On Academic Talks

I am beginning to suspect that most academics do not want to be heard. This is a paradox, given the number and regularity of academic talks. Indeed, some experts estimate that at least eighty thousand academic talks occur at any given moment, and that some three quarters of these are designed to fill up a time slot during the week which simply must be filled, lest we begin to think about what we used to do before meetings were invented. Most of the remainder are to distract the attendees from distressing events such as grant rejections, increases in conference fees, or foreign armies parachuting onto campus. Academic talks, like most variations of committee work, are becoming a polite form of debauch.

No matter. Regardless of how many talks they give, I still think these students, these professors, these men and women, do not want to be heard. Which is too bad. A talk, for me at least, is a chance to see, hear, and possibly smell the person behind the research. A talk injects red-blooded humanity into an enterprise which would rapidly become sterile without it. Journal articles and book chapters at best radiate a kind of cool elegance. Academic writing only tells me about what they think; I want to know more about what they feel. Where their passions lie. And when someone is talking to me in the same room they can't help but show some of those emotions, giving me a sense of why they are doing what they do in the first place.

Yet some of them would deny me even that pleasure. They talk to their laptop, or to the slides, but not to me. They use small font I can't read; complicated diagrams I can't follow; color schemes and animations that are in bad taste. I would be willing to forgive most of this if I could actually hear what they were saying. Usually I can't.

That has led me to outline six simple ways to improve a talk, any of which can be used profitably:

1. Suspense! If it is to have any worth at all, if it is to function as a stimulant and not a narcotic, a talk needs to have that essential ingredient of any effective story, which is suspense. When hearing a good story, the listener always wants to know what happens next: Who is this character, and what are his motivations? Why is there a note on the table and what does it say? What's the deal with those last two or three pages at the end of a book that are intentionally blank? So it is with good talks.

2. Dress well! A well-dressed speaker is a confident speaker, and a confident speaker is an engaging speaker. When in doubt, follow these "quick tips" on how to dress:

• For Men:
• Right way: Sport coat, open collar dress shirt, loafers, good pair of jeans.
• Wrong way: Graphic tee with the words, "Legalize It."
• For Ladies:
• Right way: Pantsuit
• Wrong way: Jeggings

3. Take notes! To be specific, have a friend take notes about you during your talk. Ideally, this should be a friend who is "brutally honest," also known as "being insufferable and pretentious when pointing out your flaws, and having it hurt even more because, deep down, you know he's right." Some people also refer to this person as "Dan."* No matter how much it hurts, remember that if you want to improve, you need to learn how to take criticism graciously! Also remember that when it's all over you can cut "Dan" out of your life completely.

4. Practice! The speaker putting together his slides at the last minute is guaranteed to embarrass himself and waste the audience's time. Since one of the major goals in life is to not be that one person everybody hates, avoid this by having your slides ready days in advance and doing at least two or three run-throughs ahead of time - preferably, in front of a live audience that includes Dan.

5. Eye contact! Try making eye contact with different people during your talk, but be careful of making eye contact for too little or too long. When in doubt, consult the following chart to make sure you hit the "sweet spot":

• 1-2 seconds: Too little!
• 2-5 seconds: Just right!
• 5-10 seconds: Too much!
• 10-15 seconds: Restraining order!
• More than 15 seconds: This might be normal for, say, a serial killer

6. Lastly, find speakers you admire - and then imitate them. Really. Nothing helps your style more. Note their posture, the cadence of their voice, the way they carry themselves. Some rely more on humor, others have more of a quiet confidence; some tell stories that move the talk along, others tell you the point of the talk right away and never let you lose focus of it. But they all keep you wanting to know what happens next. They keep you in suspense.

Do not mistake this as recommending the substitution of humor for substance, of histrionics for actual thought. (The results are usually awful.) All I ask is that a speaker think about how he would want to be talked to, and then think about how seriously he has to prepare to meet that standard. Only then he begins to realize the gravity of his situation, no matter how small the talk or how low the stakes. In fact the stakes, when he thinks about it, are quite high. A typical one-hour talk attended by twenty of his colleagues can be either satisfyingly filled or grossly wasted, and a few simple calculations reveals a spread of forty attention-hours - a tremendous responsibility - all hinging on one man's decision about whether he actually wants to tell something and be heard. His choice is one between a successful talk and a crashing bore.

