Apathy

Le Heron et al. (2018) defines apathy as a marked reduction in goal-directed behavior. But in order to move, one must be motivated to do so. Therefore, a generalized form of impaired motivation also hallmarks apathy.

The authors compiled for us a nice mini-review combing through the literature of motivation in order to identify, if possible, the neurobiological mechanism(s) of apathy. First, they go very succinctly though the neuroscience of motivated behavior. Very succinctly, because there are literally hundreds of thousands of worthwhile pages out there on this subject. Although there are several other models proposed out-there, the authors’ new model on motivation includes the usual suspects (dopamine, striatum, prefrontal cortex, anterior cingulate cortex) and you can see it in the Fig. 1.

Fig. 1 from Le Heron et al. (2018). The red underlining is mine because I really liked how well and succinctly the authors put a universal truth about the brain: “A single brain region likely contributes to more than one process, but with specialisation”. © Author(s) (or their employer(s)) 2018.

After this intro, the authors go on to showcasing findings from the effort-based decision-making field, which suggest that the dopamine-producing neurons from ventral tegmental area (VTA) are fundamental in choosing an action that requires high-effort for high-reward versus a low-effort for low-reward. Contrary to what Wikipedia tells you, a reduction, not an increase, in mesolimbic dopamine is associated with apathy, i.e. preferring a low-effort for low-reward activity.

Next, the authors focus on why are the apathetic… apathetic? Basically, they asked the question: “For the apathetic, is the reward too little or is the effort too high?” By looking at some cleverly designed experiments destined to parse out sensitivity to reward versus sensitivity to effort costs, the authors conclude that the apathetics are indeed sensitive to the reward, meaning they don’t find the rewards good enough for them to move.  Therefore, the answer is the reward is too little.

In a nutshell, apathetic people think “It’s not worth it, so I’m not willing to put in the effort to get it”. But if somehow they are made to judge the reward as good enough, to think “it’s worth it”, they are willing to work their darndest to get it, like everybody else.

The application of this is that in order to get people off the couch and do stuff you have to present them a reward that they consider worth moving for, in other words to motivate them. To which any practicing psychologist or counselor would say: “Duh! We’ve been saying that for ages. Glad that neuroscience finally caught up”.  Because it’s easy to say people need to get motivated, but much much harder to figure out how.

This was a difficult write for me and even I recognize the quality of this blogpost as crappy. That’s because, more or less, this paper is within my narrow specialization field. There are points where I disagree with the authors (some definitions of terms), there are points where things are way more nuanced than presented (dopamine findings in reward), and finally there are personal preferences (the interpretation of data from Parkinson’s disease studies). Plus, Salamone (the second-to-last author) is a big name in dopamine research, meaning I’m familiar with his past 20 years or so worth of publications, so I can infer certain salient implications (one dopamine hypothesis is about saliency, get it?).

It’s an interesting paper, but it’s definitely written for the specialist. Hurray (or boo, whatever would be your preference) for another model of dopamine function(s).

REFERENCE: Le Heron C, Holroyd CB, Salamone J, & Husain M (26 Oct 2018, Epub ahead of print). Brain mechanisms underlying apathy. Journal of Neurology, Neurosurgery & Psychiatry. pii: jnnp-2018-318265. doi: 10.1136/jnnp-2018-318265. PMID: 30366958 ARTICLE | FREE FULLTEXT PDF

By Neuronicus, 24 November 2018

Painful Pain Paper

There has been much hype over the new paper published in the latest Nature issue which claims to have discovered an opioid analgesic that doesn’t have most of the side effects of morphine. If the claim holds, the authors may have found the Holy Grail of pain research chased by too many for too long (besides being worth billions of dollars to its discoverers).

The drug, called PZM21, was discovered using structure-based drug design. This means that instead of taking a drug that works, say morphine, and then tweaking its molecular structure in various ways and see if the resultant drugs work, you take the target of the drug, say mu-opioid receptors, and design a drug that fits in that slot. The search and design are done initially with sophisticated software and there are many millions of virtual candidates. So it takes a lot of work and ingenuity to select but a few drugs that will be synthesized and tested in live animals.

