Sunday, August 20, 2017

Mind Your Back

This is one of my occasional public service announcements.  I have at least one previous post on spinal health on this blog.  Some might wonder why a psychiatrist is interested in the spine.  I had an early interest in neurosurgery and over the years have talked with people who have sustained various spinal injuries that they have recovered from or been disabled by.  These injuries are very common and can occur along any number of trajectories. They can be associated with chronic pain and result in numerous surgical or pain intervention procedures that have varying degrees of success.  Once a chronic pain state has been established it is unlikely to be resolved completely at any time in the future.

Mapped onto that landscape of acute injuries are injuries to the aging spine.  For various reasons aging has an impact on every persons spine.  Degenerate disk disease is a normative finding on imaging studies as a person ages.  Acute injuries can make a spine image appear to be older because it looks like age-related changes.  For example, I have had athletes who injured their back tell me that their physician told them that after a certain injury their x-ray "looked like a the x-ray of a 70 year old man."  Older spines may not be as dense and I have seen many people diagnosed with acute compression fractures that were either spontaneous or they occurred after a fall.  I have talked with people who had a compression fracture as a first sign of cancer from metastatic disease but I want to emphasize that this is a rare cause of acute back pain.  The commonest cause of back pain and back injury are acute accidents and per my example - acute injury to the aging spine.

Let me give a clear example.  Consider the theoretical case of Bob X.  For 35 years Bob has worked on a railroad section crew.  Even though there is a lot of mechanization on the railroad these days, Bob's strength was legendary in terms of what he could lift off the ground.  He retired at age 66 and became relatively sedentary.  He gained a substantial amount of weight and spend most of his day watching television.  He happened to be out in his yard one afternoon and his neighbor asked him  to help him lift a mower onto trailer.  Bob looked at the mower and figured it was much less than what he was used to lifting on the railroad.  He decided to lift it up by himself and set it on the trailer.  He noticed almost immediate lower back pain and then some pain radiating down his left leg.  After persistent pain for a few days he went in to see high physician and an MRI scan of the lumbar spine was done showing a minor facet fracture and an L4-5 disk herniation.  In this case we have a man who has a physically demanding job and probably became deconditioned after retirement.  He became injured when handling a load that he estimated he could easily handle based on past experience and did not factor in the conditioning aspects.

That brings me to today's example.  I needed to grease the front axles of my riding lawn mower.  It is a large Toro model and the front end is weighted for stability.  The mower weighs about 550 pounds.  I typically pick up the front end and place it on an inverted 10 gallon plastic pail.  That is essentially a dead lift of at least a foot with a weight of about 100+ pounds.  Even though I have done spinal exercises every day for the past 15 years this is a setup for an injury.  Today I started to think about mechanical advantage and remembered a brief job I had during my youth.  I helped a guy change very large earthmover tires. In the process we used a small hydraulic jack to break the beads on these tires so that we could get them off the rim.  I decided to purchase a jack to do the job.  At the store, there were a great many jacks with different capacities.  I got one with a jack stand built right into it and it also had a wide stable base.

After placing the jack under the mower I moved it into the exact position I needed by pumping the jack about three times with three fingers.  No back strain at all.  

Today's take home message is that you need to protect your spine, especially if you are aging.  Aging is associated with a number of factors that decreases the ability of the spine to sustain a load and lift effectively.  Workers and athletes who are used to sustaining high loads on their spines need to reconsider that and slow down or stop as they age.  Practically everyone has degenerative disk disease and that leads to a characteristic radiographic appearance and generally some degree of chronic back pain.  I think that a reasonable approach with aging is to exercise your back in a manner consistent with maintaining adequate conditioning of the perispinal muscles and adequate density of the vertebrae.   Those programs need to be individualized especially if there is an prior spinal problem or illness affecting the spine.  Your physician should be able to recommend a specialty program or physical therapy who can provide the exercise regimen to maintain conditioning and flexibility.  That approach can also result in significant pain relief.  Many of these programs also have individualized programs on techniques to avoid lifting injuries.

Shortcuts at home to alleviate load on the spine like the hydraulic jack in the example should be considered. There are a number of useful products like small hand trucks designed to pick up plant pots that can also be useful.  The goal is avoiding a spinal or musculoskeletal injury that leads to further deconditioning and risk of future injury.

There is not enough advice and information out there on how to prevent these injuries. Once they occur, trying to get the right help can be confusing and limited to medications rather than the needed physical therapy. More importantly - these injuries can result in a marked lifestyle change and decreased physical activity required to maintain general health.