Now, I've witnessed more crashing bores than I would like to remember, and I've delivered more than I would like to admit. The fact is that there are far, far too many, and each one inflicts a serious loss on the audience - the loss of an hour they won't get back. (Were we not so complacent about what to expect out of a talk, we might feel more indignation.) Would they have wasted that hour anyway? Maybe. But a bad talk guarantees it.


*I specifically refer here to my labmate.

Society for Neuroscience 2016!

Dear friends,

I will be attending this year's Society for Neuroscience conference, arriving Saturday evening. I have no plans in particular, aside from catching up with my old lab on Sunday evening, and presenting a poster Monday morning about my latest paper in The Journal of Neuroscience. (By the way, the poster is 362.05/LLL21, 8am-12pm Monday; you should all come!) So if you see me walking around the posters with a vacant stare and you want to talk to me about something, feel free to do so, because:

1) I love hearing about any questions or comments you have about the blog, the videos, or anything related to academic life and neuroimaging analysis, as it gives me a fuller, more comprehensive understanding about what graduate students and scientists are going through in this fast-changing era; and

2) I need attention.


See you in San Diego!

-Andy

Updated Functional Connectivity Tutorial using AFNI

As part of a new course in neuroimaging methods at Haskins Laboratories, I've begun updating videos on topics such as functional connectivity, context-dependent correlations, and how to accept bribes as a reviewer. The first topic we've covered is resting-state functional connectivity, a sophisticated-sounding name designed to make the subject think he is doing something of immense scientific importance by lying still and doing nothing, when in reality it's to distract him while we find out how to hell to hook up the experimental laptop.

Aside from its usefulness as a stall tactic, resting-state connectivity can also reveal resting-state networks, or correlations between the signal of distant regions of the brain. This provides clues to how structural connectivity - i.e., white matter connections - interact with the BOLD signal, as well as whether differences in resting-state connectivity is a marker for mental disorders such as Alzheimer's or schizophrenia.

The following video takes you step-by-step through functional connectivity analysis, using an online dataset from openfmri.org. One major change from my previous tutorials is condensing all the information into one long video, and providing time markers for each segment in the "Show More" box. This way the viewer can jump around to the information that they need, without having to keep track of several different videos detailing different steps. I hope it's an improvement, and I would like to get feedback.

I've also posted the lecture on resting-state analysis given at Haskins Laboratories on November 3rd. You won't learn much new here that isn't in the video above, but it does have more information. For most of the lecture you can only see the top of my head bobbing around, but that's OK. Eyes on the slides, not the hair.

Exercises:

1. Set the errts dataset as the underlay, and select "Graph". From the "Opt" menu, select "Write Center." Rename the output 1D file, and use 1dplot to see the timecourse. This can be used as a seed for another connectivity analysis.
2. Other resting state networks include the somatosensory network, the visual network, and the language network. Research one of these networks, determine where the hubs are, and run a resting state analysis on a seed placed in that hub.
3. Run correlations for a group of subjects, convert to z-scores, and do a second-level t-test using uber_ttest.py.
4. Modify the afni_proc.py script to apply 3dRSFC to your data (see Example 10b in afni_proc.py -help)

An Interview with Reviewer #2

Peer review, the cherished academic tradition of having your work criticized by anonymous angry people, is an excellent chance for you to see your prose violated in public. According to one publisher, peer review also helps "increase networking opportunities," in that after having your paper reviewed you will become very, very interested in finding out the names and addresses of all your reviewers.

The reviewing panel consists of two or three reviewers, known by their pseudonyms "Reviewer #1," "Reviewer #2," "Johnny Two-Knuckles," "Icepick Willie," and so on. As everyone knows, the review process tends to be a "good-cop, bad-cop" routine, with Reviewer #1 being nice and lenient - pointing out you shouldn't use Comic Sans font, for instance - while Reviewer #2 is so offended to read your paper that he thinks you should, in so many words, die.

Reviewer #2 is in fact a man named Gary who owns a hardware store in Winnipeg. Although no longer in academia, Gary is still the man who can be counted on, when the chips are down, to write a scathing review of whatever he's reading. Editors scramble to recruit Gary when confronted with a paper they may have to accept, and he is regularly solicited for freelance reviewing. This week we caught up with Gary at his summer home on the banks of Lake Manitoba.

===============

Andy's Brain Blog: How did you become interested in reviewing?

