Carving Up Brain Disorders

Neurology and Psychiatry are two distinct specialties within medicine, both of which treat disorders of the brain. It's completely uncontroversial to say that neurologists treat patients with brain disorders like Alzheimer's disease and Parkinson's disease. These two diseases produce distinct patterns of neurodegeneration that are visible on brain scans. For example, Parkinson's disease (PD) is a movement disorder caused by the loss of dopamine neurons in the midbrain.

Fig. 3 (modified from Goldstein et al., 2007). Brain PET scans superimposed on MRI scans. Note decreased dopamine signal in the putamen and substantia nigra (S.N.) bilaterally in the patient.


It's also uncontroversial to say that drugs like L-DOPA and invasive neurosurgical interventions like deep brain stimulation (DBS) are used to treat PD.

On the other hand, some people will balk when you say that psychiatric illnesses like bipolar disorder and depression are brain disorders, and that drugs and DBS (in severe intractable cases) may be used to treat them. You can't always point to clear cut differences in the MRI or PET scans of psychiatric patients, as you can with PD (which is a particularly obvious example).

The diagnostic methods used in neurology and psychiatry are quite different as well. The standard neurological exam assesses sensory and motor responses (e.g., reflexes) and basic mental status. PD has sharply defined motor symptoms including tremor, rigidity, impaired balance, and slowness of movement. There are definitely cases where the symptoms of PD should be attributed to another disease (most notably Lewy body dementia)¹, and other examples where neurological diagnosis is not immediately possible. But by and large, no one questions the existence of a brain disorder.

Things are different in psychiatry. Diagnosis is not based on a physical exam. Psychiatrists and psychologists give clinical interviews based on the Diagnostic and Statistical Manual (DSM-5), a handbook of mental disorders defined by a panel of experts with opinions that are not universally accepted. The update from DSM-IV to DSM-5 was highly controversial (and widely discussed).

The causes of mental disorders are not only biological, but often include important social and interpersonal factors. And their manifestations can vary across cultures.

Shortly before the release of DSM-5, the former director of NIMH (Dr. Tom Insel) famously dissed the new manual:

The strength of each of the editions of DSM has been “reliability” – each edition has ensured that clinicians use the same terms in the same ways. The weakness is its lack of validity. Unlike our definitions of ischemic heart disease, lymphoma, or AIDS, the DSM diagnoses are based on a consensus about clusters of clinical symptoms, not any objective laboratory measure.

In other words, where are the clinical tests for psychiatric disorders?

For years, NIMH has been working on an alternate classification scheme, the Research Domain Criteria (RDoC) project, which treats mental illnesses as brain disorders that should be studied according to domains of functioning (e.g., negative valence). Dimensional constructs such as acute threat (“fear”) are key, rather than categorical DSM diagnosis. RDoC has been widely discussed on this blog and elsewhere — it's the best thing since sliced bread, it's necessary but very oversold, or it's ill-advised.

What does this have to do with neurology, you might ask? In 2007, Insel called for the merger of neurology and psychiatry:

Just as research during the Decade of the Brain (1990-2000) forged the bridge between the mind and the brain, research in the current decade is helping us to understand mental illnesses as brain disorders. As a result, the distinction between disorders of neurology (e.g., Parkinson's and Alzheimer's diseases) and disorders of psychiatry (e.g., schizophrenia and depression) may turn out to be increasingly subtle. That is, the former may result from focal lesions in the brain, whereas the latter arise from abnormal activity in specific brain circuits in the absence of a detectable lesion. As we become more adept at detecting lesions that lead to abnormal function, it is even possible that the distinction between neurological and psychiatric disorders will vanish, leading to a combined discipline of clinical neuroscience.

Actually, Insel's view dates back to 2005 (Insel & Quirion, 2005)....²

Future training might begin with two post-graduate years of clinical neuroscience shared by the disciplines we now call neurology and psychiatry, followed by two or three years of specialty training in one of several sub-disciplines (ranging from peripheral neuropathies to public sector and transcultural psychiatry). This model recognizes that the clinical neurosciences have matured sufficiently to resemble internal medicine, with core training required prior to specializing.

...and was expressed earlier by Dr. Joseph P. Martin, Dean of Harvard Medical School (Martin, 2002):

Neurology and psychiatry have, for much of the past century, been separated by an artificial wall created by the divergence of their philosophical approaches and research and treatment methods. Scientific advances in recent decades have made it clear that this separation is arbitrary and counterproductive. .... Further progress in understanding brain diseases and behavior demands fuller collaboration and integration of these fields. Leaders in academic medicine and science must work to break down the barriers between disciplines.

