“The first rule of intelligence: Don’t talk about your intelligence”

That line is from an article in The Atlantic about how poor people are at self-assessment:

People Don’t Actually Know Themselves Very Well

“The first rule of intelligence: Don’t talk about your intelligence. It’s something you prove, not something you claim. As comedian Patton Oswalt quipped about humor, the only person who goes around saying “I’m funny” is a not-funny person. If you were really funny, you’d just make people laugh.”

To me this kind of thing is pretty obvious, but I guess some people really need to be reminded of it.

Here’s another paragraph with several important reminders, particularly for people who blather about intelligence and cognitive biases:

“This is why people consistently overestimate their intelligence, a pattern that seems to be more pronounced among men than women. It’s also why people overestimate their generosity: It’s a desirable trait. And it’s why people fall victim to my new favorite bias: the I’m-not-biased bias, where people tend to believethey have fewer biases than the average American. But you can’t judge whether you’re biased, because when it comes to yourself, you’re the most biased judge of all. And the more objective people think they are, the more they discriminate, because they don’t realize how vulnerable they are to bias.”

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Are mental disorders the same as brain disorders? Maybe not!

I am currently reading an excellent paper that will be published in Behavioral and Brain Sciences soon. It raises some very important issues with popular conceptions of mental illness.

Brain disorders? Not really… Why network structures block reductionism in psychopathology research

These two figures capture some of the key points:

Here is the abstract:

“In the past decades, reductionism has dominated both research directions and funding policies in clinical psychology and psychiatry. However, the intense search for the biological basis of mental disorders has not resulted in conclusive reductionist explanations of psychopathology. Recently, network models have been proposed as an alternative framework for the analysis of mental disorders, in which mental disorders arise from the causal interplay between symptoms. In this paper, we show that this conceptualization can help understand why reductionist approaches in psychiatry and clinical psychology are on the wrong track. First, symptom networks preclude the identification of a common cause of symptomatology with a neurobiological condition, because in symptom networks there is no such common cause. Second, symptom network relations depend on the content of mental states and as such feature intentionality. Third, the strength of network relations is highly likely to partially depend on cultural and historical contexts as well as external mechanisms in the environment. Taken together, these properties suggest that, if mental disorders are indeed networks of causally related symptoms, reductionist accounts cannot achieve the level of success associated with reductionist disease models in modern medicine. As an alternative strategy, we propose to interpret network structures in terms of D. C. Dennett’s (1987) notion of real patterns, and suggest that, instead of being reducible to a biological basis, mental disorders feature biological and psychological factors that are deeply intertwined in feedback loops. This suggests that neither psychological nor biological levels can claim causal or explanatory priority, and that a holistic research strategy is necessary for progress in the study of mental disorders.”

Behavioral and Brain Sciences is one of the premier journals for “big thinking” in cognitive science and neuroscience, so it’s great to see these ideas there.

Why can’t we perceive cells? Or atoms?

I was asked the following question on Quora:

Why can’t we see, touch, hear and smell on a cellular level? And what happens if we can?

Here’s what I wrote:

Essentially, we perceive the visible world in the way that we do because of our overall size, the shape of our eyes, and the sizes of objects in the world that are relevant to our voluntary behavior.

This question might seem silly, but a closely related question can serve as a springboard for us to think very deeply about physical scale, and how it relates to biological life and to the very concept of a scientific law.


But first lets deal with the basic question.

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The kind of brain training that actually works!

Just saw this on twitter:

Here’s the link to the (thus far unreviewed!) study:

How much does education improve intelligence? A meta-analysis

“… we found consistent evidence for beneficial effects of education on cognitive abilities, of approximately 1 to 5 IQ points for an additional year of education. Moderator analyses indicated that the effects persisted across the lifespan, and were present on all broad categories of cognitive ability studied. Education appears to be the most consistent, robust, and durable method yet to be identified for raising intelligence.”

Why human memory is not a bit like a computer’s

My latest 3QD essay is about the mystery of human memory, and why it is not at all like computer memory. I discuss the quirks of human memory formation and recall, and the concept of “content-addressable memory”.

3quarksdaily: Why human memory is not a bit like a computer’s

Here is an excerpt:

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“Authentic bio-gibberish”

It turns out that one of the 2017 Nobel Laureates is quite a character!

“Jeffrey Hall, a retired professor at Brandeis University, shared the 2017 Nobel Prize in medicine for discoveries elucidating how our internal body clock works. He was honored along with Michael Young and his close collaborator Michael Roshbash. Hall said in an interview from his home in rural Maine that he collaborated with Roshbash because they shared common interests in “sports, rock and roll, beautiful substances and stuff.”

“About half of Hall’s professional career, starting in the 1980s, was spent trying to unravel the mysteries of the biological clock. When he left science some 10 years ago, he was not in such a jolly mood. In a lengthy 2008 interview with the journal Current Biology, he brought up some serious issues with how research funding is allocated and how biases creep into scientific publications.”

I highly recommend watching this video, where he comes up with the term “authentic bio-gibberish” to describe the overly technical jargon used by scientists.