Gary: I took a psychology class in college where we critiqued each other's class projects that were written like scientific articles. Then we anonymously reviewed each other's papers. The professor was impressed that I managed to reject every single paper that I read, and that I also managed to make unnecessary remarks about the author's intelligence and work ethic. At the time I didn't even know what rejecting a paper meant. It just came naturally to me. He put in a good word for me at Elsevier.

ABB: And what happened then?

Gary: Well, I began reviewing everything I read. One time I got so into it that I ended up reviewing the back of a cereal box. It was an accident, but the review was accepted anyway. Two employees at General Mills got fired because of it.

ABB: Wow.

Gary: Yeah. There were grammatical mistakes on there like you wouldn't believe. I couldn't follow the logic of how solving a word game would help Buzz escape from a bank vault full of honey. And the figures were atrocious.

ABB: What was the most memorable review you ever did?

Gary: It's funny you ask, because just last week I returned from the annual Reviewer's Gala in Manhattan. It's a private party for those who have the highest rate of rejecting manuscripts, with awards given for achievements like Most Papers Rejected, Most Brutal Review, Most Irrelevant Comment, and so on. This year I won the prize for Most Hurtful Comment, which went something like: "Writing this paper didn't make you a terrible scientist - you were born one." When the emcee read that line, the audience went wild.

ABB: What is the most ridiculous comment you've ever gotten someone to address?

Gary: I'm not that good at making crazy requests, but one of my fellow reviewers - Carl - can get people to do almost anything. One of his comments was, and I quote: "This is a strong paper, but I think it would be even stronger if, for some reason, all of the authors did the gallon challenge, and uploaded a video of it to YouTube. Now obviously you don't have to do this, but you should, because I am a reviewer."

ABB: They actually did that?

Gary: Yeah. One of them had to go to the hospital. Carl felt pretty bad about that one.

ABB: What advice would you give to a first-time reviewer?

Gary: Rejecting a paper takes a tremendous amount of courage. We've all had the temptation to accept a paper because the science was "solid," or because the logic was "air-tight," or because one of the authors secretly gave us "money." Be firm! I find that I write my best reviews when I'm pissed off about something that has nothing to do with the paper, such as getting something in the mail about taxes.

ABB: You owe a lot of taxes?

Gary: No, I just found out about them, as a concept. They're ridiculous. That's the kind of thing I'm talking about that will get you in the right mood to review a paper.

ABB: Have you ever accepted a paper?

Gary: No.

ABB: Never?

Gary: Never-ever.

ABB: Never even come close?

Gary: Well, there have been a few times. Maybe if one of the authors had the same last name as a celebrity I like, such as Barry Manilow or Kenny G. But other than that, no.

ABB: How long does it take you to write a review?

Gary: Not long. I have a template that I follow, which is a lot like Mad-Libs. For example, "This is an interesting [study / review / prophecy], but I find the [results / figures / theology] unconvincing because I am [an expert / a skeptic / a nun]." Things like that.

ABB: So, how long does it take to get back to the authors? A couple of days? A week?

Gary: No, no, nothing like that. The review takes a couple of days at the most, but you can't let the editor think that you're just blowing through it. I sit on it for at least a few months.

ABB: What are your strategies for writing a review? Is it to always go negative, or what?

Gary: Well, you have to be careful about that. Writing only negative comments raises suspicions that you're taking out your own frustrations and lack of success on the authors instead of addressing their arguments. I aim for a mix of negative comments, nitpicking, and vague sentences. Vague sentences are great, because the authors aren't going to admit that they don't understand what you're saying. Asking an academic to be clear is like asking him to take his clothes off - it's a rude request, almost obscene. So instead they reply as though they understood perfectly what you were saying. It's amazing to see how they try to interpret what is in fact nonsense.

ABB: Can you give an example?

Gary: Sure. Let me see - here's one: "Among the considerations that arise at this stage are the likelihood that the manuscript would seem of considerable interest to those working in the same area of science and the degree to which the results will stimulate new thinking in the field, although we cannot be persuaded of the justifiability, synergy, or translatability of how these results integrate with the conclusions and narrative of Fensterwhacker et al, 2009. Are you professional. Also, you spelled 'their' wrong (should be 'they're': p. 19)."

ABB: I have no idea what that means.

Gary: Exactly.

ABB: How do they respond?