Contemporary leaders and observers of academic medicine are not all equally ecstatic about this prospect, however. Taylor et al. (2015) are enthusiastic advocates of a move beyond “Neural Cubism”, to increased integration of neurology and psychiatry. Dr. Sheldon Benjamin agrees that greater cross-discipline training is needed, but wants the two fields to remain separate. But Dr. Jose de Leon thinks the psychiatry/neurology integration is a big mistake that revives early 20th century debates (see table below, in the footnotes).³

I think a distinction can (and should) be made between the research agenda of neuroscience and the current practice of psychiatry. Neuroscientists who work on such questions assume that mental illnesses are brain disorders and act accordingly, by studying the brain. They study animal models and brain slices and genes and humans with implanted or attached electrodes and humans in scanners. And they study the holy grail of neural circuits using DREDDs and optogenetics. This doesn't invalidate the existence of social, cultural, and interpersonal factors that affect the development and manifestation of mental illnesses. As an non-clinician, I have less to say about medical practice. I'm not grandiose enough to claim that neuroscience research (or RDoC, for that matter) will transform the practice of psychiatry (or neurology) in the near future. [Though you might think differently if you read Public Health Relevance Statements or articles in high profile journals.]

Basic researchers may not even think about the distinction between neurology and psychiatry. Is the abnormal deposition of amyloid-β peptide in Alzheimer's disease (AD) an appropriate target for treatment? Are metabotropic glutamate receptors an appropriate target in schizophrenia? These are similar questions, despite the fact that one disease is neurological and the other psychiatric. There are defined behavioral endpoints that mark treatment-related improvements in either case. It's very useful to measure a change in amyloid burden⁴ using florbetapir PET imaging in AD [there's nothing similar in schizophrenia], but the most important measure is cognitive improvement (or a flattening of cognitive decline).


Does Location Matter?

In response to the pro-merger cavalcade, a recent meta-analysis asked whether the entire category of neurological disorders affects different brain regions than the entire category of psychiatric disorders (Crossley et al., 2015). The answer was why yes, the two categories affect different brain areas, and for this reason neurology and psychiatry should remain separate.

I thought this was an odd question to begin with, and an even odder conclusion. It's not surprising that disorders of movement, for example, involve different brain regions than disorders of mood or disorders of thought. From my perspective, it's more interesting to look at where the two categories overlap, with an eye to specific comparisons (not global lumping). For instance, are compulsive and repetitive behaviors in OCD associated with alterations in some of the subcortical circuits implicated in movement disorders? Why yes.

But let's take a closer look at the technical details of the study.

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Happiness Is a Large Precuneus

What is happiness, and how do we find it? There are 93,290 books on happiness at Amazon.com. Happiness is Life's Most Important Skill, an Advantage and a Project and a Hypothesis that we can Stumble On and Hard-Wire in 21 Days.

The Pursuit of Happiness is an Unalienable Right granted to all human beings, but it also generates billions of dollars for the self-help industry.

And now the search for happiness is over! Scientists have determined that happiness is located in a small region of your right medial parietal lobe. Positive psychology gurus will have to adapt to the changing landscape or lose their market edge. “My seven practical, actionable principles are guaranteed to increase the size of your precuneus or your money back.”

The structural neural substrate of subjective happiness is the precuneus.

A new paper has reported that happiness is related to the volume of gray matter in a 222.8 mm³ cluster of the right precuneus (Sato et al., 2015). What does this mean? Taking the finding at face value, there was a correlation (not a causal relationship) between precuneus gray matter volume and scores on the Japanese version of the Subjective Happiness Scale.¹

Fig. 1 (modified from Sato et al., 2015).  Left: Statistical parametric map (p < 0.001, peak-level uncorrected for display purposes). The blue cross indicates the location of the peak voxel. Right: Scatter plot of the adjusted gray matter volume as a function of the subjective happiness score at the peak voxel. [NOTE: Haven't we agreed to not show regression lines through scatter plots based on the single voxel where the effect is the largest??]


“The search for happiness: Using MRI to find where happiness happens,” said one deceptive headline. Should we accept the claim that one small region of the brain is entirely responsible for generating and maintaining this complex and desirable state of being?