Manglik et al. (2016) did just that and they came up with PZM21 which, compared to morphine, is:

1) selective for the mu-opioid receptors (i.e. it doesn’t bind to anything else)
2) produces no respiratory depression (maybe a touch on the opposite side)
3) doesn’t affect locomotion
4) produces less constipation
5) produces long-lasting affective analgesia
6) and has less addictive liability

The Holy Grail, right? Weeell, I have some serious issues with number 5 and, to some extent, number 6 on this list.

Normally, I wouldn’t dissect a paper so thoroughly because, if there is one thing I learned by the end of GradSchool and PostDoc, is that there is no perfect paper out there. Consequently, anyone with scientific training can find issues with absolutely anything published. I once challenged someone to bring me any loved and cherished paper and I would tear it apart; it’s much easier to criticize than to come up with solutions. Probably that’s why everybody hates Reviewer No. 2…

But, for extraordinary claims, you need extraordinary evidence. And the evidence simply does not support the 5 and maybe 6 above.

Let’s start with pain. The authors used 3 tests: hotplate (drop a mouse on a hot plate for 10 sec and see what it does), tail-flick (give an electric shock to the tail and see how fast the mouse flicks its tail) and formalin (inject an inflammatory painful substance in the mouse paw and see what the animal does). They used 3 doses of PZM21 in the hotplate test (10, 20, and 40 mg/Kg), 2 doses in the tail-flick test (10 and 20), and 1 dose in the formalin test (20). Why? If you start with a dose-response in a test and want to convince me it works in the other tests, then do a dose-response for those too, so I have something to compare. These tests have been extensively used in pain research and the standard drug used is morphine. Therefore, the literature is clear on how different doses of morphine work in these tests. I need your dose-responses for your new drug to be able to see how it measures up, since you claim it is “more efficacious than morphine”. If you don’t want to convince me there is a dose-response effect, that’s fine too, I’ll frown a little, but it’s your choice. However, then choose a dose and stick with it! Otherwise I cannot compare the behaviors across tests, rendering one or the other test meaningless. If you’re wondering, they used only one dose of morphine in all the tests, except the hotplate, where they used two.

Another thing also related to doses. The authors found something really odd: PZM21 works (meaning produces analgesia) in the hotplate, but not the tail-flick tests. This is truly amazing because no opiate I know of can make such a clear-cut distinction between those two tests. Buuuuut, and here is a big ‘BUT” they did not test their highest dose (40mg/kg) in the tail-flick test! Why? I’ll tell you how, because I am oh sooo familiar with this argument. It goes like this:

Reviewer: Why didn’t you use the same doses in all your 3 pain tests?

Author: The middle and highest doses have similar effects in the hotplate test, ok? So it doesn’t matter which one of these doses I’ll use in the tail-flick test.

Reviewer: Yeah, right, but, you have no proof that the effects of the two doses are indistinguishable because you don’t report any stats on them! Besides, even so, that argument applies only when a) you have ceiling effects (not the case here, your morphine hit it, at any rate) and b) the drug has the expected effects on both tests and thus you have some logical rationale behind it. Which is not the case here, again: your point is that the drug DOESN’T produce analgesia in the tail-flick test and yet you don’t wanna try its HIGHEST dose… REJECT AND RESUBMIT! Awesome drug discovery, by the way!

So how come the paper passed the reviewers?! Perhaps the fact that two of the reviewers are long term publishing co-authors from the same University had something to do with it, you know, same views predisposes them to the same biases and so on… But can you do that? I mean, have reviewers for Nature from the same department for the same paper?

Alrighty then… let’s move on to the stats. Or rather not. Because there aren’t any for the hotplate or tail-flick! Now, I know all about the “freedom from the tyranny of p” movement (that is: report only the means, standard errors of mean, and confidence intervals and let the reader judge the data) and about the fact that the average scientist today needs to know 100-fold more stats that his predecessors 20 years ago (although some biologists and chemists seem to be excused from this, things either turn color or not, either are there or not etc.) or about the fact that you cannot get away with only one experiment published these days, but you need a lot of them so you have to do a lot of corrections to your stats so you don’t fall into the Type 1 error. I know all about that, but just like the case with the doses, choose one way or another and stick to it. Because there are ANOVAs ran for the formalin test, the respiration, constipation, locomotion, and conditioned place preference tests, but none for the hotplate or tailflick! I am also aware that to be published in Science or Nature you have to strip your work and wordings to the bare minimum because the insane wordcount limits, but you have free rein in the Supplementals. And I combed through those and there are no stats there either. Nor are there any power analyses… So, what’s going on here? Remember, the authors didn’t test the highest dose on the tail-flick test because – presumably – the highest and intermediary doses have indistinguishable effects, but where is the stats to prove it?