Gary: Usually they begin with something like "We thank the reviewer for their insightful comment," or "We are just thrilled by this excellent suggestion," or "I simply cannot wait to meet this reviewer in person and show him how incredibly, insanely grateful I am, which in no way would include kidnapping his dog." It's interesting how far someone will bend over backwards to address a comment that could've been written by a complete space loon.

ABB: Why do you keep doing this? You're not in academia anymore.

Gary: I try to focus on the big picture. I think that by irritating so many people, everybody will have something in common to talk about. Then they can bond over their shared frustrations and challenges. It makes academia more like a family, except in the sense of being related to or liking or caring about one another.

ABB: Gary, thanks for your time.

Gary: You spelled "your" wrong.

New Website

Readers have complained I haven't updated in a while. Do you know why I haven't updated? Too much Andy's Brain Blog is bad for you. It's like cigarettes, booze, or Nutella. It should be enjoyed in moderation - if at all.

Many of you probably felt that the writing here was slowly petering out. I don't blame you. I've come across sites like that - sites that make me feel as though I'm walking through an abandoned house. What's unsettling is that the writing didn't end; it stopped. That makes me think something terrible happened to the author. Maybe he said everything he had to say; maybe he lost interest; maybe he simply lost inspiration - and couldn't bear to look at those half-stitched monstrosities he began but never finished. I understand. There are many posts that I began to write, but then abandoned - they didn't sound right. You would be surprised how many of these limbless horrors I have buried in my graveyard.

There are two other reasons why I haven't written. One, long periods of absence tend to filter out the fair-weather readers and leave me with only the fanatics. Two, I have been building a new website - a professional website, complete with photos of me doing professional things, such as posing for the camera. I felt that it was time to move; some may disagree. I hate to disappoint them.

Regardless, my posts will continue on the new website; and, to smooth the transition, new writings will be posted to both sites for the next few months. I haven't decided yet what I'll do with this blog; I am too fond of it to simply press "delete" and see it vanish into the electricity. There's history here. Perhaps I'll write something here once in a while with my more unprofessional thoughts. I don't intend to stop anytime soon.

Yet I know that, whatever happens to me, there are others who carry the flag; that there are others who are doing what I do. A few examples come to mind: Mumford Brain Stats; Crash Log; Diffusion Imaging. And that is why this blog, being what it is - a desire to help you understand, to get you excited about neuroimaging; above all, to make you see - will survive even if it die.

fMRI Power Analysis with NeuroPower

One of my biggest peeves is complaints about how power analyses are too hard. I often hear things like "I don't have the time," or "I don't know how to use Matlab," or "I'm being held captive in the MRI control room by a deranged physicist who thinks he is taking orders from the Quench button."

Well, Mr. Whiny-Pants, it's time to stop making excuses - a new tool called NeuroPower lets you do power analyses quickly and easily, right from your web browser. The steps are simple: Upload a result from your pilot study, enter a few parameters - sample size, correction threshold, credit card number - and, if you listen closely, you can hear the electricity of the Internet go booyakasha as it finishes your power analysis. Also, if a few days later you notice some odd charges on your credit card statement, I know nothing about that.

The following video will help you use NeuroPower and will answer all of your questions about power analysis, including:

• What is a power analysis?
• Why should I do a power analysis?
• Why shouldn't I do a power analysis on a full dataset I already collected?
• How much money did you spend at Home Depot to set up the lighting for your videos?
• What's up with the ducks? "Quack cocaine"? Seriously?

All this, and more, now in 1080p. Click the full screen button for the full report.

Getting Started with E-Prime, Chapter 1: Objects

When I first opened up E-Prime, the experiment builder, I was struck by how colorful it was: the thumbnails of flags, hourglasses, computer screens; the blocks of code in shades of blues, greens, and grays; and, especially charming, the outline of a little purple man running, a cute way to represent the "run" button - yet to develop associations of errors, troubleshooting, and failure. Always watching, always waiting, perpetually frozen in running profile, was the little purple man, future inhabitant of future nightmares.

All of these colors led me to believe that E-Prime was a friendly software package for the non-programmer, and that it would definitely not lead to feelings of worthlessness, frustration, and eating an entire Sara Lee cake. However, I was proved wrong when I had to make an experiment more complicated than displaying the words "Hello," "Goodbye," and possibly loading a video file of a dog burping. (This can be found with your E-Prime installation under My Experiments/DogBurp_Demo.es2.) Which is how I came upon the E-Prime documentation.