NO. Of course not. And the experimental subjects were not actively involved in any sort of task at all. The study used a static measure of gray matter volume in four brain Regions of Interest (ROIs): left anterior cingulate gyrus, left posterior cingulate gyrus, right precuneus, and left amygdala. These ROIs were based on an fMRI activation study in 26 German men (mean age 33 yrs) who underwent a mood induction procedure (Habel et al., 2005). The German participants viewed pictures of faces with happy expressions and were told to “Look at each face and use it to help you to feel happy.” The brain activity elicited by happy faces was compared to activity elicited by a non-emotional control condition. Eight regions were reported in their Table 1.

Table 1 (modified from Habel et al., 2005).


Only four of those regions were selected as ROIs by Sato et al. (2015). One of these was a tiny 12 voxel region in the paracentral lobule, which was called precuneus by Sato et al. (2015).

Image: John A Beal, PhD. Dept. of Cellular Biology & Anatomy, Louisiana State University Health Sciences Center Shreveport.


Before you say I'm being overly pedantic, we can agree that the selected coordinates are at the border of the precuneus and the paracentral lobule. The more interesting fact is that the sadness induction of Habel et al. (2005) implicated a very large region of the posterior precuneus and surrounding regions (1562 voxels). An area over 100 times larger than the Happy Precuneus.

Oops. But the precuneus contains multitudes, so maybe it's not so tragic. The precuneus is potentially involved in very lofty functions like consciousness and self-awareness and the recollection of  autobiographical memories. It's also a functional core of the default-mode network (Utevsky et al., 2014), which is active during daydreaming and mind wandering and unconstrained thinking.

But it seems a bit problematic to use hand picked ROIs from a study of transient and mild “happy” states (in a population of German males) to predict a stable trait of subjective happiness in a culturally distinct group of younger Japanese college students (26 women, 25 men).


Cross-Cultural Notions of Happiness

Isn't “happiness” a social construct (largely defined by Western thought) that varies across cultures?

Ipsos

Should we expect “the neural correlates of happiness” (or well-being) to be the same in Japanese and Chinese and British college students? In the Chinese study, life satisfaction was positively correlated with gray matter volume in the right parahippocampal gyrus but negatively correlated with gray matter volume in the left precuneus... So the participants with the largest precuneus volumes in that study had the lowest well-being.

What does a bigger (or smaller) size even mean for actual neural processing? Does a larger gray matter volume in the precuneus allow for a higher computational capacity that can generate greater happiness?? We have absolutely no idea: “...there is no clear evidence of correlation between GM volume measured by VBM and any histological measure, including neuronal density” (Gilaie-Dotan et al., 2014).

Sato et al. (2015) concluded that their results have important practical implications: Are you happy? We don't have to take your word for it any more!

In terms of public policy, subjective happiness is thought to be a better indicator of happiness than economic success. However, the subjective measures of happiness have inherent limitations, such as the imprecise nature of comparing data across different cultures and the difficulties associated with the applications of these measures to specific populations, including the intellectually disabled. Our results show that structural neuroimaging may serve as a complementary objective measure of subjective happiness.

Finally, they issued the self-help throw down: “...our results suggest that psychological training that effectively increases gray matter volume in the precuneus may enhance subjective happiness.”


Resting-state functional connectivity of the default mode network associated with happiness is so last month...

adapted from Luo et al. (2015)

Further Reading

Are You Conscious of Your Precuneus?

Be nice to your Precuneus – it might be your real self…

Your Precuneus May Be the Root of Happiness and Satisfaction

The Precuneus and Recovery From a Minimally Conscious State


Footnote

¹ The Subjective Happiness Scale is a 4-item measure of global subjective happiness (Lyubomirsky & Lepper, 1999).

References

Habel, U., Klein, M., Kellermann, T., Shah, N., & Schneider, F. (2005). Same or different? Neural correlates of happy and sad mood in healthy males NeuroImage, 26 (1), 206-214 DOI: 10.1016/j.neuroimage.2005.01.014

Sato, W., Kochiyama, T., Uono, S., Kubota, Y., Sawada, R., Yoshimura, S., & Toichi, M. (2015). The structural neural substrate of subjective happiness Scientific Reports, 5 DOI: 10.1038/srep16891

The Neuroscience of Social Media: An Unofficial History

There's a new article in Trends in Cognitive Sciences about how neuroscientists can incorporate social media into their research on the neural correlates of social cognition (Meshi et al., 2015). The authors outlined the sorts of social behaviors that can be studied via participants' use of Twitter, Facebook, Instagram, etc.: (1) broadcasting information; (2) receiving feedback; (3) observing others' broadcasts; (4) providing feedback; (5) comparing self to others.

Meshi, Tamir, and Heekeren / Trends in Cognitive Sciences (2015)

More broadly, these activities tap into processes and constructs like emotional state, personality, social conformity, and how people manage their self-presentation and social connections. You know, things that exist IRL (this is an important point to keep in mind for later).

