Saturday soundbites: 6 RBI edition

Is Google the closest thing we have to mind reading?

Mind Hacks points to a great article on blind mathematicians. It turns out that they tend to be talented in geometry.

This week in neuro-nonsense, dieting causes your brain to eat itself.

Neuroskeptic describes a cool new proposed antidepressant that selectively modifies gene expression.

Google and Microsoft are launching new biobliometric tools, according to Nature.

Over at the Frontal Cortex, Jonah Lehrer reviews a study telling us that the Flynn effect is about more than just bringing up the lower part of the IQ distribution through nutrition, de-leading, etc. The top 5% are also getting smarter.

How getting tenure actually does change your life.

Can we predict which soldiers are going to develop PTSD? Should we?

Proposed changes to IRBs

Institutional review boards (IRBs) are committees formed within universities and research organizations. Their job is to review proposed research that uses human subjects, evaluating it for ethical treatment of the human participants. It's an important job given the rather spotty history we have with ethical research (see here, here and here among others).

However, there is a wide range of activities that count as human subjects research, ranging from experimental vaccine trials to personality tests, from political opinions to tests of color vision. Currently, all of this research is broken up into two groups: "regular" human subjects research, which is subject to a full review process and "minimal risk" research, which is subject to a faster review process. Research is defined as minimal risk when it poses no more potential for physical or psychological harm than any other activity in daily life.

My research falls into the minimal risk category. My experiments have been described by several subjects as being "like the world's most boring video game". Outside of being boring, they are not physically harmful, and there is no exposure of deep psychological secrets either. No matter. Each year, researchers like me fill out extensive protocols detailing the types of experiments they propose to do, detailing all possible risks, outlining how subject confidentiality will be maintained, etc. And each participant in a study (each time s/he participates) receives a 3-4 page legal document explaining all of the risks and benefits of the research, which the subject signs to give his consent.

This does seem to be overkill for research which really doesn't pose any sort of physical or psychological threat to participants, and I applaud new efforts to modernize and streamline this process. (Read here for a great summary of the details. Researchers: you can comment until the end of September, the Department of Health and Human Services is soliciting opinions on a bunch of things).

Among the changes are moving minimal risk research from expedited review to no review, and eliminating the need for physical consent forms (a verbal "is this OK with you?" will suffice). These are both good things that would improve my life substantially. However, I believe that standardizing IRB policies across the country would do the most good.

I am currently at my 4th institution and have seen as many IRBs. Two of them have been entirely reasonable, requiring the minimal amount of paperwork and approving minimal risk research across the board. The other two, however, have been less helpful. As Tal Yarkoni points out, "IRB analysts have an incentive to be pedantic (since they rarely lose their jobs if they ask for too much detail, but could be liable if they give too much leeway and something bad happens)". However, I think it goes beyond this. In some sense, IRBs feel they are productive by showing that they have stopped or delayed some proportion of the research that crosses their desks.

I have had an IRB reject my protocol because they didn't like my margin size, didn't like my font size, and didn't like the cute cartoon I put on my recruitment posters (apparently cartoons are coercive). I've had an IRB send an electrician into the lab with a volt meter to make sure my computer monitor wouldn't electrocute anyone. My last institution did not approve an experiment that was a cornerstone of my fellowship proposal as it required data to be gathered online (this is very common in my field) and I couldn't guarantee that someone outside of my approved age range (18-50) was doing my experiment. Under the current rules, I couldn't just use my collaborator's IRB approval as all institutions need to approve a protocol. However, another of the proposed changes will require only one approval.

I'm very optimistic about these proposed changes... let's hope they happen!

Soundbites: relocation blues edition

The ever-informative Andrew Gelman asks how we statistically evaluate some of the rather improbable claims from recent studies.

Speaking of improbable claims, Ed Yong deconstructs the latest on Google ruining your mind.

Peter Kramer defends antidepressants in the New York Times.

Neuroethics at the Core has a nice discussion of the issues involved in pharmacologically enhancing soldiers.

The New York Times education section has a special issue on grad school for all of your bitter academic ranting. I especially like these infographics.

