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The Seductive Allure of Neuroscience Explanations
Does dropping a few brain-related words into an argument cause people to lose the capacity for critical thought?
As regular readers will be well aware, much of what I've covered on this blog has been about the use and abuse of the prefix "neuro" to mislead. You don't have to look far to see that most people seem to be pretty disconnected from the science of the brain. This becomes a problem once you realize how this allows us to be misled. Take, for example, the adverts for "brain training" games that stalk you on the internet with claims that don't even remotely hold water; or the fact that a laughable technique called "Brain Gym" that involves making children perform pointless exercises and is based on no evidence whatsoever continues to be widespread in schools across the world at a cost of hundreds of thousands of dollars, and has been used by as many as 39 percent of teachers in the UK. Drop a few brain-related words and it seems even teachers can lose the capacity for critical thought en masse.
In 2008, a paper titled "The Seductive Allure of Neuroscience Explanations," struck a chord with me when it made the case that we can be suckered into judging bad psychological explanations as better than they really are if they are served with a side order of irrelevant neuroscience. Another paper published the same year suggested that just showing an image of the brain alongside articles describing fictitious neuroscience research (for example claiming that watching TV improves mathematical ability) resulted in people rating the standard of reasoning in the articles as higher.
In 2013 however, a paper was published that remains a strong contender for the award of best-named paper of all time: "The Seductive Allure of Seductive Allure." The paper pointed out flaws in both of the 2008 papers: The neuroscience explanations were longer and arguably added to the psychological explanations. It could be the case that more complicated-sounding, or seemingly better-explained explanations are simply more persuasive. If this were the case, this would be a rather less ground-breaking conclusion. This suggestion was posed way back in 2009 by the blogger Neuroskeptic. Furthermore, a systematic replication of the 2008 brain scan paper involving 10 experiments and a whopping 2,000 participants failed to find any evidence that the addition of a brain scan alone had any real impact on people; it seemed the "seductive allure of neuroscience explanations" was in tatters.
Soon the "Seductive Allure of Seductive Allure" debate was everywhere; even Vice got involved. The realization that simply adding pretty pictures of brains to an argument isn't enough to fool most people probably shouldn't have been so surprising. What seems to have been largely ignored however, is that the huge 2013 systematic replication, which was the centerpiece of the "Seductive Allure of Seductive Allure" case, in fact did replicate the original " Seductive Allure of Neuroscience Explanations" finding: that bad neuroscience explanations (as opposed to images) are more convincing than psychological explanations alone. The authors of the replication offered up a plausible explanation for the failure of the brain images to persuade: "Why the disparity, then, between the trivial effects of a brain image and the more marked effects of neuroscience language? ... Perhaps, then, the persuasive influence of the brain image is small when people have already been swayed by the neuroscience language in the article."
Fast-forward to today and a new group of researchers have entered the fray, publishing a paper in the Journal of Cognitive Neuroscience, in which the Seductive Allure of Neuroscience Explanations is tested a little more rigorously. The researchers gave students descriptions of psychological phenomena that were either good explanations or circular explanations. The circular explanations simply restated the claim in a different way rather than providing any actual explanation. The researchers tested to see what happened if superfluous neuroscience information or images of brain scans were added into the mix. Crucially, to control for the neuroscience explanations being more seemingly complex, the researchers also added a "hard science" condition in which superfluous physics or genetics information (for example) was added to the psychological explanation. A superfluous social science condition was also added for good measure.
Like the earlier replication, the brain images alone had little effect, but the superfluous neuroscience explanations were once again found to be more convincing to the students. Crucially they were also found to be more convincing than the superfluous social science and the superfluous hard science explanations. The results also make clear that people are really very bad at spotting circular arguments in science in general — they are just particularly bad at it when the circular argument is glossed under a veneer of neuroscience:
This is a conclusion that I don't find surprising. I'm a firm believer that in some quarters of academia, in the words of Steven Pinker, some scholars "spout obscure verbiage to hide the fact that they have nothing to say. They dress up the trivial and obvious with the trappings of scientific sophistication, hoping to bamboozle their audiences with highfalutin gobbledygook." That superfluous neuroscience seems to be more alluring than other superfluous science makes perfect sense, when it is a subject that is seen as a black box by so many.
This is the point where you are probably expecting me to advocate more and better neuroscience education. But that's absolutely not what I think we need to solve this problem. The key problem here isn't people's knowledge of neuroscience; it's their failure to identify irrational arguments. You certainly could spot the flaws in the arguments made in these studies by becoming an expert on all things brain-related. It would be a far more efficient and likely a far more practical use of your time to develop the critical-thinking skills and skeptical mindset necessary to simply spot the errors of logic. A great starting point in this area is Stuart Sutherland's Irrationality, for a more extensive account see Daniel Kahneman's Thinking, Fast and Slow.
