Here is a relatively simple math problem:  A bat and a ball cost $1.10 combined. The bat costs $1 more than the ball. How much does the ball cost? (I will provide the answer below the fold.)

This problem is the basis of a large psychological literature on thinking systems in the human brain, discussed in Daniel Kahneman’s book: Thinking, Fast and Slow. The idea is that there are two parallel thinking systems in the brain, a fast intuitive system that provides quick answers which may or may not be strictly true, and a slow analytical system that will go through a problem systematically and check the results.

This basic scheme is fairly well established in the research literature, but there are many sub-questions. For example – what is the exact nature of the intuition for any particular problem? What is the interaction between the fast and slow system? What if multiple intuitions come into conflict by giving different answers to the same problem? Is it really accurate to portray these different thinking styles as distinct systems? Perhaps we should consider them subsystems, since they are ultimately part of the same singular mind. Do they function like subroutines in a computer program? How can we influence the operations or interaction of these subroutines with prompting?

A recent publication present multiple studies with many subjects addressing these subquestions. If you are interested in this question I suggest reading the original article in full. It is fairly accessible. But here is my overview. Continue Reading »

I will acknowledge up front that I never drink, ever. The concept of deliberately consuming a known poison to impair the functioning of your brain never appealed to me. Also, I am a bit of a supertaster, and the taste of alcohol to me is horrible – it overwhelms any other potential flavors in the drink. But I am also not judgmental. I understand that most people who consume alcohol do so in moderation without demonstrable ill effects. I also know I am in the minority when it comes to taste.

But we do need to recognize that alcohol, like many other substances of abuse like cocaine, has the ability to be addictive, and can result in alcohol use disorder. Excessive alcohol use costs the US economy $249 billion per year from health care costs, lost productivity, traffic accidents, and criminal justice system costs. It dwarfs all other addictive substances combined. It is also well established that long term, excessive alcohol use reduces cognitive function.

Recent research has explored the question of exactly what the effects of addictive substances are on the brain with chronic use. One of the primary effects appears to be on cognitive flexibility. In general terms this neurological function is exactly what it sounds like – flexibility in thinking and behavior. But researchers always need a way to operationalize such concepts – how do we measure it? There are two basic ways to operationalize cognitive flexibility – set shifting and task switching. Set shifting involves change the rules of how to accomplish a task, while task switching involves changes to a different task altogether.

For example, a task switching test might involve sorting objects that are of different shapes, colors, textures, and sizes. First subjects may be told to sort by colors, but also they are to respond to a specific cue (such as a light going on) by switching to sorting by shape. The test is – how quickly and effectively can a subject switch tasks like this? How many sorting mistakes will they make after switching tasks? Set shifting, on the other hand, changes the rules rather than the task – push the button every time the red light comes on, vs the green light.

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There is a lot of social psychology out there providing information that can inform our everyday lives, and most people are completely unaware of the research. Richard Wiseman makes this point in his book, 59 Seconds – we actually have useful scientific information, and yet we also have a vast self-help industry giving advice that is completely disconnected from this evidence. The result is that popular culture is full of information that is simply wrong. It is also ironically true that it many social situations our instincts are also wrong, probably for complicated reasons.

Let’s consider gift-giving, for example. Culture and intuition provide several answers as to what constitutes a good gift, which we can define as the level of gratitude and resulting happiness on the part of the gift recipient. We can also consider a secondary, but probably most important, outcome – the effect on the relationship between the giver and receiver. There is also the secondary effect of the satisfaction of the gift giver, which depends largely on the gratitude expressed by the receiver.

When considering what makes a good gift, people tend to focus on a few variables, reinforced by cultural expectations – the gift should be a surprise, it should provoke a big reaction, it should be unique, and more expensive gifts should evoke more gratitude. But it turns out, none of these things are true.