Managing scholarly reading

Reading, after a certain age, diverts the mind too much from its creative pursuits. Any man who reads too much and uses his own brain too little falls into lazy habits of thinking. —ALBERT EINSTEIN

How much literature should one read as an academic? Of course, the answer will vary by field, but even within my own field, I find little consensus as to the "right" amount of reading to do.

It is true that no one can read everything that is published, even in a single field such as cognitive science, while maintaining one's own productivity. In my Google reader, I subscribe to the RSS of 26 journals, and from these, I get an average of 37 articles per day. However, in an average day, I feel like I should pay attention to 5 of these. If I were to closely read all of these, I would run out of time to create new experiments, analyze data and write my own papers.

It turns out that in an average day, I'll read one of these papers and "tag" the other 4 as things I should read. But this strategy gets out of control quickly. In May, I went to a conference, didn't check my  reader for a couple of days and came back to over 500 journal articles, or around 35 that I felt deserved to be read. I have over 1300 items tagged "to read" in my Zotero library. At my current rate of reading, it would take me over 3.5 years to get through the backlog even if I didn't add a single article to the queue.

So, how to stay informed in an age of information overload? It seems that there are a few strategies:

1. Read for, rather than read to. In other words, read when knowledge on a particular topic is to be used in a paper or grant review, but don't read anything without a specific purpose for that information. According to proponents of this method, information obtained when reading-for-reading's-take will be lost anyway, leading to re-reading when one needs the information.

This method vastly decreases the overwhelming nature of the information, and makes info acquisition efficient. However, it is not always practical for science: if you're only reading for your own productivity, you're going to miss critical papers, and at worst, are going to be doing experiments that were already done.

2. Social "reading", augmented by abstract skimming. In this method, one does not spend time reading, but spends time going to as many talks and conferences as possible, learning about literature by using the knowledge of one's colleagues. This method seems to work best in crowded fields. The more unique your research program, the more you'll have to do your own reading. And all of this traveling is time and money consuming.

3.  Don't worry about checking through many journals, but set alerts for the specific topics. My favorite is PubCrawler, suggested by Neuroskeptic. Works well when my key words and the authors' key words coincide, but I seem to have set too many topics and I get both too many "misses" and "false alarms".

How do you keep up with literature?

Is college worth it for everyone?

In yesterday's New York Times, David Leonhardt opined that we ought to send as many young adults to college as possible. His economic arguments ran as follows:

- The income delta between college grads and non-college grads has increased from 40% to over 80% in the last three decades.
- If one calculates a return on investment for a college education, it is 15%, higher than stocks, and certainly higher than current real-estate.

Unfortunately, he completely glosses over the problem of cost. He writes:

"First, many colleges are not very expensive, once financial aid is taken into account. Average net tuition and fees at public four-year colleges this past year were only about $2,000 (though Congress may soon cut federal financial aid)."

As if the eminent cutting of federal financial aid can be reduced to a parenthetical! The reality is that college prices have increased over 130% since 1988 while median family incomes have remained stagnant. This situation makes college possible only through the amassing of large amounts of student debt. Indeed, for the first time in this country, student loan debt has surpassed credit card debt. Taking on this kind of debt in this lackluster economy is problematic. Furthermore unlike mortgages, student loan debt does not go away with bankruptcy, loading some thinkers to forecast education as the next bubble.

Leonhardt also unhelpfully compares the arguments against universal college education to the arguments against universal high school education from over half a century ago. This would be fine if we were in the position to make four years of university education part of public education. However, calling for all families to take on this debt seems irresponsible and elitist.

Soundbites: misplaced adrenaline edition

New vaccine-autism paper expertly dismembered by Neuroskeptic.

Plastic surgery to prevent recidivism?

Colleges are not as meritocratic as they would lead us to believe.

Neurophilosophy on human echolocation in the blind.

During the Singularity, will there be corporate sponsors for your thoughts? Asked by Sue Halpern for the New York Review of Books.

Brain Ethics argues that "neuromarketing", when not used for marketing, might be a good thing.

Review of David Eagleman's new book at Nature.

I highly recommend this New York Times article on the consciousness of conjoined twins.

Scientific American interviews Chris Chabris on how to test the "10,000 hours" idea.

On a light ending, I can't tell whether this is the coolest or weirdest thing ever.