George Dawson, MD, DFAPA      

Disclaimer:  This is a non-commercial blog.  The pictures here depict the equipment that I have purchased and am really using.  There is no promotional consideration.


Thursday, August 17, 2017

Making Sense of Alcohol Consumption in the USA

I don't know how many people are aware of it but a crisis of alcohol use was declared about a week ago (1) by Marc Schuckit, MD.  Dr. Schuckit is one of the top psychiatric experts in alcohol use disorders and I have been reading his work for the past 35 years.  His commentary was based on an article (2) in that same issue of JAMA Psychiatry  on the epidemiology of alcohol use in the United states in the 21st century.

Most of the researchers listed as authors of this paper are affiliated with the Epidemiology and Biometry Branch of the National Institute on Alcohol Abuse and Alcoholism (NIAAA).  They are analyzing data collected in the National  Epidemiological Survey on Alcohol and Related Conditions (NESARC and NESARC-III)) during two different time points: 2001-2002 (N=43,093) and 2012-2013 (N=36,309).  Typical response rates were noted for both the initial selections and the individual response rates for the face-to-face interviews.  Both surveys were designed to be nationally representative samples adjusted to account for sampling error and non-response.  I interpret that to mean that the percentages listed in the following table to represent population wide numbers based on these samples. Respondents were paid $90 for participation.  The specific sampling strategies were listed in the paper.

The structured interview was the Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV Version (AUDADIS-IV) in NESARC and AUDADIS-V in NESARC-III.  The definitions of high risk drinking are noted in the table.  DSM-IV diagnoses of alcohol abuse or dependence were given according to the suggested criteria match.  Various measures of reliability and validity of the structured interview are referenced as being fair to high.  All of the demographic variables noted in the test subjects are noted in the article as well as some discussion of how subgroups varied.  For example very  large increases were noted in practically all subgroups for 12-month DSM-IV AUD diagnoses with subjects in the 65 years and older increased by 106.7%  

NESARC (2001-2003)
NESARC III (2012-2013)
Percentage Increase
12-month alcohol use
12-month high-risk drinking
12-month DSM-IV AUD diagnosis
12-month DSM-IV AUD among 12-month alcohol users
12-month DSM-IV AUD among 12 month high-risk drinkers

The trend according to this study is only in the upward direction.  The authors speculate about socioeconomic etiologies (unemployment, discrimination, income disparities, stigma of alcoholism) and increased permissiveness in what is acceptable drinking for women.  Subgroup analysis shows these groups had the highest increases in alcohol use.  The authors also point out that there are primary and secondary effects in these groups that can significantly increase the known morbidity and mortality associated with drinking such as more significant alcohol related illnesses in women for the same dose of alcohol due to decreased metabolic clearance and increased likelihood of adverse drug effects due to polypharmacy in both women and the elderly.  They also point out that alcohol related problems seem to have gone under the radar with higher visibility of less commonly used intoxicants like cannabis and hallucinogens.  I would add that permissiveness of intoxicant use in general is a cultural phenomenon and it probably not too surprising that the widespread legalization and hype about cannabis would be associated with increased alcohol consumption.  There are certainly many people with the belief that alcohol alleviates chronic pain, insomnia, anxiety, and depression as well as cannabis.  The popular notion that alcohol is a healthy beverage that provides protection against heart attacks and stroke is undoubtedly another factor.  Few people realize that the maximum number of drinks per day for men and women (2 and 1 respectively) was based on the fact that above that level the risks for cardiovascular disease and cancer increase significantly.

The new study also has some implications for other large scale estimates of alcohol use and the associated morbidity and mortality.  As an example, the World Health Organization came out with a large study in 2014 that reported on data from 2010 and 2012.  Comparison with the NESARC data shows that 12-month alcohol use (WHO v. NESARC III) is fairly close at 68.9 v. 72.7%.  Comparison of 12-month high risk drinking uses different measures.  For WHO, high-risk drinking is defined as at least 60 grams of alcohol in a single day in any 30 day period.  For NESARC III, the definition is 4 or more standard drinks on any day for women and 5 or more standard drinks on any day for men.  In the US, a standard drink is considered 14 g of pure alcohol.  That results in 16.2% of American drinkers being classified as heavy episodic drinkers and 12.6% classified as 12-month high risk drinkers.  From a diagnostic standpoint, WHO estimates that the prevalence of 12-month alcohol use disorders is 7.4% and NESARC III gives and estimate of 12.7%.  It is likely that different methodologies explain the marked difference in prevalence estimate for alcohol use disorders.  The WHO estimate was based on ICD alcohol use disorders as well as disorders representing harmful use of alcohol.  The NESARC III estimate was lay interviewers using a standard interview format to provide as DSM-IV diagnosis.  That means that the WHO estimate for alcohol use disorders based on the NESARC III data would be 20-30% higher than the 12.7% estimate.  A further note on the heavy episodic or high-risk drinking.  In treatment centers it is very common for people seeking admission to be drinking in excess of those rates on a daily basis.