The neural systems that mediate these phenomena, as studied by social cognitive neuroscience types, are the Mentalizing Network (in blue below), the Self-Referential Network (red), and the Reward Network (green).

Fig. 2 (Meshi et al., 2015). Proposed Brain Networks Involved in Social Media Use.  (i) mentalizing network: dorsomedial prefrontal cortex (DMPFC), temporoparietal junction (TPJ), anterior temporal lobe (ATL), inferior frontal gyrus (IFG), posterior cingulate cortex/precuneus (PCC). (ii) self-referential network: medial prefrontal cortex (MPFC) and PCC. (iii) reward network: ventromedial prefrontal cortex (VMPFC), ventral striatum (VS), ventral tegmental area (VTA). 


The article's publication was announced on social media:

The emerging neuroscience of social media. New review in @TrendsCognSci: https://t.co/2JDIeCvJsT pic.twitter.com/2vwv827bdI

— CellPressNews (@CellPressNews) November 11, 2015

I anticipated this day in 2009, when I wrote several satirical articles about the neurology of Twitter.  I proposed that someone should do a study to examine the neural correlates of Twitter use:

It was bound to happen. Some neuroimaging lab will conduct an actual fMRI experiment to examine the so-called "Neural Correlates of Twitter" -- so why not write a preemptive blog post to report on the predicted results from such a study, before anyone can publish the actual findings?

Here are the conditions I proposed, and the predicted results (a portion of the original post is reproduced below).


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Obesity Is Not Like Being "Addicted to Food"

Credit: Image courtesy of Aalto University

Is it possible to be “addicted” to food, much like an addiction to substances (e.g., alcohol, cocaine, opiates) or behaviors (gambling, shopping, Facebook)? An extensive and growing literature uses this terminology in the context of the “obesity epidemic”, and looks for the root genetic and neurobiological causes (Carlier et al., 2015; Volkow & Bailer, 2015).

Fig. 1 (Meule, 2015). Number of scientific publications on food addiction (1990-2014). Web of Science search term “food addiction”.


Figure 1 might lead you to believe that the term “food addiction” was invented in the late 2000s by NIDA. But this term is not new at all, as Adrian Meule (2015) explained in his historical overview, Back by Popular Demand: A Narrative Review on the History of Food Addiction Research. Dr. Theron G. Randolph wrote about food addiction in 1956 (he also wrote about food allergies).

Fig. 2 (Meule, 2015). History of food addiction research.


Thus, the concept of food addiction predates the documented rise in obesity in the US, which really took off in the late 80s to late 90s (as shown below).¹

Prevalence of Obesity in the United States, 1960-2012

1960-62	1971-74	1976-80	1988-89	1999-2000
12.80%	14.10%	14.50%	22.50%	30.50%
				2007-08	2011-12
				33.80%	34.90%

Sources: Flegal et al. 1998, 2002, 2010; Ogden et al. 2014


One problem with the “food addiction” construct is that you can live without alcohol and gambling, but you'll die if you don't eat. Complete abstinence is not an option.²

Another problem is that most obese people simply don't show signs of addiction (Hebebrand, 2015):

...irrespective of whether scientific evidence will justify use of the term food and/or eating addiction, most obese individuals have neither a food nor an eating addiction.³ Obesity frequently develops slowly over many years; only a slight energy surplus is required to in the longer term develop overweight. Genetic, neuroendocrine, physiological and environmental research has taught us that obesity is a complex disorder with many risk factors, each of which have small individual effects and interact in a complex manner. The notion of addiction as a major cause of obesity potentially entails endless and fruitless debates, when it is clearly not relevant to the great majority of cases of overweight and obesity.

Still not convinced? Surely, differences in the brains' of obese individuals point to an addiction. The dopamine system is altered, right, so this must mean they're addicted to food? Well think again, because the evidence for this is inconsistent (Volkow et al., 2013; Ziauddeen & Fletcher, 2013).

An important new paper by a Finnish research group has shown that D2 dopamine receptor binding in obese women is not different from that in lean participants (Karlsson et al., 2015). Conversely, μ-opioid receptor (MOR) binding is reduced, consistent with lowered hedonic processing. After the women had bariatric surgery (resulting in mean weight loss of 26.1 kg, or 57.5 lbs), MOR returned to control values, while the unaltered D2 receptors stayed the same.