Edison, Gretsky and the gritty side of success

"If I find 10,000 ways something won’t work, I haven’t failed. I am not discouraged, because every wrong attempt discarded is another step forward." Thomas Edison.

Fundamentally different views of achievement can be seen in the well-known debates between Nikola Tesla and Thomas Edison. Tesla, the theoretician, conducted experiments only after careful consideration and calculation while Edison's approach was an "empirical dragnet" according to Tesla.

Similarly, hockey great Wayne Gretsky has stated "You miss 100% of the shots you don't take".

Is the key to success to multiply your rate of failure?

Of course, ability matters. But how much does perseverance matter? In other words, how much difference in success will be seen for two people of equal ability but unequal perseverance?

In success psychology, one can measure "grit", defined as "perseverance and passion for long-term goals". Duckworth and colleagues have created a self-report measure for this trait, known as the Grit Scale. In this survey, items such as "I have achieved a goal that took years of work" correlate with high grit, while items such as "New ideas and new projects sometimes distract me from previous ones" are negatively correlated with grit.

Here are some interesting things they found about grit:
* Highly educated people have more grit than people with less education.

* When controlling for age, grit increases with age.

* Grit is related to the Big Five Personality trait of Conscientiousness.

* When examining undergraduates at the University of Pennsylvania, students with more grit had a higher GPA, but students with lower SAT scores had higher grit. This could suggest that getting to an elite university can be through ability (reflected in SAT scores) or grit.

* Although grit was unrelated to rankings of West Point cadets, grit was the best predictor of whether cadets would complete summer training.

* Students with higher grit were more likely to make it to the final round of the National Spelling Bee, due to putting in more time to studying.

I've been thinking a lot about grit in the last day of trying to win a scholarship (as I wrote about yesterday). The video I made is about grit, but the promotion I'm doing for it is putting me way out of my comfort zone as a shy person. I may fail, but I'll be back. :)

A reverse decline effect for RSVP?

Last week I attended the Vision Sciences Society annual meeting in Florida. Good times, good science. Although I don't use this blog for talking about my own research or field, I was struck by a talk from Molly Potter that was germane to this blog. (In full disclosure, Molly was the chair of my PhD committee, a personal hero of mine, and a large influence on my thinking).

In the 1960s and 1970s, Prof. Potter sought to study the temporal limits of complex visual processing. As our eyes move multiple times per second, the visual input we receive is constantly changing. To emulate this process, she developed the technique of rapid serial visual presentation (RSVP). In this method, one presents a participant with a stream of photographs, one after another, for a very brief time (half a second or less per picture). She found that when you give a participant a target scene (either by showing the picture or describing the picture), the participant can detect the presence or absence of this picture even when the pictures are presented for a tenth of a second each! Below is an example of one of these displays. Try to find a picture of the Dalai Lama wearing a cowboy hat.

Pretty cool, huh?

In her new research, Prof. Potter was trying to determine how much faster the visual system can be pushed by presenting RSVP steams that were only 50, 33 or even 13ms per picture. Here is a graph adapted from my notes at her talk:

Even at 13 ms per image, participants were performing at about 60% correct, and by 80ms per image, they were nearly perfect.

"Huh" I thought to myself during the talk, "this is really high performance. It seems even higher than performances for longer presentation times that were in the original papers".

So back in Boston, I looked up the original findings. Here is one of the graphs from 1975:

So, participants in 1975 needed 125ms per picture to reach the same level or performance that modern participants can perform with 33ms/picture.

I've complained a bit here about the so-called "decline effect", the phenomenon of effect sizes in research declining over time. The increased performance for RSVP displays can be seen as a kind of reverse decline effect.


In 1975, the only way to present pictures at a rapid rate was through the use of a tachistoscope. Today's research is done on computer monitors. Although the temporal properties of CRT monitors are well-worked out, perhaps these two methods are not fully equivalent. On the other hand, compared to 1975, our lives are full of fast movie-cuts, video games and other rapid stimuli, and so the new generation of participants may have faster visual systems.

Growing PhDs "like mushrooms"

If you have been following this blog, it comes as no surprise that I frequently worry about the state of the university system. I believe there are structural problems in the system that are a disservice to students (both at the undergraduate and graduate levels) as well as staff (particularly adjuncts and non-tenure track faculty, but also to junior tenure-track professors as well).