A closely related phenomenon to high risk drinking is binge-drinking.  The CDC uses the same volume definition for high risk drinking but states that it occurs in an unspecified short period of time to elevate blood alcohol content above 0.08 g/dL.  According to their reviews the average binge drinker consumes 8 drinks per episode.  The main risk is alcohol poisoning.  Six people a day die of alcohol poisoning in the US, most of them are white men between the ages of 35 and 64.  Binge drinking carries with it all of the related risks of acute intoxication.

In his commentary, Dr. Schuckit reviews his concerns about the potential implications of alcohol use increases in both women and the elderly.  He points out that elderly patients almost always have co-morbid medical illnesses that will be exacerbated by drinking.  He discussed an intervention that his group did with 500 college freshmen as 4 - 50 minute internet-based videos.  The course was designed to help them recognize their vulnerability to heavy drinking.  The intervention was effective at both 6 and 12 months.  He concludes by focusing in on the threats to research funding in this area - specifically with the proposed cuts to the National Institutes of Health budget.  He suggests that supporting politicians who recognize the importance of research, identifying health crisis, and addressing them.

I think there is a lot of room to be a lot more proactive in our society.  Apart from the cultural myths that I already mentioned, a dangerous one is: "I am not an alcoholic and therefore I don't have any problems with alcohol."  The above research and others point out that it is possible to be a high risk drinker and not have a 12-month diagnosis of an alcohol use disorder.  Psychiatrists see variations of this pattern over the course of their careers.  They may be called on to assess the teenager in the ICU after they had an episode of acute alcohol poisoning after voluntarily drinking too much.  They may be called on to assess people who were violent or victimized when they drank too much.  They may have to do specialized assessments on professionals who engaged in high risk drinking for some reason and ended up placing their credentials and licensure at risk.

It is time to realize that there is much more to alcohol use than being an alcoholic or technically having a diagnosis of an alcohol use disorder.  Even one episode of high risk drinking may end or permanently alter a persons life.  Education on alcohol use is needed to dispel these popular myths and help people negotiate what is commonly a difficult decision in their life.  

George Dawson, MD, DFAPA


1: Schuckit MA. Remarkable Increases in Alcohol Use Disorders. JAMA Psychiatry.2017 Aug 9. doi: 10.1001/jamapsychiatry.2017.1981. [Epub ahead of print] PubMed PMID: 28793142.

2:  Grant BF, Chou SP, Saha TD, Pickering RP, Kerridge BT, Ruan WJ, Huang B, Jung J, Zhang H, Fan A, Hasin DS. Prevalence of 12-Month Alcohol Use, High-Risk Drinking, and DSM-IV Alcohol Use Disorder in the United States, 2001-2002 to 2012-2013: Results From the National Epidemiologic Survey on Alcohol and Related Conditions. JAMA Psychiatry. 2017 Aug 9. doi: 10.1001/jamapsychiatry.2017.2161. [Epub ahead of print] PubMed PMID: 28793133.

3:  World Health Organization.  Global Status Report On Alcohol and Health, 2014 edition

4:  CDC Press Release November 20, 2014.  Most people who drink excessively are not alcohol dependent. 

5: Quinn AE, Brolin M, Stewart MT, Evans B, Horgan C. Reducing Risky Alcohol Use: What Health Care Systems Can Do. Issue Brief (Mass Health Policy Forum). 2016 Apr 27;(46):1-50. PubMed PMID: 27911073.

6: Stahre M, Roeber J, Kanny D, Brewer RD, Zhang X. Contribution of excessive alcohol consumption to deaths and years of potential life lost in the United States. Prev Chronic Dis. 2014 Jun 26;11:E109. doi: 10.5888/pcd11.130293. PubMed PMID: 24967831; PubMed Central PMCID: PMC4075492. 