As I so enjoy discussing at length on this blog, the evidence that people seem to fail to apply basic critical thinking to claims made about the brain is all around us. What I find equally concerning and somewhat closely related is the causes and consequences of a culture of "academic bullshitting" in which academics can feel coerced into speaking in a language of pseudoacademia, a language that only differs from everyday English in that it is impenetrable to the naive observer — enclosing an argument in a black box where it cannot be dismantled without great effort. This problem affects all disciplines to some degree, psychology perhaps more than others — as I suggested in a feature I wrote recently with Jon Sutton for The Psychologist. Taking advantage of terminology from neuroscience is just one trick in the toolbox.
Fernandez-Duque D., Evans J., Christian C. & Hodges S.D. (2014). Superfluous neuroscience information makes explanations of psychological phenomena more appealing., Journal of cognitive neuroscience, PMID: http://www.ncbi.nlm.nih.gov/pubmed/25390208
Why mega-eruptions like the ones that covered North America in ash are the least of your worries.
- The supervolcano under Yellowstone produced three massive eruptions over the past few million years.
- Each eruption covered much of what is now the western United States in an ash layer several feet deep.
- The last eruption was 640,000 years ago, but that doesn't mean the next eruption is overdue.
The end of the world as we know it
Panoramic view of Yellowstone National Park
Image: Heinrich Berann for the National Park Service – public domain
Of the many freak ways to shuffle off this mortal coil – lightning strikes, shark bites, falling pianos – here's one you can safely scratch off your worry list: an outbreak of the Yellowstone supervolcano.
As the map below shows, previous eruptions at Yellowstone were so massive that the ash fall covered most of what is now the western United States. A similar event today would not only claim countless lives directly, but also create enough subsidiary disruption to kill off global civilisation as we know it. A relatively recent eruption of the Toba supervolcano in Indonesia may have come close to killing off the human species (see further below).
However, just because a scenario is grim does not mean that it is likely (insert topical political joke here). In this case, the doom mongers claiming an eruption is 'overdue' are wrong. Yellowstone is not a library book or an oil change. Just because the previous mega-eruption happened long ago doesn't mean the next one is imminent.
Ash beds of North America
Ash beds deposited by major volcanic eruptions in North America.
Image: USGS – public domain
This map shows the location of the Yellowstone plateau and the ash beds deposited by its three most recent major outbreaks, plus two other eruptions – one similarly massive, the other the most recent one in North America.
The Huckleberry Ridge eruption occurred 2.1 million years ago. It ejected 2,450 km3 (588 cubic miles) of material, making it the largest known eruption in Yellowstone's history and in fact the largest eruption in North America in the past few million years.
This is the oldest of the three most recent caldera-forming eruptions of the Yellowstone hotspot. It created the Island Park Caldera, which lies partially in Yellowstone National Park, Wyoming and westward into Idaho. Ash from this eruption covered an area from southern California to North Dakota, and southern Idaho to northern Texas.
About 1.3 million years ago, the Mesa Falls eruption ejected 280 km3 (67 cubic miles) of material and created the Henry's Fork Caldera, located in Idaho, west of Yellowstone.
It was the smallest of the three major Yellowstone eruptions, both in terms of material ejected and area covered: 'only' most of present-day Wyoming, Colorado, Kansas and Nebraska, and about half of South Dakota.
The Lava Creek eruption was the most recent major eruption of Yellowstone: about 640,000 years ago. It was the second-largest eruption in North America in the past few million years, creating the Yellowstone Caldera.
It ejected only about 1,000 km3 (240 cubic miles) of material, i.e. less than half of the Huckleberry Ridge eruption. However, its debris is spread out over a significantly wider area: basically, Huckleberry Ridge plus larger slices of both Canada and Mexico, plus most of Texas, Louisiana, Arkansas, and Missouri.
This eruption occurred about 760,000 years ago. It was centered on southern California, where it created the Long Valley Caldera, and spewed out 580 km3 (139 cubic miles) of material. This makes it North America's third-largest eruption of the past few million years.
The material ejected by this eruption is known as the Bishop ash bed, and covers the central and western parts of the Lava Creek ash bed.
Mount St Helens
The eruption of Mount St Helens in 1980 was the deadliest and most destructive volcanic event in U.S. history: it created a mile-wide crater, killed 57 people and created economic damage in the neighborhood of $1 billion.
Yet by Yellowstone standards, it was tiny: Mount St Helens only ejected 0.25 km3 (0.06 cubic miles) of material, most of the ash settling in a relatively narrow band across Washington State and Idaho. By comparison, the Lava Creek eruption left a large swathe of North America in up to two metres of debris.
The difference between quakes and faults
The volume of dense rock equivalent (DRE) ejected by the Huckleberry Ridge event dwarfs all other North American eruptions. It is itself overshadowed by the DRE ejected at the most recent eruption at Toba (present-day Indonesia). This was one of the largest known eruptions ever and a relatively recent one: only 75,000 years ago. It is thought to have caused a global volcanic winter which lasted up to a decade and may be responsible for the bottleneck in human evolution: around that time, the total human population suddenly and drastically plummeted to between 1,000 and 10,000 breeding pairs.