A recent study, for example, tried to simulate prior expectations on gift giving and found no significant effect on gratitude. These kinds of studies are all constructs, but there is a pretty consistent signal in the research that surprise is not an important factor to gift-giving. In fact, it’s a setup for failure. The gift giver has raised expectations of gratitude because of the surprise factor, and is therefore likely to be disappointed. The gift-receiver is also less likely to experience happiness from receiving the gift if the surprise comes at the expense of not getting what they really want. You would be far better off just asking the person what they want, or giving them something you know that they want and value rather than rolling the dice with a surprise. To be clear, the surprise factor itself is not a negative, it’s just not really a positive and is a risk.

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Do birds of a feather flock together, or do opposites attract? These are both common aphorisms, which means that they are commonly offered as generally accepted truths, but also that they may by wrong. People like pithy phrases, so they spread prolifically, but that does not mean they contain any truth. Further, our natural instincts are not adequate to properly address whether they are true or not.

Often people will resort to the “availability heuristic” when confronted with these types of claims. If they can readily think of an example that seems to support the claim, then they accept it as probably true. We use the availability of an example as a proxy for data, but it’s a very bad proxy. What we really need to address such questions is often statistics, something which is not very intuitive for most people.

Of course, that’s where science comes in. Science is a formal system we use to supplement our intuition, to come to more reliable conclusions about the nature of reality. Recently researchers published a very large review of data, a meta-analysis, combined with a new data analysis to address this very question. First, we need operationalize the question, to put it in a form that is precise and amenable to objective data. If we look at couples, how similar or different are they? To get even more precise, we need to identify specific traits that can be measured or quantified in some way and compare them.

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What’s going on in the minds of people who appear to be comatose? This has been an enduring neurological question from the beginning of neurology as a discipline. Recent technological advances have completely changed the game in terms of evaluating comatose patients, and now a recent study takes our understanding one step further by teasing apart how different systems in the brain contribute to conscious responsiveness.

This has been a story I have been following closely for years, both as a practicing neurologist and science communicator. For background, when evaluating patients who have a reduced ability to execute aspects of the neurological exam, there is an important question to address in terms of interpretation – are they not able to perform a given task because of a focal deficit directly affecting that task, are they generally cognitively impaired or have decreased level of conscious awareness, or are other focal deficits getting in the way of carrying out the task? For example, if I ask a patient to raise their right arm and they don’t, is that because they have right arm weakness, because they are not awake enough to process the command, or because they are deaf? Perhaps they have a frozen shoulder, or they are just tired of being examined. We have to be careful in interpreting a failure to respond or carry out a requested action.

One way to deal with this uncertainty is to do a thorough exam. The more different types of examination you do, the better you are able to put each piece into the overall context. But this approach has its limits, especially when dealing with patients who have a severe impairment of consciousness, which gets us to the context of this latest study. For further background, there are different levels of impaired consciousness, but we are talking here about two in particular. A persistent vegetative state is defined as an impairment of consciousness in which the person has zero ability to respond to or interact with their environment. If there is any flicker of responsiveness, then we have to upgrade them to a minimally conscious state. The diagnosis of persistent vegetative state, therefore, is partly based on demonstrating the absence of a finding, which means it is only as reliable as the thoroughness with which one has looked. This is why coma specialists will often do an enhanced neurological exam, looking really closely and for a long time for any sign of responsiveness. Doing this picks up a percentage of patients who would otherwise have been diagnosed as persistent vegetative.

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Decades of complex research and persevering through repeated disappointment appears to be finally paying off for the diagnosis and treatment of Alzheimer’s  disease (AD). In 2021 Aduhelm was the first drug approved by the FDA (granted contingent accelerated approval) that is potentially disease-modifying in AD. This year two additional drugs received FDA approval. All three drugs are monoclonal antibodies that target amyloid protein. They each seem to have overall modest clinical effect, but they are the first drugs to actually slow down progression of AD, which represents important confirmation of the amyloid hypothesis. Until now attempts at slowing down the disease by targeting amyloid have failed.

Three drugs in as many years is no coincidence – this is the result of decades of research into a very complex disease, combined with monoclonal antibody technology coming into its own as a therapeutic option. AD is a form of dementia, a chronic degenerative disease of the brain that causes the slow loss of cognitive function and memory over years. There are over 6 million people in the US alone with AD, and it represents a massive health care burden. More than 10% of the population over 65 have AD.