7: Landen M, Roeber J, Naimi T, Nielsen L, Sewell M. Alcohol-attributable mortality among American Indians and Alaska Natives in the United States, 1999-2009. Am J Public Health. 2014 Jun;104 Suppl 3:S343-9. doi: 10.2105/AJPH.2013.301648. Epub 2014 Apr 22. PubMed PMID: 24754661; PubMed Central PMCID: PMC4035890. 

8: Gonzales K, Roeber J, Kanny D, Tran A, Saiki C, Johnson H, Yeoman K, Safranek T, Creppage K, Lepp A, Miller T, Tarkhashvili N, Lynch KE, Watson JR, Henderson D, Christenson M, Geiger SD; Centers for Disease Control and Prevention (CDC). Alcohol-attributable deaths and years of potential life lost--11 States, 2006-2010. MMWR Morb Mortal Wkly Rep. 2014 Mar 14;63(10):213-6. PubMed PMID: 24622285. 

9: Sacks JJ, Roeber J, Bouchery EE, Gonzales K, Chaloupka FJ, Brewer RD. State costs of excessive alcohol consumption, 2006. Am J Prev Med. 2013 Oct;45(4):474-85. doi: 10.1016/j.amepre.2013.06.004. PubMed PMID: 24050424. 

10: Nelson DE, Naimi TS, Brewer RD, Roeber J. US state alcohol sales compared to survey data, 1993-2006. Addiction. 2010 Sep;105(9):1589-96. doi: 10.1111/j.1360-0443.2010.03007.x. Epub 2010 Jul 9. PubMed PMID: 20626370. 

11: Woerle S, Roeber J, Landen MG. Prevalence of alcohol dependence among excessive drinkers in New Mexico. Alcohol Clin Exp Res. 2007 Feb;31(2):293-8. PubMed PMID: 17250622.

12:  WHO Global Information System On Alcohol and Health:


Click to enlarge and clarify the graphic at the top of this post.

Tuesday, August 15, 2017

The Google Memo

I decided to comment on the now famous (or at least viral) Google memo as an anchor point for social media on the blog. After making its way through the social media and into the mainstream media, I don’t think that it is necessary to say much about it other than it was written by a Google software engineer James Damore who was subsequently fired for the effort. I qualify my statements by saying that I do not know this engineer or anything about the corporate culture at Google other than what was written in his long memo. I do have 33 years of experience steeped in every aspect of medical culture. That includes working for corporations that have implemented many of the initiatives discussed in the memo. My overall take is that corporate politics can be dangerous to your health, but not because of major party politics.

The Memo presents a confusing introduction. The author states that he does not believe in stereotypes but proceeds to argue from that viewpoint. He discusses the predominate liberal atmosphere at Google and what that means in terms of liberal stereotypes. He refers to himself as a classic liberal, but at the same time complains about and refers to being discriminated against as a conservative. Despite the ample qualifiers, there is an implicit suggestion that due to inherently different characteristics – it may not be possible for a substantially male population in coding to be altered in material ways and that the programs in place to do an end run around this issue are not cost effective for the company. It is a strong argument to maintain the status quo.

As a kid growing up in the 1960s, female physicians were unheard of.  In the subsequent decades all of that changed drastically.  When I started in medical school, about half of the class was women, but women were substantially underrepresented in largely surgical specialties. There were clear problems with the transition. I can recall rounding where there were open arguments and verbal attacks based on gender by people at the same level of training. As a medical student I was privy to the private conversations of both sides and in those days it was all about gender. But thankfully only in a few areas. I had the opportunity to train with attendings and residents who were women and who were first rate physicians and academicians. Because of the gender based undercurrent, I also felt the backlash. Being an introvert is like being a projective test for some people. I got feedback from a male resident that the female attending on one of my rotations thought that I did not like women and that was just inaccurate. I attributed it and some other attitudes from a few women I encountered to biases they may have encountered along the way. I won’t say that did not have an effect on me – but it did not adversely impact my progress on the path to being a physician.

By the time I became a resident, half of my class was women. I viewed them as colleagues. They were all clearly as bright as I was. The farther I got into psychiatry, the more remote the gender biases seemed to be. I was eventually hired into a department that was largely women. It had a collegial atmosphere. In all areas of patient care, I never doubted that the work they were doing was at the level of my work. I would not hesitate to refer people to them or consult with them in tough situations and do so even today. In psychiatry, women are well represented in professional societies, scientific meetings and publications. I have never heard a male psychiatrist utter a word about women being less skilled or professional in psychiatry. It would be taken as an absurd statement.