Image: USGS – public domain
So, what are the chances of something that massive happening anytime soon? The aforementioned mongers of doom often claim that major eruptions occur at intervals of 600,000 years and point out that the last one was 640,000 years ago. Except that (a) the first interval was about 200,000 years longer, (b) two intervals is not a lot to base a prediction on, and (c) those intervals don't really mean anything anyway. Not in the case of volcanic eruptions, at least.
Earthquakes can be 'overdue' because the stress on fault lines is built up consistently over long periods, which means quakes can be predicted with a relative degree of accuracy. But this is not how volcanoes behave. They do not accumulate magma at constant rates. And the subterranean pressure that causes the magma to erupt does not follow a schedule.
What's more, previous super-eruptions do not necessarily imply future ones. Scientists are not convinced that there ever will be another big eruption at Yellowstone. Smaller eruptions, however, are much likelier. Since the Lava Creek eruption, there have been about 30 smaller outbreaks at Yellowstone, the last lava flow being about 70,000 years ago.
As for the immediate future (give or take a century): the magma chamber beneath Yellowstone is only 5 percent to 15 percent molten. Most scientists agree that is as un-alarming as it sounds. And that its statistically more relevant to worry about death by lightning, shark, or piano.
Strange Maps #1041
Got a strange map? Let me know at firstname.lastname@example.org.
The potential of CRISPR technology is incredible, but the threats are too serious to ignore.
- CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a revolutionary technology that gives scientists the ability to alter DNA. On the one hand, this tool could mean the elimination of certain diseases. On the other, there are concerns (both ethical and practical) about its misuse and the yet-unknown consequences of such experimentation.
- "The technique could be misused in horrible ways," says counter-terrorism expert Richard A. Clarke. Clarke lists biological weapons as one of the potential threats, "Threats for which we don't have any known antidote." CRISPR co-inventor, biochemist Jennifer Doudna, echos the concern, recounting a nightmare involving the technology, eugenics, and a meeting with Adolf Hitler.
- Should this kind of tool even exist? Do the positives outweigh the potential dangers? How could something like this ever be regulated, and should it be? These questions and more are considered by Doudna, Clarke, evolutionary biologist Richard Dawkins, psychologist Steven Pinker, and physician Siddhartha Mukherjee.
Measuring a person's movements and poses, smart clothes could be used for athletic training, rehabilitation, or health-monitoring.
In recent years there have been exciting breakthroughs in wearable technologies, like smartwatches that can monitor your breathing and blood oxygen levels.
But what about a wearable that can detect how you move as you do a physical activity or play a sport, and could potentially even offer feedback on how to improve your technique?
And, as a major bonus, what if the wearable were something you'd actually already be wearing, like a shirt of a pair of socks?
That's the idea behind a new set of MIT-designed clothing that use special fibers to sense a person's movement via touch. Among other things, the researchers showed that their clothes can actually determine things like if someone is sitting, walking, or doing particular poses.
The group from MIT's Computer Science and Artificial Intelligence Lab (CSAIL) says that their clothes could be used for athletic training and rehabilitation. With patients' permission, they could even help passively monitor the health of residents in assisted-care facilities and determine if, for example, someone has fallen or is unconscious.
The researchers have developed a range of prototypes, from socks and gloves to a full vest. The team's "tactile electronics" use a mix of more typical textile fibers alongside a small amount of custom-made functional fibers that sense pressure from the person wearing the garment.
According to CSAIL graduate student Yiyue Luo, a key advantage of the team's design is that, unlike many existing wearable electronics, theirs can be incorporated into traditional large-scale clothing production. The machine-knitted tactile textiles are soft, stretchable, breathable, and can take a wide range of forms.
"Traditionally it's been hard to develop a mass-production wearable that provides high-accuracy data across a large number of sensors," says Luo, lead author on a new paper about the project that is appearing in this month's edition of Nature Electronics. "When you manufacture lots of sensor arrays, some of them will not work and some of them will work worse than others, so we developed a self-correcting mechanism that uses a self-supervised machine learning algorithm to recognize and adjust when certain sensors in the design are off-base."
The team's clothes have a range of capabilities. Their socks predict motion by looking at how different sequences of tactile footprints correlate to different poses as the user transitions from one pose to another. The full-sized vest can also detect the wearers' pose, activity, and the texture of the contacted surfaces.
The authors imagine a coach using the sensor to analyze people's postures and give suggestions on improvement. It could also be used by an experienced athlete to record their posture so that beginners can learn from them. In the long term, they even imagine that robots could be trained to learn how to do different activities using data from the wearables.
"Imagine robots that are no longer tactilely blind, and that have 'skins' that can provide tactile sensing just like we have as humans," says corresponding author Wan Shou, a postdoc at CSAIL. "Clothing with high-resolution tactile sensing opens up a lot of exciting new application areas for researchers to explore in the years to come."
The paper was co-written by MIT professors Antonio Torralba, Wojciech Matusik, and Tomás Palacios, alongside PhD students Yunzhu Li, Pratyusha Sharma, and Beichen Li; postdoc Kui Wu; and research engineer Michael Foshey.
The work was partially funded by Toyota Research Institute.