And now the thing that really really bothered me: the claim that PZM21 takes away the affective dimension of pain but not the sensory. Pain is a complex experience that, depending on your favourite pain researcher, has at least 2 dimensions: the sensory (also called ‘reflexive’ because it is the immediate response to the noxious stimulation that makes you retract by reflex the limb from whatever produces the tissue damage) and the affective (also called ‘motivational’ because it makes the pain unpleasant and motivates you to get away from whatever caused it and seek alleviation and recovery). The first aspect of pain, the sensory, is relatively easy to measure, since you look at the limb withdrawal (or tail, in the case of animals with prolonged spinal column). By contrast, the affective aspect is very hard to measure. In humans, you can ask them how unpleasant it is (and even those reports are unreliable), but how do you do it with animals? Well, you go back to humans and see what they do. Humans scream “Ouch!” or swear when they get hurt (so you can measure vocalizations in animals) or humans avoid places in which they got hurt because they remember the unpleasant pain (so you do a test called Conditioned Place Avoidance for animals, although if you got a drug that shows positive results in this test, like morphine, you don’t know if you blocked the memory of unpleasantness or the feeling of unpleasantness itself, but that’s a different can of worms). The authors did not use any of these tests, yet they claim that PZM21 takes away the unpleasantness of pain, i.e. is an affective analgesic!

What they did was this: they looked at the behaviors the animal did on the hotplate and divided them in two categories: reflexive (the lifting of the paw) and affective (the licking of the paw and the jumping). Now, there are several issues with this dichotomy, I’m not even going to go there; I’ll just say that there are prominent pain researchers that will scream from the top of their lungs that the so-called affective behaviors from the hotplate test cannot be indexes of pain affect, because the pain affect requires forebrain structures and yet these behaviors persist in the decerebrated rodent, including the jumping. Anyway, leaving the theoretical debate about what those behaviors they measured really mean aside, there still is the problem of the jumpers: namely, the authors excluded from the analysis the mice who tried to jump out of the hotplate test in the evaluation of the potency of PZM21, but then they left them in when comparing the two types of analgesia because it’s a sign of escaping, an emotionally-valenced behavior! Isn’t this the same test?! Seriously? Why are you using two different groups of mice and leaving the impression that is only one? And oh, yeah, they used only the middle dose for the affective evaluation, when they used all three doses for potency…. And I’m not even gonna ask why they used the highest dose in the formalin test… but only for the normal mice, the knockouts in the same test got the middle dose! So we’re back comparing pears with apples again!

Next (and last, I promise, this rant is way too long already), the non-addictive claim. The authors used the Conditioned Place Paradigm, an old and reliable method to test drug likeability. The idea is that you have a box with 2 chambers, X and Y. Give the animal saline in chamber X and let it stay there for some time. Next day, you give the animal the drug and confine it in chamber Y. Do this a few times and on the test day you let the animal explore both chambers. If it stays more in chamber Y then it liked the drug, much like humans behave by seeking a place in which they felt good and avoiding places in which they felt bad. All well and good, only that is standard practice in this test to counter-balance the days and the chambers! I don’t know about the chambers, because they don’t say, but the days were not counterbalanced. I know, it’s a petty little thing for me to bring that up, but remember the saying about extraordinary claims… so I expect flawless methods. I would have also liked to see a way more convincing test for addictive liability like self-administration, but that will be done later, if the drug holds, I hope. Thankfully, unlike the affective analgesia claims, the authors have been more restrained in their verbiage about addiction, much to their credit (and I have a nasty suspicion as to why).

I do sincerely think the drug shows decent promise as a painkiller. Kudos for discovering it! But, seriously, fellows, the behavioral portion of the paper could use some improvements.

Ok, rant over.

EDIT (Aug 25, 2016): I forgot to mention something, and that is the competing financial interests declared for this paper: some of its authors already filed a provisional patent for PZM21 or are already founders or consultants for Epiodyne (a company that that wants to develop novel analgesics). Normally, that wouldn’t worry me unduly, people are allowed to make a buck from their discoveries (although is billions in this case and we can get into that capitalism-old debate whether is moral to make billions on the suffering of other people, but that’s a different story). Anyway, combine the financial interests with the poor behavioral tests and you get a very shoddy thing indeed.

