The program officers they have listed on their regular NRSA announcements are not necessarily the right ones for you to email.  The right ones, of course, are listed in this totally different page that the NRSA announcement doesn’t point you to.




Things to think about when writing your proposal:



These are the things that helped me think about how to be productive and how to be less stressed about being productive.  I’m not saying they will help you, but sometimes people ask me.

1. Only 20% (and most likely, this is more like 10%, 5%) of what you do every day actually makes a difference to what your successfulness will be next year, or 10 years later.  So most of what you are doing, doesn’t matter.  This is also true of advertising: Only a small % (say, 20%) of the money spent on advertising a product is actually useful at generating purchases of the product.  Businesses spend huge amounts of effort trying to figure out what that 20% is that is bringing in 80% of the consumers.  Maybe one day they’ll figure it out, but you as a single individual have even less chance of figuring out what 20% of what you’re doing today actually matters.

2. Procrastination expands to take up the time available.  If you have 2 weeks to do an essay and ask for an extension, chances are you will spend about the same amount of time on the essay, but just extra time procrastinating about it.  So you might as well schedule doing something else in those 2 weeks, because you sure aren’t losing out on time you would actually have spent working on the essay.

3. Most todo list items that get done are done within about 10 minutes of putting them on the todo list.  So if you get the urge, just do it.  Don’t worry about whether it makes poetic sense for you to wash the dishes at midnight while waiting for the tea kettle to boil.  Who cares?

4. Sometimes, worrying about something is helpful.  Most of the time, it has no positive impact on the task you are worrying about.  So you might as well feel relaxed, even if disaster is looming, if worrying isn’t going to make that disaster any less disastrous or prepare you better to deal with that disaster.  As a corollary though, sometimes worrying does help boost your perseverance at analyzing a situation, and sometimes that is exactly what the situation requires.  Learning to figure out which situations require worrying to improve the situation and which do not, is a life skill that you probably get better at with experience.  You can also hack this if you have an awesome best friend who helps you classify these things when you’re too stressed to do it properly yourself.

permutation models, HCP troubleshooting, establishing better reading habits

catch up on Machine Learning Coursera lectures + Comp Neuro?

f30 specific aims outline

abstract for Biol Psych Due in beginning of Dec:

COVER LETTER revisions..

revise chinese paper maybe.

revise ppt slides/download Work/Keynote

Figure out scheduling/3year plan re: quals, thesis proposal, committees, opportunities for short sojourns at other institutions/industry to diversify experience.  SF?


Talk to boss about hyper connectivity for the chinese paper;  revise current paper to reduce word count 

Geometric analysis?  graph theory manifesto?

finish DH reading summary

meeting john at 2:15

catch up on R and Machine Learning Coursera lectures

revise ppt slides/download Work/Keynote

f30 specific aims outline due Oct 26?

abstract for CNS due

abstract for Biol Psych Due in Nov?:

Read v9 to edit for flow etc.

Look over methods, with focus on writing your sections of the analysis methods

troubleshoot the S simulation issues

random C testing

Geometric analysis?

“Deficits in manual motor speed and coordination are among the most consistently found impairments in schizophrenia.”-

If we knew more about the incidence of “high-risk” individuals actually developing the disease, it would be really cool if somebody did a “prevention” program for at-risk children where they learn to improve motor speed and coordination (juggling?) in order to maybe make those brain circuits less vulnerable.

I’ve privatized a lot of this blog as of today.  For a time, I thought that as long as I didn’t write anything about what I actually am doing in lab, and if I’m “only” summarizing readings of already-published papers I’m reading as I learn about my field, there is no issue, because those published papers are accessible to everybody in the world already.

But, what is unique about my blogging, I suppose, is that I would be choosing certain papers in combination, synthesizing ideas to be applied across papers, and that is different from what a regular schmoe looking at PubMed would see.


I had thought that summarizing already-published papers and writing them out in a more lay-person accessible way would be a public good, since I believe there should be more effort in the scientific community to convey science in plain language, lest an underinformed media engine mis-communicate it to the public.


But the particular combination of papers I have been summarizing could, potentially, lead someone else down the same research questions I have been pursuing silently in tandem.  When I first started summarizing papers and only had a couple of papers summarized, I felt there was no distinct or focused pattern for any reader to pick up upon or scoop me over.  But at this point, there are too many papers and too many ideas. 

In academia, sometimes uniquely brilliant ideas are all you have, to convince an institution or government to choose you as a recipient of limited resources.