In the study, 16 obese women (mean BMI=40.4, age 42.8) had PET scans before and six months after undergoing the standard Gastric Bypass procedure (Roux-en-Y Gastric Bypass) or the Sleeve Gastrectomy. A comparison group of non-obese women (BMI=22.7, age 44.9) was also scanned. The radiotracer [¹¹C]carfentanil measured MOR availability and [¹¹C]raclopride measured D2R availability in two separate sessions. The opioid and dopamine systems are famous for their roles in neural circuits for “liking” (pleasurable consumption) and “wanting” (incentive/motivation), respectively (Castro & Berridge, 2014).

The pre-operative PET scans in the obese women showed that MOR binding was significantly lower in a number of reward-related regions, including ventral striatum, dorsal caudate, putamen, insula, amygdala, thalamus, orbitofrontal cortex and posterior cingulate cortex. Six months after surgery, there was an overall 23% increase in MOR availability, which was no longer different from controls.

Fig. 1 (modified from Karlsson et al., 2015). Top: μ-opioid receptors are reduced in obese participants pre-operatively (middle), but after bariatrc surgery (right) they recover to control levels (left). Bottom: D2 receptors are unaffected in the obese participants.


Karlsson et al. (2015) suggest that:

The MOR system promotes hedonic [pleasurable] aspects of feeding, and this can make obese individuals susceptible to overeating in order to gain the desired hedonic response from food consumption, which may further promote pathological eating. We propose that at the initial stages of weight gain, excessive eating may cause perpetual overstimulation of the MOR system, leading to subsequent MOR downregulation.  ...  However, bariatric surgery-induced weight loss and decreased food intake may reverse this process.

The unchanging striatal dopamine D₂ receptor densities in the obese participants are in stark contrast to what is seen in individuals who are addicted to stimulant drugs, such as cocaine and methamphetamine (Volkow et al., 2001). Drugs of abuse are consistently associated with decreases in D2 receptors.

Fig. 1 (modified from Volkow et al., 2001). Ratio of the Distribution Volume of [¹¹C]Raclopride in the Striatum (Normalized to the Distribution Volume in the Cerebellum) in a Non-Drug-Abusing Comparison Subject and a Methamphetamine Abuser.


So the next time you see a stupid ass headline like, “Cheese really is crack. Study reveals cheese is as addictive as drugs”, you'll know the writer is on crack.


Further Reading - The Scicurious Collection on Obesity

Overeating and Obesity: Should we really call it food addiction?

No, cheese is not just like crack

Dopamine and Obesity: The D2 Receptor

Dopamine and Obesity: The Food Addiction?

Cheesecake-eating rats and food addiction, a commentary


Footnotes

¹ Not surprisingly, papers on the so-called obesity epidemic lagged behind the late 80s-mid 90s rise in prevalence.

- click on image for a larger view -

Number of papers on "obesity epidemic" in PubMed (1996-2015)

² Notice in Fig. 2 that anorexia is considered the opposite: an addiction to starving.

³ Binge eating disorder (BED) might be another story, and I'll refer you to an informative post by Scicurious for discussion of that issue. You do not have to be obese (or even overweight) to have BED.


References

Carlier N, Marshe VS, Cmorejova J, Davis C, Müller DJ. (2015). Genetic Similarities between Compulsive Overeating and Addiction Phenotypes: A Case for "Food Addiction"? Curr Psychiatry Rep. 17(12):96.

Castro, D., & Berridge, K. (2014). Advances in the neurobiological bases for food ‘liking’ versus ‘wanting’ Physiology & Behavior, 136, 22-30 DOI: 10.1016/j.physbeh.2014.05.022

Karlsson, H., Tuulari, J., Tuominen, L., Hirvonen, J., Honka, H., Parkkola, R., Helin, S., Salminen, P., Nuutila, P., & Nummenmaa, L. (2015). Weight loss after bariatric surgery normalizes brain opioid receptors in morbid obesity Molecular Psychiatry DOI: 10.1038/mp.2015.153

Meule A (2015). Back by Popular Demand: A Narrative Review on the History of Food Addiction Research. The Yale journal of biology and medicine, 88 (3), 295-302 PMID: 26339213

Volkow ND, Baler RD. (2015). NOW vs LATER brain circuits: implications for obesity and addiction. Trends Neurosci. 38(6):345-52.

Volkow ND, Wang GJ, Tomasi D, Baler RD. (2013). Obesity and addiction: neurobiological overlaps. Obes Rev. 14(1):2-18.

Ziauddeen H, Fletcher PC. (2013). Is food addiction a valid and useful concept? Obes Rev. 14(1):19-28.