Reference: Manglik A, Lin H, Aryal DK, McCorvy JD, Dengler D, Corder G, Levit A, Kling RC, Bernat V, Hübner H, Huang XP, Sassano MF, Giguère PM, Löber S, Da Duan, Scherrer G, Kobilka BK, Gmeiner P, Roth BL, & Shoichet BK (Epub 17 Aug 2016). Structure-based discovery of opioid analgesics with reduced side effects. Nature, 1-6. PMID: 27533032, DOI: 10.1038/nature19112. ARTICLE 

By Neuronicus, 21 August 2016

Intracranial recordings in human orbitofrontal cortex

How is reward processed in the brain has been of great interest to neuroscience because of the relevance of pleasure (or lack of it) to a plethora of disorders, from addiction to depression. Among the cortical areas (that is the surface of the brain), the most involved structure in reward processing is the orbitofrontal cortex (OFC). Most of the knowledge about the human OFC comes from patients with lesions or from imaging studies. Now, for the first time, we have insights about how and when the OFC processes reward from a group of scientists that studied it up close and personal, by recording directly from those neurons in the living, awake, behaving human.

Li et al. (2016) gained access to six patients who had implanted electrodes to monitor their brain activity before they went into surgery for epilepsy. All patients’ epilepsy foci were elsewhere in the brain, so the authors figured the overall function of OFC is relatively intact.

While recording directly form the OFC the patients performed a probabilistic monetary reward task: on a screen, 5 visually different slot machine appeared and each machine had a different probability of winning 20 Euros (0% chances, 25%, 50%, 75% and 100%), fact that has not been told to the patients. The patients were asked to press a button if a particular slot machine is more likely to give money. Then they would use the slot machine and the outcome (win 20 or 0 Euros) would appear on the screen. The patients figured out quickly which slot machine is which, meaning they ‘guessed’ correctly the probability of being rewarded or not after only 1 to 4 trails (generally, learning is defined in behavioral studies as > 80% correct responses). The researchers also timed the patients during every part of the task.

Not surprisingly, the subjects spent more time deciding whether or not the 50% chance of winning slot machine was a winner or not than in all other 4 possibilities. In other words, the more riskier the choice, the slower the time reaction to make that choice.

The design of the task allowed the researchers to observe three 3 phases which were linked with 3 different signals in the OFC:

1) the expected value phase where the subjects saw the slot machine and made their judgement. The corresponding signal showed an increase in the neurons’ firing about 400 ms after the slot machine appeared on the screen in moth medial and lateral OFC.

2) the risk or uncertainty phase, when subjects where waiting for the slot machine to stop its spinners and show whether they won or not (1000-1500 ms). They called the risk phase because both medial and lateral OFC had the higher responses when there was presented the riskiest probability, i.e. 50% chance. Unexpectedly, the OFC did not distinguish between the winning and the non-wining outcomes at this phase.

3) the experienced value or outcome phase when the subjects found out whether they won or not. Only the lateral OFC responded during this phase, that is immediately upon finding if the action was rewarded or not.

For the professional interested in precise anatomy, the article provides a nicely detailed diagram with the locations of the electrodes in Fig. 6.

The paper is also covered for the neuroscientists’ interest (that is, is full of scientific jargon) by Kringelbach in the same Journal, a prominent neuroscientist mostly known for his work in affective neuroscience and OFC. One of the reasons I also covered this paper is that both its full text and Kringelbach’s commentary are behind a paywall, so I am giving you a preview of the paper in case you don’t have access to it.

Reference: Li Y, Vanni-Mercier G, Isnard J, Mauguière F & Dreher J-C (1 Apr 2016, Epub 25 Jan 2016). The neural dynamics of reward value and risk coding in the human orbitofrontal cortex. Brain, 139(4):1295-1309. DOI: http://dx.doi.org/10.1093/brain/awv409. Article

By Neuronicus, 25 March 2016

The Firsts: Anandamide (1992)

Cannabis, the plant whose psychoactive tetrahydrocannabinol (THC) binds to the same receptors in the brain as anandamide.

A rare tragedy took place in France a few days ago when a Phase I clinical trial for a new drug destined to improve mood and alleviate pain has resulted in one person dead and five other hospitalized. Phase I means that the drug successfully passed all animal tests and was being tried for the first time in humans to test its safety (efficacy and potency are tested in phase II and III, respectively).