The brief recap of my experience of gender representation in psychiatry has its limitations. It is my experience over 30 years in the field. It is in a field that is in short supply and may be dying – rationed out of existence by the government and managed care companies. For many years, interest in psychiatry was low. The problem has never been studied to my knowledge but my speculation is that enrollment by women in both medical school and psychiatric residency programs probably averted a much greater crisis. I can’t speak to the initiatives that got the enrollment in medical schools to go higher, but whatever it was – consider it highly successful.

That does not mean it was an easy transition.  Although I never personally witnessed it, I have no doubt that women and minority students were treated badly at some point in their medical training.  I base this on my own experience of being treated badly.  There were clearly attending physicians who were not interested in the education of medical students and were openly hostile.  I was ridiculed in front of one of my teams by the attending physician when he learned that I was going into psychiatry.  "You don't want to work Dawson?  Psychiatrists don't work as hard as other physicians and if I needed counseling I wouldn't see a psychiatrist".  All of that was presented with a congruent sneer. I held back at that time at the time, and did not tell him it would probably take years of psychoanalysis rather than a few counseling sessions.  

I observed in those days that the abusive cultures seemed to be localized in private institutions.  I naturally gravitated to the public ones - the County Hospital and Veteran's Administration Medical Center.  In these places there was a certain  esprit de corps.  There was a lot of work.  The staff were interested in caring for very ill patients with limited resources being available.  There was generally a wide sampling of specialists and everyone seemed accepting of medical students and residents as long as they pulled their own weight.  I met some of the best attendings and teachers in these settings.

The corporate takeover of medicine facilitated by the federal government created a hostile and authoritarian atmosphere.  Instead of being responsible for your own knowledge and how you took care of patients you were now burdened with totally subjective administrative standards.  The first was the new billing and coding standards.  Miss a bullet point in the document and get accused of fraudulent billing.  Send that bill in the mail and get accused of racketeering and go to Leavenworth.  People may find that humorous now, but I can assure you that in about 1996, every physician in my organization had to attend a seminar and that is part of what we were told.  As the feds transferred their power to intimidate to managed care organizations a whole new set of rules to intimidate and control physicians was put into place.  The "disruptive physician" concept was suddenly co-opted from physicians with clear personality disorders to just about anything that a physician did that somebody did not like.  In some institutions the accusations did not have to be witnessed or even factual.  Some institutions just adapted a "three strikes and you are out" policy.  In other words, if they collect 3 unsubstantiated, unwitnessed and (according to their rules) uncontested complaints - the physician could be fired.  That was a discretionary rule, I have seen physicians fired for just one complaint.  By the time the corporations had taken over, these rules were equally applied regardless of gender or race.  I personally know male and female physicians who were fired or who just collected a strike or two.  Equal oppression by the corporation may be the ultimate sign of egalitarianism.            

I am going to digress for a minute on the science of the memo, because the author seems to invoke this theme several times, even to the point of offering to send more references.  This memo is not a scientific endeavor, it is a political one.  In that process, even the extremes of liberalism and conservatism will be able to come up with scientific papers to support their extreme positions.  Even though there is a general consensus on climate change this is an example.  Not everyone agreed with Einstein's revolutionary theory and at the time his work was highly politicized based in part on his ethnicity.  The process of science is not designed to be taken in a political context.  The other aspect of the science of the memo has to do with measurement.  Measurement in the social sciences is a very approximate matter.  It requires individualized expert interpretation in a highly specific context.  I have lost count of the number of professional people that I know who were told by guidance counselors that they would never make it in college.  Measures of personality and intelligence have significant limitations.  They are not quantitative by any means.  One interesting conceptualization of the problem is Massimo Pigliucci's graph of empirical knowledge versus theoretical understanding.  On this graph, theoretical understanding of social sciences is definitely lagging.  Even though there is a well publicized reproducibility problem in social sciences, I consider that to be expected rather than a problem that needs to be solved.  In situations where the human conscious states is the subject of analysis, it is necessary to keep in mind that we have no adequate analysis of a very large number of possible states and how they overlap between men and women.  There is nothing to suggest that interracial differences at this level are significant.  Everyone has a somewhat heritable biological substrate, but in the case of the brain we have an infinitely plastic and complex organ that we are just beginning to understand.  It is easy to mistake the positive and negative effects of socialization for a biologically inherent trait.      