Recently, Nature published a series of opinion articles on the over-production of PhDs in the sciences. We are producing too many people who are apprenticed in a career path that can accommodate only a fraction of them.

As a result, we are spending longer in graduate school and in our postdocs, but the number of people passing through the needle eye to professorship is shrinking as tenure-track jobs get replaced with temporary and adjunct positions. In 1973, 55% of US biology PhDs secured tenure-track positions within six years of completing their degrees, and only 2% were in a postdoc or other untenured academic position. By 2006, only 15% were in tenured positions six years after graduating, with 18% un-tenured. This largely fits with my perception: it has been seven years since I began graduate school, and considering my incoming class,  we are evenly spread across remaining in school, having a post-doc and getting a job in industry. Not one of us currently has a tenure-track faculty position. Something must be very broken in the system for prospects to be this bleak for graduates of a top-five department.

So why doesn't the market change such that supply meets demand? Essentially, it's that the system runs on cheap graduate and postdoctoral labor. "Yet many academics are reluctant to rock the boat as long as they are rewarded with grants (which pay for cheap PhD students) and publications (produced by their cheap PhD students). So are universities, which often receive government subsidies to fill their PhD spots." In fact, faculty members who are reluctant to perpetuate this cycle are punished in grant review, writing in costs for a research scientist at $80,000 per year when others have the same work done by a postdoc at $40,000 per year.

So, how did we get here? Part of the issue has to be that more people are going to college than ever before and the university system does not properly scale to the demand. In the US in 1970, only 11% of people over the age of 25 had a bachelor's degree, but this number had climbed to 28% by 2009. So more graduate students, postdocs and adjuncts are being used to teach the courses to accommodate all of these new students. While some claim that it is just too expensive to have tenure-track faculty teaching all of these courses, one must also consider the recent trend towards massive salaries for university professors.

Actually, if anyone could explain university economics to me, I'd be grateful.

And where do we go from here? Personally, I love the suggestions made by William Deresiewicz in this fantastic article. Particularly, "The answer is to hire more professors: real ones, not academic lettuce-pickers."

(Just) soundbites

Touching article on the end of life and career of an ALS researcher who is succumbing to the disease of his own expertise.

A really great article on irrational affection for sports teams, written by someone who clearly understands that all human drama can be explained in terms of the 2004 Red Sox.

Speaking of sports, some insight into elite athletes who push beyond the limits of their bodies. On the less fatal side of things, dissociating oneself from current discomfort can be an effective strategy for top performance.

We have so much data! Can't we do something more interesting with it than get people to click on ads?

Over at the Statistics Forum, curious close replications are discussed.

Gender and scientific success

I didn't want to write this post.  I really don't want to touch this with a ten foot pole. What follows is messy and complicated and guaranteed to make everyone mad at least some of the time. (Ask Larry Summers).

We need a sane approach to how we deal with gender in the sciences.

Women are making measurable representation gains in the sciences. This is an undisputed good. Everyone benefits when the right people are doing the right job. However, despite the fact that the majority of bachelor's degrees are now being awarded to women, women only make up about 20% of professorships in math and the sciences. Why?

The three basic alternative answers: 1.) women tend not to choose careers in math or science (either willingly or due to life/family circumstances); 2.) women are barred from achievement in math and science through acts of willful discrimination; or 3.) women do not have the same aptitude for achievement in math and sciences as men.

This is a difficult issue to study as people's careers cannot be manipulated experimentally, and we are left to mostly correlational evidence. An exception are CV studies where identical CVs are given to judges with either a woman or man's name on the top. Judges are asked to determine the competence of the candidates. These studies typically find that the "male candidates" are judged to be more competent than the "female candidates". As no objective differences exist between them, this is a measure of sex discrimination.

Reviewing the correlational evidence for gender discrimination in the sciences, Ceci and Williams find that when examining researchers with equal access to resources (lab space, teaching loads, etc), that no productivity difference is found between male and female scientists. Female scientists are, on average, less likely to have as many resources as male scientists as they are more likely to take positions with heavier teaching loads. How to reconcile the CV studies showing discrimination and the correlational evidence suggesting none? In an excellent analysis of the Ceci and Williams paper, Alison Gopnik asserts a possible hypothesis: "Women, knowing that they are subject to discrimination, may work twice as hard to produce high-quality grants and papers, so that the high quality offsets the influence of discrimination".