The probable reason we have rapidly crossed over the threshold to detectable clinical effect is attributed by experts to two main factors – treating people earlier in the disease, and giving a more aggressive treatment (essentially pushing dosing to a higher level). The higher dosing comes with a downside of significant side effects, including brain swelling and bleeding. But that it what it took to show even a modest clinical benefit. But the fact that three drugs, which target different aspects of amyloid protein, show promising or demonstrated clinical benefit helps confirm that the amyloid protein and the plaques they form in the brain are, to some extend driving AD. They are not just a marker for brain cell damage, they are at least partly responsible for that damage. Until now, this was not clear.

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Psychologists have been studying a very basic cognitive function that appears to be of increasing importance – how do we choose what to believe as true or false? We live in a world awash in information, and access to essentially the world’s store of knowledge is now a trivial matter for many people, especially in developed parts of the world. The most important cognitive skill in the 21st century may arguably be not factual knowledge but truth discrimination. I would argue this is a skill that needs to be explicitly taught in school, and is more important than teaching students facts.

Knowing facts is still important, because you cannot think in a vacuum. Our internal model of the world is build on bricks of fact, but before we take a brick and place it in our wall of knowledge, we have to decide if it is probably true or not. I have come to think about this in terms of three categories of skills – domain knowledge (with scientific claims this is scientific literacy), critical thinking, and media savvy.

Domain knowledge, or scientific literacy, is important because without a working knowledge of a topic you have no basis for assessing the plausibility of a new claim. Does it even make basic sense? An easily refutable claim may be accepted simply because you don’t know it is easily refutable. Critical thinking skills involve an understanding of the heuristics we naturally use to estimate truth, our cognitive biases, cognitive pitfalls like conspiracy thinking, how motivation affects our thought processes, and mechanisms of self deception. Media savvy involves understanding how to assess the reliability of information sources, how information ecosystems work, and how information is used by others to deceive us.

A recent study involves one aspect of this latter category – how do we assess the reliability of information sources and how this affects our bottom line assessment of whether or not something is true. The researchers did two studies involving 1,181 subjects. They gave the subjects factual information, then presented them with claims made by a media outlet. They were further told whether the media outlet intended to inform or deceive on this topic. They studies claims that are considered highly politicized and those that were not.

What they found is that subjects were more likely to deem a claim true if it came from a source considered to be trying to inform, and more likely to be false when the source was characterized as trying to deceive – even if the claims were the same. At first this result seems strange because the subjects were told the actual facts, so they knew absolutely (within the confines of the study) whether or not the claim was true.

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In my last post I noted that even mentioning general vague support for the LGBTQ community was enough to trigger very specific feedback, often making erroneous scientific claims. Each claim requires a deep dive and article-length discussion. Even though the discussion that followed in the comments was better than I thought it would be, it still filled with additional dubious claims. I suspect there are two main reasons for this. The first is that the topic of gender identity is complex and not intuitive. It may feel intuitive, as if your immediate gut reaction is all that is necessary to deal adequately with the topic, but it really isn’t. Ultimate this topic deals with how our brains construct our own sense of self, identity, and reality. These are always tricky concepts to deal with – and as I have pointed out before in other contexts, our brain constructs are counterintuitive by their very nature. In other words, our brains evolved for these constructs to feel real and automatic, and for the subconscious processes that create them to be invisible to us.

Second, the issue of gender identity has been highly politicized. This has resulted in any discussion of the topic being flooded with biased and deliberate misinformation. The usual FUD (fear, uncertainty doubt) strategies apply. And of course – science is hard. Even seemingly straightforward questions are actually quite complex. This makes it easy to create confusion by “just asking questions” or selectively applying skepticism.

One question at the heart of the trans issue is this – what is the rate of regret or even detransitioning after medical transition? One narrative is that adolescents (often conflated with “children”) are being prematurely herded down a road to transition, which they later regret. The other narrative is that, generally speaking, making the decision to transition is taken very seriously, with very low levels of later regret. Which is true?