The documentation for E-Prime is big. I recommend printing it, stapling it together with an industrial-sized Kirkland stapler from Costco, and feeling its heft. Or, if you prefer not to print it, open it up in a word processor and see how the scrollbar shrinks to the size of a tic-tac. In both cases the feeling is the same: This thing is Big. Huge. Biggest thing ever.

And then there are the words - the words! Words like object, procedure, list; context, attribute, trial; dimension, property, sphincter, photosynthesis. For someone with no coding background, this is a strange argot - words familiar in everyday life, but hopelessly confusing when trying to build an experiment. No wonder so many graduate students lose faith, drop out of school, and, instead of pursuing the invigorating career of a researcher spending the majority of his life in front of a computer, they wind up in some dull, unexciting job, such as professional gambler or hitman.

I don't want you to suffer the same fate. This is the start of my own documentation for E-Prime: An alternative to the Youtube videos posted by PST, the company that spawned E-Prime, and its bastard, slack-titted gorgon half-sister, E-Basic. I find those videos well-meaning and sometimes informative, but incomplete. After all, they were made by the programmers of E-Prime - they didn't have to slave away at it, suffer for it, like you and I did! This is my perspective from the other side; recognizing the typical pitfalls awaiting a new programmer and how to avoid them, along with how to make E-Prime submit to your will. The solutions are not always elegant; the coding will infuriate; but, if you watch the videos, you just might get the answers you need. No school this afterlunch, but education certain, with Andy as teacher.

AFNI Install on OS X El Capitan

It's been two and half years (three, if you round up) since I uploaded the first videos about AFNI: How to install it, how to run it, how to make it fulfill all your wildest dreams, which may or may not include taking a dollop of Nutella, drying it in the sun, grinding it into a fine powder, and then snorting it.

I was in Rochester for three weeks in July, lodged at a fly-blown hostel. During the days I would talk with researchers and go to meetings and help design studies, but found myself more often on the benches of Eastman Quadrangle, lazily swatting at mosquitoes and feeling the burst of their rubescent abdomens against my skin. I would sit outside where in the distance you could see a church with large oval stained glass and I would think about nothing in particular. The weather in the mornings was perfect, and I took my exercise down by the Erie canal, up around Cobbs Hill Reservoir, and through neighborhoods I didn't know. In the evenings I would make my way downtown for music at the Eastman School and barbecue on the Genesee. And in those nights I worked, obsessively, on those tutorials and videos whose fate had somehow become strangely entangled with mine. Who knew who was reading, who was watching? There was something of an inverted voyeuristic pleasure in thinking about it.

And now here I am, three years later, promoted to seedy manhood and reminiscing of towns and cities; those icy runs on the country lanes of Northfield in windchills of forty below; going to the piano rooms of the Wexner center to practice Scriabin etudes and my beloved, immortal Waldstein; running around Woodlawn field, each loop zero point four-two miles, running ten, twenty, thirty loops at a time, hoping that enough physical exertion would work off a serious infection of heartsickness; crossing the finish line in Indianapolis with burning lungs and knotted calves, surrounded by the vomit of fellow runners, the clock just a shade under two hours and thirty minutes, feeling something break inside me and knowing it was the end of something.

Such were the days, comrades - and how the days have changed! All that I did back then was well enough for its time; but as new wine requires new bottles, so do new operating systems require new installation instructions; and it has come to my attention that several AFNI users are having issues, both technically and emotionally, with getting AFNI to cooperate with Macintosh's newest OS, El Capitan (which is Spanish for, "The Capitan.")

Sensing that urgent action was needed, I turned on my computer, booted up my web browser, and sat with my posterior firmly planted on my chair until somebody else fixed the problem. Fortunately this was not long in coming, and Pete Molfese over at Crash Log has documented how to do it; however, as I am sensitive to how long it takes to click on links, I have reproduced all of the instructions here in full, along with a helpful video which maybe includes a special effect involving my sports jacket.