My experience in the workplace, at various levels of medical and scientific endeavor has made it very clear - irrespective of socialization or biology - men and women can function interchangeably doing the same tasks. The idea that one sex is intellectually superior or has personality characteristics that can lead to inherently better performance in the workplace is just plain wrong. I certainly can't speak to the workplace or political environment at Google, but I can say that the political environment in most real workplaces these days is dominated by corporate rather than major party politics. That corporate approach opens a number of avenues for the corporation to demand specific compliant behaviors from employees with possible penalties right up to termination.   Squabbling about major party politics at the water cooler pales in comparison.

It turns out that every corporation is an "ideological echo chamber" but that ideology originates at the level of the executives and the board of directors.  It is overwhelmingly focused on the best interests of the corporation and not the employees.  Attempting to impact that with a generally released memo like this one is a naive mistake and it misses the mark for many reasons.  The commentary from outside of the organization is predictable given the source, and of course entirely irrelevant to the intended purpose of the memo. And lastly, Damore's ideas about why men make superior software engineers is possibly accurate but I doubt it.  The women I have gone to school with and worked with were very bit as good as the men in those settings.  Engineers may be tempted to say that medicine is not software engineering and that is true, but for some of us there are a significant number of quantitative sciences and mathematics courses long the way.

And it was always obvious to me that we need as many women in those classes and professional schools as possible.

George Dawson, MD, DFAPA

Supplementary 1:  I could not work this into the main body of the post but the social media spin on this memo has been intense.  Spins saying that it has the science right and spin saying that it has the science wrong.  The author having to defend himself on the issue of whether or not he supports the alt-right.  He said that women aren't good at tech and he has said that there are women who are good coders at Google.  The reality is that women can do what men do and at no point in our history has there been more proof of that.  That is a much different issue from corporate governance or politics.


1:  James Damore.  Google's Ideological Echo Chamber.  July 2017.

      It is available from several sites on the Internet.    

Friday, August 11, 2017

Computational Psychiatry

From Reference 1

In the 1970s I was reading a lot of science fiction in the Peace Corps. One of those books had a story about a scientist who had figured out all of the mathematical equations for human behavior. Although it was clearly fiction that thought stayed in my mind over the decades. When I was doing quantitative EEG work in the 1990s, I thought about it but it was apparent that the statistical models being used for that work were not remotely related to the observed behaviors that these devices were trying to classify – and there was always some clinical variable (eg. Did the subject have an alcohol problem or traumatic brain injury?) – that seemed to make the equations even more approximate. An electrical engineer that I was working with was able to apply a complexity measure to the output from a single electrode from an EEG and demonstrate the expected decrease in complexity with neural networks in Alzheimer’s Disease. That metric was interesting but not at the level where second to second behaviors could be examined. It was more of a brain state function.

That brings me to the recent article in JAMA Psychiatry entitled “Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression”. Reward prediction errors are the difference between experienced and predicted rewards. The authors note that if the reward exceeds the expectation then “the value associated with the chosen option is increased, making it more likely to be chosen again.” As I read this, I thought about the case of chronic addiction where that is no longer the case and the maladaptive choice is made over and over again. I also thought about the subtler case of low frequency unexpected rewards. A common experience would be the “Aha” experience that universally occurs when problems are suddenly solved and exam questions answered after a unique insight is realized. As I tell my students, there is good evidence that if we put the person’s head into an fMRI scanner right at that instant that their nucleus accumbens would be lighting up. There does appear to be a lot more going on that the difference between experienced rewards and expected rewards.

This study looked at the issue of whether depression attenuates ventral striatal reward prediction errors (RPEs) in a task that did not involve a significant learning component. It was already known that there were attenuated RPE signals in the ventral striatum of people with depression during reinforced learning. It was also known that in healthy controls RPE variation explains momentary mood fluctuations.

The experiment itself consisted of two phases. In the first, a laboratory study looked at 34 subjects and 10 controls with diagnoses of depression after fairly rigorous exclusion criteria were applied at the clinical and fMRI level. The majority of the experimental group and half of the controls were women. It appears that all of the depressed patients were taking antidepressant medication. The subjects completed a risk decision task that did not require any learning and was designed so that performance by the depressed patients and controls was the same. The task consisted of 160 trials where the subject was asked to choose monetary gambles with two outcomes. The outcomes were given in real money. They were then asked to rate their happiness on an analog scale in response to the question: “How happy are you at this moment?” During the tasks, fMRI blood oxygen level dependent (BOLD) activity was measured. The MRI plane was optimized to view the ventral striatum. In the graphics both transverse and coronal MRI planes are depicted with the pixelated areas of interest in the ventral striatum.

