lab produced that uses microdialysis to study release of the neurotransmitter dopamine.

Evidence of probe placement in the Caudate  Putamen. (Zhang Y et al. Brain Res. 2001.)
Evidence of probe placement in the caudate putamen. (Zhang Y et al. Brain Res. 2001.)


Cocaine-induced increase in DA. (Zhang Y et al. Brain Res. 2001.)
Cocaine-induced increase in DA. (Zhang Y et al. Brain Res. 2001.)


In this study, the effect of cocaine on dopamine release in a region of the brain called the caudate putamen is being studied. The first image shows you that the microdialysis probe was placed in the right area of the brain (the white line that pierces through the dark area is the tract in the caudate putamen). The graph shows that injection of cocaine (the arrows) causes an increase in dopamine release in this brain region. Interestingly, the dopamine levels have returned to normal by the end of the experiment. Note: C57Bl/6J is the strain of mouse used in this study.

These are just three of the techniques that are used in addiction research. But we scientists have very big toolboxes! I’ll to explain some more in a later post.

Feel free to contact me or comment if you have questions!

Thanks for reading 🙂