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On the current episode of the SGU, because it is pride month, we expressed our general support for the LGBTQ community. I also opined about how important it is to respect individual liberty, the freedom to simply live your authentic life as you choose, and how ironic it is that often the people screaming the loudest about liberty seem the most willing to take it away from others. That was it – we didn’t get into any specific issues. And yet this discussion provoked several responses, filled with strawman accusations about things we never said, and weighed down with a typical list of tropes and canards. It would take many articles to address them all, so I will focus on just one here. One e-mailer claimed: “It is obvious to me that the 98% of trans people have a mental illness that should be treated like any other mental illnesses.”

Being trans itself is not considered a mental illness, but this deserves some extensive discussion. It’s important to first establish some basic principles, starting with – what is mental illness? This is a deceptively tricky question. The American Psychiatric Association provides this definition:

Mental illnesses are health conditions involving changes in emotion, thinking or behavior (or a combination of these). Mental illnesses can be associated with distress and/or problems functioning in social, work or family activities.

But this is not a technical or operational definition (something that requires book-length exploration to be thorough), but rather a quick summary for lay readers. In fact, there is no one generally accepted technical definition. There is some heterogeneity throughout the scientific literature, and it may vary from one illness to another and one institution to another. But there are some generally accepted key elements.

First, as the WHO states, “Mental disorders involve significant disturbances in thinking, emotional regulation, or behaviour.” But then we have to define “disorder”, which is typically defined as a lack or alternation in a function possessed by most healthy individuals that causes demonstrable harm. “Significant” is also a word that’s doing a lot of heavy lifting there. This is typically determined disorder by disorder, but usually includes elements of persistent duration for greater than some threshold, and some pragmatic measure of severity. For example, does the disorder prevent someone from participating in meaningful activity, productive work, or activities of daily living? Does it provoke other demonstrable harms, such as severe depression or anxiety? Does it entail increased risk of negative health or life outcomes?

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The story of a woman, in a severe state of catatonia for years and “waking up” after being treated for an autoimmune disease, is making the rounds and deserves a little bit of context. April Burrell was diagnosed with a severe form of schizophrenia resulting in catatonia, and has been in long term care since 2000. However, she was also more recently found to have lupus, an autoimmune disease that can affect the brain. After being treated with immunosuppressive medications, multiple courses of treatment over months, her condition steadily improved. She still has symptoms of psychosis and is not cognitively normal, but is able to recognize people and interact and does much better on standard cognitive tests. The credit for her recovery goes to a psychiatrist, Sander Markx, who had seen the patient 20 years before, and upon learning that she was still institutionalized and unchanged order the workup that resulted in the diagnosis.

This is a remarkable case, but is not ultimately surprising. I had a similar case as a resident. A patient was admitted with worsening schizophrenia. He had severe schizophrenia for the last 20 years or so, mostly cared for at home by his family, but now was simply getting too difficult to give proper care. He was admitted to the psychiatry floor, and they consulted the neurology service almost as an afterthought, because the patient had been lost to follow up for so long. We had a low clinical suspicion that there was anything neurological going on, but recommended a CT scan of the brain and other workup, just to be thorough. The CT scan found a very large tumor pushing in on his frontal lobes. The tumor itself was outside the brain but inside the skull. Neurosurgery was consulted, the tumor was promptly removed, and within days the patient was almost back to his pre-schizophrenic baseline – essentially cured. That’s the kind of case you never forget.

To put such cases into clinical perspective it’s important to recognize that schizophrenia is a clinical diagnosis, meaning that it is based upon signs and symptoms, not any pathological findings on imaging or laboratory workup. There are markers and researchers are trying to understand it better as a brain disease, but for now the diagnosis is still mainly clinical. Part of the clinical diagnosis, however, is ruling out neurological pathology. This is a standard referral that we neurologists get from psychiatrists – rule out neurological disease. Only when that is done is the patient given a psychiatric diagnosis.

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