In the second phase of the experiment, the risky decision tasks was translated to a smartphone app, The Great Brain Experiment ( A total of 1833 participants completed 30 choice trials and 12 ratings. They were not compensated.

In terms of results, the depressed group and controls had similar earning on the probabilistic reward task ($7.75). Median reaction times and choice accuracy were also similar. Ventral striatal BOLD activity on the fMRI correlated with reward magnitude and did not differ between depressed subjects and controls. A lack of difference between these groups was also examined across reward magnitude, anhedonia, and antidepressant use and no differences were found.

In the smartphone sample, the momentary mood computational model (see above equation) correlated with happiness ratings. The model worked better is severe forms of depression. Anhedonia did not correlate with the impact of RPEs but other depression questions on the Beck Depression Inventory-II did.

The authors conclude that their results demonstrate that there is no impairment in “basic reward-related neural and emotional processes in depression in a non-learning context”. The dopaminergic RPE signal was the same in the depressed group and controls. They make the further arguments that dopamine signaling in the ventral striatum is complex and other factors are involved. They discuss a model from the literature that discusses the cognitive deficit in depression as one of goal directed reasoning based on a model of the causal structure of the world. They imply that dopamine at least in the studied reward systems may not have a central role in depression.

The authors discuss a major limitation of their study in that only 9/32 subjects with depression were unmedicated. They discuss how they examined some parameters that suggests this effect was not significant. An ideal study would look at both the effects of severe depression (PHQ-9 score here was 15.8 [SD 4.7]) , no medications, and patients who have never been medicated. It might be useful to consider more rigorous elimination of other disorders affecting the ventral striatum. All things considered it is a useful look at an experimental paradigm that demonstrates the utility of brain imaging in applications that can be used on a wider population basis and whether or not they may be valid.

The accompanying editorial by Rabinovich and Varona was interesting.  They make the argument that the global conscious state is too complex to be described by mathematical equations but various components are not.  They go on to describe their own model of global brain networks and how they interact with one another.  They suggest that brain networks are very similar and vary only in content and the complexity of their content.  As an example in the creativity process, the channels stay the same whether the process involves music, poetry, or mathematics.  They suggest the same processes are active in psychiatric disorders and illustrate cognitive and ritual heteroclinic channels in obsessive-compulsive disorder.  They suggest that these dynamic systems in the brain can be determined and can be quantitatively characterized by various means like the value of the Kolmogorov-Sinai entropy. Mathematically modeling the brain as dynamic systems has been around for some time.  I will have to review this work but it seems that it may not incorporate enough of the physical characteristics of the systems into the mathematics.

Finally, I would be remiss if I did not mention the excellent review by Wang and Krystal (3) and well as many of their other articles on computational psychiatry.  Their definition of computation psychiatry is a discipline that seeks to incorporate the computational mechanism from a real neural network into its role in psychiatric disorders and the way a person actually functions.  This is an exciting approach because it represents the ultimate integration of all of the anatomy, physiology and pharmacology that we study into a real working system. It is exactly where the field needs to be heading.  I think there is a natural overlap with the study of human consciousness.

These are exciting times and computational psychiatry is adding to that mix. 

George Dawson, MD, DFAPA


1:  Rutledge RB, Moutoussis M, Smittenaar P, Zeidman P, Taylor T, Hrynkiewicz L, Lam J, Skandali N, Siegel JZ, Ousdal OT, Prabhu G, Dayan P, Fonagy P, Dolan RJ. Association of Neural and Emotional Impacts of Reward Prediction Errors With Major Depression. JAMA Psychiatry. 2017 Aug 1;74(8):790-797. doi: 10.1001/jamapsychiatry.2017.1713. PubMed PMID: 28678984.

2:  Rabinovich MI, Varona P. Consciousness as Sequential Dynamics, Robustness, andMental Disorders. JAMA Psychiatry. 2017 Aug 1;74(8):771-772. doi: 10.1001/jamapsychiatry.2017.0273. PubMed PMID: 28564683

3:  Wang XJ, Krystal JH. Computational psychiatry. Neuron. 2014 Nov5;84(3):638-54. doi: 10.1016/j.neuron.2014.10.018. Epub 2014 Nov 5. Review. PubMed PMID: 25442941

4: Keller K, Mangold T, Stolz I, Werne J. Permutation entropy: new ideas and challenges. Entropy 2017, 19(3), 134; doi:10.3390/e19030134

Contains a section on Kolmogorov-Sinai Entropy and a discussion of EEG applications.