Here are the steps:

1. Install XQuartz from xquartz.org (Allows GUIs to run from Unix shells; the "X" symbol that pops up in your dock when you first run AFNI)
2. Install XCode from the Apple Store
3. Install Homebrew (a package manager for Mac) using the following command:
1. For bash: ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
2. For tcsh: curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install | ruby
4. Use homebrew to get the following:
1. The GNU Compiler Collection (GCC) with: brew install gcc --with-all-languages --without-multilib
2. Pyqt, which you'll need for the .py scripts in AFNI: brew install cartr/qt4/pyqt
3. GLib, low-level libraries that take care of the little things under the hood: brew install glib
5. Link libgomp to the correct location using the following:
1. ln -s /usr/local/Cellar/gcc/7.2.0/lib/gcc/5/libgomp.1.dylib /usr/local/lib/libgomp
2. Note that the version is continually being updated, so this command may change; for example, replace 7.2.0 with whatever the latest version happens to be. Check the path to /usr/local/Cellar/gcc to see if the path exists. If you link the wrong path, rerun the command with the correct path and the -sf option.
6. Download the latest AFNI package here, or type the following into your terminal (assuming you are installing version 10.7; replace with whatever version you want to download):  

cd

mkdir abin

curl -O http://afni.nimh.nih.gov/pub/dist/tgz/macosx_10.7_Intel_64.tgz tar -xzf macosx_10.7_Intel_64.tgz 

mv macosx_10.7_Intel_64 abin
rm macosx_10.7_Intel_64.tgz

1. Paste the following commands from the AFNI install webpage into your terminal (for tcsh shell):

echo 'set path = (/usr/local/bin $path $HOME/abin)' >> .cshrc
echo 'setenv DYLD_FALLBACK_LIBRARY_PATH $HOME/abin' >> .cshrc

echo 'setenv PYTHONPATH /usr/local/lib/python2.y/site-packages' >> .cshrc

source .cshrc

rehash

Top Ten Things I Learned in Graduate School (TRIGGER WARNING: Includes Spiro Agnew)

"It is a duty incumbent on upright and creditable men of all ranks who have performed anything noble or praiseworthy to record in their own words the events of their lives. But they should not undertake this honorable task until they are past the age of forty."

-Benvenuto Cellini, opening sentence of his Autobiography (c. 1558)

1. Date within your cohort! Or not. Either way, you'll have a great time! Maybe.
2. If you have more than ten things to say, you can make a longer list.
3. If you rearrange the letters in the name "Spiro Agnew," you can spell "Grow A Penis." Really? Really.
4. Think of teaching a class as a PG-13 movie: to keep the class titillated and interested, you're allowed to make slightly crude references without being explicit; and, if you want, you're entitled to say the f-word ("fuck") once during the semester.
5. When they say, "Don't date your students until the class is over," they mean when the semester is over, not just when classtime is over.
6. Virtually everyone who throws around the word "sustainable" has no idea what they're talking about, unless it's that water situation in California. Things are seriously f-worded over there.
7. If you come into graduate school not knowing how to code, teach yourself. Only after getting frustrated and making no headway, only after you have exhausted every avenue of educating yourself - only then is it acceptable to find someone else to do it for you, and then take credit for it. You gotta at least try!
8. You know you've been doing neuroimaging analysis for a long time when you don't think twice about labeling a directory "anal." Ditto for "GroupAnal."
9. You know you've been in graduate school too long when you can remember the deidentification codes for all of your subjects, but not necessarily the names of all of your children.
10. When you first start a blog in graduate school, everything you write is very proper and low-key, in the fear that you may offend one of your colleagues or a potential employer. Then after a while you loosen up. Then you tighten up again when you're on the job market. Then you get some kind of employment and you loosen up again. And so on.
11. When I first started blogging, I figured that people would take the most interest in essays that I had taken considerable pains over, usually for several days or weeks. Judging from the amount of hits for each post, readers seem to vastly prefer satirical writings about juvenile things such as "the default poop network," and humorous neuroimaging journal titles with double entendres - silly crap I dashed off in a few minutes. Think about that.
12. The whole academic enterprise is more social than anything. It sounds obvious and you will hear it everywhere, but you never appreciate it until you realize that you can't just piss off people arbitrarily and not suffer any consequences somewhere down the line. Likewise, if you are good to people and write them helpful blog posts and make them helpful tutorial videos, they are good to you, usually. Kind of like with everything else in life.
13. If you get a good adviser, do not take that for granted. Make every effort to make that man's life easier by doing your duties, and by not breaking equipment or needlessly stabbing his other graduate students. By "good adviser" I mean someone who is considerate, generous with his time and resources, and clear about what you need to do to get your own career off the ground while giving you enough space to develop on your own. I had such an adviser, and that is a big part of the reason that the past five years of my life have also been the best five years. That, and the fact that I can rent cars on my own now.