It's possible. But Gopnik also admits that it is also possible that policy changes could be responsible. In other words, that affirmative action-style policies that give women advantages could counteract the subconscious gender discrimination seen in the CV studies.

There's a darker side to these policies, though. Some worry about the discounting of a female professor's abilities, assuming she rose to the position via policy rather than talent. Furthermore, some policies designed to given women more voice actually end up give them more work - if a certain number of women need to be on a committee, then female professors are doing more service work than their male counterparts.

And then there's the matter of why female faculty find themselves in low-resource situations to begin with. Stated eloquently by Gopnik, "the conflict between female fertility and the typical tenure process is one important factor in women's access to resources. You could say that universities don't discriminate against women, they just discriminate against people whose fertility declines rapidly after 35."

And well-meaning policies also interact with the fertility issue in insidious ways. For example, many universities offer to "pause" the tenure clock for a year for a faculty member who gives birth before tenure. Sounds great, right?  It could be, except that there is a tremendous amount of pressure to not take this credit for fear of seeming weak. This is especially true in departments that have faculty members who have already chosen not to take the time.

So... we have unconscious discrimination, conscious policies to counter said unconscious discrimination, conscious and unconscious backlash against the policies, and a structural problem for female fertility. In other words, it's a complicated picture and I don't know what the answer is. I do, however agree with Shankar Vedantam's assessment: "It is true that fewer women than men break into science and engineering careers today because they do not choose such careers. What isn't true is that those choices are truly "free.""

Sunday soundbites

The New York Times on artificial intelligence.

A surprisingly large number of people taking anti-depressants have not received any psychiatric diagnosis.

Problems for lie detection: the more you lie, the better you get at it.

They were funded for that?! The Intelligent Animal describes a study in "dog telepathy".

Here's an uplifting article on defining death for the purposes of organ donation.

How to get tenure at a major research university.

Mind Hacks has a history of psychology through objects.

Sunday soundbites: out like a lamb

Pretty devastating article in Rolling Stone on the military's use of "psychological operations" to "win the hearts and minds" of US senators.

Barking up the Wrong Tree reports on a first placebo-controlled clinical trial of nootropic dietary supplements.

Speaking of nootropics, a discussion of the ethical issues presented by the film Limitless.

Scientific American examines a new study on free will.

Neurophilosophy discusses study showing gut bacteria can alter cognitive function.

This is a great new tool for publishing data that are otherwise unpublishable, such as null results.

Another skirmish in the tenure wars.

The Invisible Gorilla shares a great Richard Feynman video discussing science with a chess analogy.

Sunday soundbites: wall of sound edition

David Rumelhart has left the building.

Owsley Stanley has left the building.

In memory, why don't you build your own set of hallucination goggles?

This is a great radio program on the uncertainty of fingerprint analysis.

The Guardian on the (lost?) art of memorization.

Barking up the Wrong Tree tries to find the most typical person.

Why do scientists, artists and criminals have the same age-range of peak productivity?

Jonah Lehrer on grit.

The value of teaching at the university level

The Neuroskeptic has a particularly insightful post on the uncomfortable disconnect between how universities, academics and politicians see the role of teaching. I've written occasionally on some of the broken aspects of the academy, and I think Neuroskeptic's piece adds a couple of crucial thoughts to the discussion:

"And academics have no incentive to teach well and, in most cases, no incentive to make sure that their university has a reputation for good teaching."

(Emphasis mine.)
Indeed, if anything, being involved in excellent teaching is viewed as the "kiss of death" for one's tenure at many American research universities. And, as Neuroskeptic points out, the nomadic lives of young researchers prevents strong ties to a particular university:

"Until you get to the level of tenured professor, if ever, you cannot assume that you'll be working in the same place for very long. Many academics will go to one university for their undergraduate degrees, another for their masters, another for their doctorate, and then another two or three as junior faculty member before they "settle down" - and the majority don't make it that far."

Perhaps the solution is to tenure faculty more often and earlier.  Imagine young, energetic, passionate academics, unafraid to teach with excellence and filled with a sense of place in their institution. Maybe this is what we need for excellent undergraduate education.