5: Donoso M, Collins AG, Koechlin E. Human cognition. Foundations of human reasoning in the prefrontal cortex. Science. 2014 Jun 27;344(6191):1481-6. doi: 10.1126/science.1252254. Epub 2014 May 29. PubMed PMID: 24876345
I included this reference as a great example of the network in the frontal cortex that are active in reasoning and activation of the ventral striatum during good decisions (the "aha effect").

6: Piray P, Toni I, Cools R. Human Choice Strategy Varies with Anatomical Projections from Ventromedial Prefrontal Cortex to Medial Striatum. J Neurosci. 2016 Mar 9;36(10):2857-67. doi: 10.1523/JNEUROSCI.2033-15.2016. PubMed PMID:26961942.

7: Jarbo K, Verstynen TD. Converging structural and functional connectivity oforbitofrontal, dorsolateral prefrontal, and posterior parietal cortex in the human striatum. J Neurosci. 2015 Mar 4;35(9):3865-78. doi: 10.1523/JNEUROSCI.2636-14.2015. PubMed PMID: 25740516.

Monday, August 7, 2017

Why There Are No Bipartisan Solutions To Exorbitant Healthcare Costs In The USA

I happened to see Face The Nation yesterday.  Governors John Kasich and John Hickenlooper were on, talking about their attempted bipartisan solution to health care reform.  Their basic idea is that they and their staffers should be able to compromise and come up with a better proposal and possibly model cooperation for all of the uncompromising members of Congress.  Things did not look very well after the opening question by host John Dickerson:

"And we have seen in Washington both sides say they don't want to give up much of anything.  Give me your sense of what Republicans should back down on and what Democrats should back down on just as a preliminary good-faith effort to show that people are, on the health care question, committed to maybe working together."

I took out the key statement for both responses and included them in the above graphic.

The statements are very telling in terms of political rhetoric disguised as political philosophy.  Kasich seems to believe that there is a free market at work.  Hickenlooper seems to be more focused on the insurance principle of adverse selection - in this case the buyers of insurance with health problems are more likely to buy health insurance than younger healthy people without health concerns.  That leads to a concentration of buyers who increase the risk for the insurance company paying out and in the worst case a loss for the company.  Translation - the Democrats should give up on the idea of mandatory health insurance and the Republicans should give up on the idea of repealing mandatory health insurance.   That is quite a compromise.

An ethical framework is probably a better one to start from.  As I argued in a recent post - if your ethical priority from a political perspective is to allow people to have a choice - then give them choices when it comes to health care.  No choice is not an ethical option.  If your ethical priority is the value of human life - then universal access is necessary.  If the ethical priority is making sure that the resources being used by people who need health care services is finite and needs stewardship - then by all means make the entire system more cost effective for society at a whole.

All of the suggested ethical approaches cannot occur when the level of financial conflict of interest is large like it is in Congress.  Members of the US Senate get on the average $438,000 in donations from the Health care sector (PACs and individual contributions in the 2015-2016 election cycle).  That is a powerful incentive to keep making arguments about free markets and insurance markets that do not make any sense.  They make even less sense when it is clear that these same politicians are being lobbied to maintain the status quo - even though it is the most expensive and most inefficient health care system in the world.  The following graphic on the accumulation of administrators relative to the increase in physicians is just one illustration of that point.

Personal Communication David Himmelstein with his permission - July 2017.

So the next time you hear about the need for compromise and results from Congress, keep this scenario from Face The Nation in mind. Unless you have a reasonable assessment of what the problems really are, there is no starting point for compromise or consensus building. Policy makers in Washington are so far removed from an accurate assessment of the problem bad policy after bad policy is the logical outcome.

In discussing the problem with them a fair question is why the United States is incapable of coming up with effective health care at a reasonable price when all health care is currently rationed by for-profit companies.

It does not take single payer to get a better result, but it does take a government that is for the people rather than big health care business.

George Dawson, MD, DFAPA


1: Face The Nation Transcript from August 6, 2017: Guests included Tom Cotton, John Kasich, John Hickenlooper, Jeh Johnson, Susan Page, Reihan Salam, Jennifer Jacobs and Jamelle Bouie. (Accessed on August 6, 2017).