The trial has been suspended and an investigation is on the way. So far, it appears that both the manufacturer (Bial) and the testing company (Biotrial) have followed all the guidelines and regulations. The running hypothesis is that the drug (BIA 10-2474) is acting on an unexpected target. What does that mean?

BIA 10-2474 is a FAAH inhibitor (fatty acid amide hydrolase). This enzyme breaks down anandamide, which is an endocannabinoid. In other words, is a neurotransmitter in the brain that binds to the same receptors as THC, the main active component of marijuana. So, if you give someone BIA 10-2474, the result would be an increase in the availability of anandamide, presumably with anxiolytic and analgesic effects (yes, similar to smoking weed).

There are other FAAH inhibitors out there that had been previously tried in humans and they were never marketed not because they were unsafe, but because they were ineffective in producing the desired results, i.e. less pain and/or anxiety.

So we don’t know yet why BIA 10-2474 killed people, but the bet is that in addition to FAAH, it also binds to some other protein. Why they didn’t discover this in animal trials, is a mystery; perhaps the unknown protein is unique to humans? By the looks of the drug’s structure, I think is computer generated, meaning is composed of a bunch of functional groups that someone put together in the hopes that it would fit neatly on the target binding site; but so many functional groups thrown in together might bind unexpectedly to other places than the intended. More on the story in Nature.

Anyway, that was the very long intro to today’s featured paper: the discovery of anandamide. Which happened very recently, in 1992, by the Mechoulam group at the Hebrew University of Jerusalem, Israel. Anandamide is the first endocannabinoid to be isolated. Mechoulam’s postodcs, William Devane and Lumir Hanus, used mass spectroscopy and NMR (nuclear magnetic resonance, MRI is an application of the same principles) to identify and isolate the molecule in a pig brain. And then they named it, fittingly, the “amide of bliss”…

Of note, members of the same Mechoulam group identified two more of the six known endocannabinoids. The three pages paper is highly technical, but I am assured (by a chemist) that is an easy-peasy read for any organic chemist.

Reference: Devane WA, Hanus L, Breuer A, Pertwee RG, Stevenson LA, Griffin G, Gibson D, Mandelbaum A, Etinger A, & Mechoulam R (18 Dec 1992). Isolation and structure of a brain constituent that binds to the cannabinoid receptor. Science, 258(5090):1946-9. PMID: 1470919, DOI: 10.1126/science.1470919.  Article | Research Gate Full Text

By Neuronicus, 18 January 2016

Yeast can make morphine

Opiates like morphine and heroin can be made at home by anybody with a home beer-brewing kit and the right strain of yeast. In 2015, two published papers and a Ph.D. dissertation described the relatively easy way to convince yeast to make morphine from sugar (the links are provided in the Reference paper). That is the bad news.

The good news is that scientists have been policing themselves (well, most of them, anyway) long before regulations are put in place to deal with technological advancements by, for example, limiting access to the laboratory, keeping things under lock and key, publishing incomplete data, and generally being very careful with what they’re doing.

Complementing this behavior, an article published by Oye et al. (2015) outlines other measures that can be put in place so that this new piece of knowledge doesn’t increase the accessibility to opiates, thereby increasing the number of addicts, which is estimated to more than 16 million people worldwide. For example, researchers can make the morphine-producing yeast dependent on unusual nutrients or engineer the existing strain to produce less-marketable varieties of opiates or prohibit the access to made-to-order DNA sequences for this type of yeast and so on.

You may very well ask “Why did the scientists made this kind of yeast anyway?”. Because some medicines are either very expensive or laborious to produce by the pharmaceutical companies, the researchers have sought a method to make these drugs more easily and cheaply by engineering bacteria, fungi, or plants to produce them for us. Insulin is a good example of an expensive and hard-to-get-by drug that we managed to engineer yeast strains to produce it for us. And opiates are still the best analgesics out there.

Reference: Oye KA, Lawson JC, & Bubela T (21 May 2015). Drugs: Regulate ‘home-brew’ opiates. Nature, 521(7552):281-3. doi: 10.1038/521281a. Article | FREE Fulltext PDF

By Neuronicus, 2 January 2016

The culprit in methamphetamine-induced psychosis is very likely BDNF

Psychoses. Credit: NIH (Publication Number 15-4209) & Neuronicus. License: PD.