Have you finished graduate school and are now in a slightly higher paying but still menial and depressing job, and would like to share your wisdom with the newer generation of young graduate students? Can you rent a car on your own now? Did you try the Spiro Agnew Anagram Challenge (SAAC)? Share your experiences in the comments section!

SPM Smoothing: A Reader Writes

The angry red pustule of the Gaussian normal distribution

I love questions, because questions get answers. One question you may be asking is, "Why are my smoothness estimates in SPM so whack?" To which the obvious response is, "How much whack are we talking about here? Whiggidy-whack, or just the regular kind?" Details matter.

If the former, then the following code snippet may help. In the absence of a gold standard for calculating smoothness estimates, often we have to resort to our own ingenuity and cunning, by which I mean: Copy what other people are doing. One alert reader, Tamara, noticed that the standard SPM function for estimating smoothness, spm_est_smoothness, is so whack that all the other SPM functions want nothing to do with it. Which is kind of the goal of life, when you think about it - to not be that guy everyone else wants to avoid.

In any case, if you are having issues with it, the following code may help. I've also included the rest of the email, just to make you aware that I can and will publish your correspondence without your consent.

Hi Andy, I never figured out why spm_est_smoothness is not working, although other people have had the same issue with getting estimates in the thousands.  Ultimately, I ended up using this simple code to estimate each individual's smoothness, and then averaged across subjects.  Jim Lee posted this on the SPM listserv along with this note:  

The smoothness estimates in SPM.xVol.FWHM are in units of VOXELS, so you need to multiply by the voxel dimensions to get them in mm. Something like this:

load SPM.mat; M = SPM.xVol.M; VOX = sqrt(diag(M(1:3,1:3)'*M(1:3,1:3)))'; FWHM = SPM.xVol.FWHM; FWHMmm= FWHM.*VOX; disp(FWHMmm);

Thanks again for your help!!

Mumford & Stats: Up Your Neuroscience Game

Jeanette Mumford, furious at the lack of accessible tutorials on neuroimaging statistics, has created her own Tumblr to distribute her knowledge to the masses.

I find examples like these heartening; researchers and statisticians providing help to newcomers and veterans of all stripes. Listservs, while useful, often suffer from poorly worded questions, opaque responses, and overspecificity - the issues are individual, and so are the answers, which go together like highly specific shapes of toast in a specialized toaster.* Tutorials like Mumford's are more like pancake batter spread out over a griddle, covering a wide area and seeping into the drip pans of understanding, while being sprinkled with chocolate chips of insight, lightly buttered with good humor, and drizzled with the maple syrup of kindness.

I also find tutorials like these useful because - let's admit it - we're all slightly stupid when it comes to statistics. Have you ever tried explaining it to your dad, and ended up feeling like a fool? Clearly, we need all the help we can get. If you've ever had to doublecheck why, for example, a t-test works the way it does, or brush up on how contrast weights are made, this website is for you. (People who never had to suffer to understand statistics, on the other hand, just like people who don't have any problems writing, are disgusting and should be avoided.)

Jeanette has thirty-two videos covering the basics of statistics and their application to neuroimaging data, a compression of one of her semester-long fMRI data courses which should be required viewing for any neophyte. More recent postings report on developments and concerns in neuroimaging methods, such as collinearity, orthogonalization, nonparametric thresholding, and whether you should date fellow graduate students in your cohort. (I actually haven't read all of the posts that closely, but I'm assuming that something that important is probably in there somewhere.) And, unlike myself, she doesn't make false promises and she posts regularly; you get to stay current on what's hot, what's not, and, possibly, you can begin to make sense of those knotty methods sections. At least you'll begin to make some sense of the gibberish your advisor mutters in your general direction the next time he wants you to do a new analysis on the default pancake network - the network of regions that is activated in response to a contrast of pancakes versus waffles, since they are matched on everything but texture.**

It is efforts such as this that make the universe of neuroimaging, if not less complex, at least more comprehensible, less bewildering; more approachable, less terrifying. And any effort like that deserves its due measure of praise and pancakes.


*It was only after writing this that I realized you put bread into a toaster - toast is what comes out - but I decided to just own it.

**Do not steal this study idea from me.