I will have to find a different way of promoting science accessibility.

Long economics model paper on joint marriage and career utility functions for young men (young as in under 40): Marriage and Career: The Dynamic Decisions of Young Men

Copy paste of the abstract-
“This paper estimates the returns to career decisions in the marriage market and the returns to marital choices in the labor market. Theoretically, investments in the labor market could affect the chances of receiving a marriage offer, the type of offer, and the probability of getting divorced. Also, marital status could affect one’s outcomes in the labor market, most notably the “marriage premium” in wages. To untangle this simultaneous decision-making process, I develop a dynamic programming model of the joint career and marital decisions of young men between the ages of 16 and 39. The results show that labor market decisions are strongly influenced by their returns in the marriage market. If there were no returns to career choices in the marriage market, men would tend to work less, study less, and choose blue-collar jobs over white-collar jobs. These results suggest that the existing literature underestimates the true returns to human capital investments by ignoring their returns in the marriage market. In addition, the results show that the “marriage premium” is much lower than traditional OLS estimates, and is virtually non-existent for higher wage men. This result suggests that while marriage may make low wage men more serious about their careers, marriage has little effect on high wage men who are already highly motivated.”

The paper goes on to compare the model predictions with actual data, and the model does surprisingly well.  Then, Gould adjusts some parameters in the model, such as making divorce impossible, or making women more variable as marriage candidates (more really good matches and more really bad matches).  The effect on men’s decisions to delay first marriage, remain married, seek additional education, and change careers/working hours is interesting.


But enough about men.  Here, check out the very different wage response functions between men and women:

In general, women respond to increase in wages by working more hours (substitution effect stronger than income effect), whereas men tend to respond to wage increases by working slightly fewer hours (income effect stronger than substitution effect), unless these men live in a very low wage bracket.

The behavior of married women, on the other hand, differs from unmarried women, in that married women are less responsive (elastic) to changes in wage, and require a higher wage to enter the workforce. In a sense, married women aren’t able to focus on their careers to the same degree that they did when they were single (by comparison, if you look at the first paper I linked, blue collar men seem to work more and/or switch to white collar after marriage, while marriage has almost no effect on work sector/amount decisions for high income men).

There are a lot of generalizations from the article that make interpretation tricky.  Do those women observed to work more in response to wage increases arise out of a large hypothetical subset of women who work part time jobs until they can be hired full time?  Are women just being paid less, so they’re behaving more like men in low wage situations?  Having numbers would be helpful.

But supposing we feel like generalizing and saying most women value high wage work more than men do (substitution effect?), and that marriage makes them less sensitive to wage increases (though presumably more sensitive to wage drops? if they’re not entering the work force unless the wage is high?), then can we say that the opportunity cost of not working a high wage job only outweighs the opportunity cost of not being a home-maker for a job paying significantly more than a job that would entice a single woman to work?    If you look at another tab on the same Dickinson website, called Opportunity Cost of Leisure Time, it seems to support the idea that high income, highly educated women incur far greater opportunity costs for not working (and engaging in leisure, or spending a lot of time dating several people, or spending a lot of time at home in a traditional marriage set up).  So divorce is more costly for these women if they value being married, since they’re going to have to spend a lot of time not working to get another marriage.  (Does that mean high income women have to be pickier than everyone else?)  On the other hand, divorce is also costly for women of low income who sign prenups, perhaps, because then they don’t have a means of support?  Does it also mean that divorce is more costly for blue collar men who were married to women who support their men’s careers than it is for high-income men?

All this sort of reminded me of a LARP my friend runs, where the premise is that you are at a dance and you have to find your True Love.  In short, a dating LARP.  Personally, it seemed a little depressing to me, but it also seemed like a ripe situation for applying economic models to figure out optimal matches in the game.  (Whoa… neurixir is a nerd?  No way.)

For instance, you might initially try to match ambitious blue collar men with high income, highly educated women, because they each perhaps find divorce the most costly compared to other marriage-seeking members of their gender, but then you’d realize that the reason why divorce might be extra costly for the blue-collar guy is because of the hypothetical career-supporting wife, and this would be a huge opportunity cost to the high income woman.

If your character is a really insecure man (particularly worried about being divorced and/or not getting career support), maybe your best match would be a woman who can support you in your career until you’re a high-income man, and then (to protect the marriage, economics-style) you should push her into the workforce toward a megastar high-income career of her own, at which point you’ll probably see her less often, but she’ll also be less likely to divorce you—What?

BSing with economics is fun..