Methamphetamine prolonged use may lead to psychotic episodes in the absence of the drug. These episodes are persistent and closely resemble schizophrenia. One of the (many) molecules involved in both schizophrenia and meth abuse is BDNF (brain derived neurotrophic factor), a protein mainly known for its role in neurogenesis and long-term memory.

Lower BDNF levels have been observed in schizophrenia, therefore Manning et al. (2015) wondered if it’s also involved in meth-induced psychosis. So they got normal mice and mice that were genetically engineered to express lower levels of BDNF. They gave them meth for 3 weeks, with escalating doses form one week to the next. Interestingly, no meth on weekends, which made me rapidly scroll to the beginning of the paper and confirm my suspicion that the experiments were not done in USA; if they were, the grad students would not have had the weekends off and mice would have received meth every day, including weekends. Look how social customs can influence research! Anyway, social commentary aside, after the meth injections, the researchers let the mice untroubled for 2 more weeks. And then they tested them on a psychosis test.

How do you measure psychosis in rodents? By inference, since the mouse will not grab your coat and tell you about the newly appeared hypnotizing wall pattern and the like. Basically, it was observed that psychotic people have a tendency to walk in a disorganized manner when given the opportunity to explore, a behavior that was also observed in rodents on amphetamines. This disorganized walk can be quantifies into an entropic index, which is thought to reflect occurrence of psychosis (I know, a lot of inferring. But you come up with a better model of psychosis in rodent!).

Manning et al. (2015) gave their mice amphetamine to mimic psychosis and then observed their behavior. And the results were that the genetically engineered mice to express less BDNF showed reduced psychosis (i.e. had a lower entropic index). In conclusion, the alteration of the BDNF pathway may be responsible for the development of psychosis in methamphetamine users.

Reference: Manning EE, Halberstadt AL, & van den Buuse M. (Epub 9 Oct 2015). BDNF-Deficient Mice Show Reduced Psychosis-Related Behaviors Following Chronic Methamphetamine. International Journal of Neuropsychopharmacology, 1–5. doi: 10.1093/ijnp/pyv116. Article | FREE FULLTEXT PDF

By Neuronicus, 9 November 2015

The good and the bad of abstinence

The nucleus accumbens, a key region involved in reward processing and addiction. Credit: Zou et al. (2015)

Consumption of addictive drugs changes your brain and these changes underlie the consequent dependence. It is very difficult to quit, and certainly it is not a matter of lack of will power that the majority of drug users have such a great difficulty in trying to quit. But what happens to the brains of the lucky few who managed to kick the addiction out the window? Are their brains reverting to their pre-addiction states? As the paper below shows, sadly, no. But there is hope.

Zhou et al. ( 2015) used resting state fMRI (which means scanning your brain without requiring you to perform any task) to investigate the brains of 30 healthy controls and 30 heroin-addicts who were abstinent from the drug for more than 3 years. Specifically, they looked to see if the connectivity of certain brain regions involved in addiction is different after such a long abstinence time.

The bad news is that the abstinents still had some abnormal connectivity (for specialists: “stronger functional connectivity between the nucleus accumbens and the right ventromedial prefrontal cortex and relatively weaker connectivity between the nucleus accumbens and the left putamen, left precuneus, and supplementary motor area” p. 1697).

The good news: the longer the abstinence time, the greater the strength of the connection between nucleus accumbens and putamen (first structure involved in reward processing, the second in habit-learning), suggesting a partial neural recovery.

The study has some limitations: technical (did not control for heartbeat and respiration), methodological (most of the heroin abstinents were smokers, another addiction) and theoretical (one brain area does not support only one function, so its connectivity shouldn’t be over interpreted). With the caveat that the connectivity differences observed do not in any way point to a cause and effect relationship – that is we don’t know if these differences existed before the first heroin intake and caused it or they appeared after as a result of drug consumption, I think the paper is still is worth reading.

Reference: Zou F, Wu X, Zhai T, Lei Y, Shao Y, Jin X, Tan S, Wu B, Wang L, Yang Z (November 2015, Epub 17 Aug 2015). Abnormal resting-state functional connectivity of the nucleus accumbens in multi-year abstinent heroin addicts. Journal of Neuroscience Research, 93(11):1693-702. doi: 10.1002/jnr.23608. Article | FREE PDF

By Neuronicus, 9 October 2015