Category: conferences

Neurohackademy 2018: A wrap-up

It’s become something of a truism in recent years that scientists in many fields find themselves drowning in data. This is certainly the case in neuroimaging, where even small functional MRI datasets typically consist of several billion observations (e.g., 100,000 points in the brain, each measured at 1,000 distinct timepoints, in each of 20 subjects). Figuring out how to store, manage, analyze, and interpret data on this scale is a monumental challenge–and one that arguably requires a healthy marriage between traditional neuroimaging and neuroscience expertise, and computational skills more commonly found in data science, statistics, or computer science departments.

In an effort to help bridge this gap, Ariel Rokem and I have spent part of our summer each of the last three years organizing a summer institute at the intersection of neuroimaging and data science. The most recent edition of the institute–Neurohackademy 2018–just wrapped up last week, so I thought this would be a good time to write up a summary of the course: what the course is about, who attended and instructed, what everyone did, and what lessons we’ve learned.

What is Neurohackademy?

Neurohackademy started its life in Summer 2016 as the somewhat more modestly-named Neurohackweek–a one-week program for 40 participants modeled on Astrohackweek, a course organized by the eScience Institute in collaboration with data science initiatives at Berkeley and NYU. The course was (and continues to be) held on the University of Washington’s beautiful campus in Seattle, where Ariel is based (I make the trip from Austin, Texas every year–which, as you can imagine, is a terrible sacrifice on my part given the two locales’ respective summer climates). The first two editions were supported by UW’s eScience Institute (and indirectly, by grants from the Moore and Sloan foundations). Thanks to generous support from the National Institute of Mental Health (NIMH), this year the course expanded to two weeks, 60 participants, and over 20 instructors (our funding continues through 2021, so there will be at least 3 more editions).

The overarching goal of the course is to give neuroimaging researchers the scientific computing and data science skills they need in order to get the most out of their data. Over the course of two weeks, we cover a variety of introductory and (occasionally) advanced topics in data science, and demonstrate how they can be productively used in a range of neuroimaging applications. The course is loosely structured into three phases (see the full schedule here): the first few days feature domain-general data science tutorials; the next few days focus on sample neuroimaging applications; and the last few days consist of a full-blown hackathon in which participants pitch potential projects, self-organize into groups, and spend their time collaboratively working on a variety of software, analysis, and documentation projects.

Who attended?

Admission to Neurohackademy 2018 was extremely competitive: we received nearly 400 applications for just 60 spots. This was a very large increase from the previous two years, presumably reflecting the longer duration of the course and/or our increased efforts to publicize it. While we were delighted by the deluge of applications, it also meant we had to be far more selective about admissions than in previous years. The highly interactive nature of the course, coupled with the high per-participant costs (we provide two weeks of accommodations and meals), makes it unlikely that Neurohackademy will grow beyond 60 participants in future editions, despite the clear demand. Our rough sense is that somewhere between half and two-thirds of all applicants were fully qualified and could have easily been admitted, so there’s no question that, for many applicants, blind luck played a large role in determining whether or not they were accepted. I mention this mainly for the benefit of people who applied for the 2018 course and didn’t make it in: don’t take it personally! There’s always next year. (And, for that matter, there are also a number of other related summer schools we encourage people to apply to, including the Methods in Neuroscience at Dartmouth Computational Summer School, Allen Institute Summer Workshop on the Dynamic Brain, Summer School in Computational Sensory-Motor Neuroscience, and many others.)

The 60 participants who ended up joining us came from a diverse range of demographic backgrounds, academic disciplines, and skill levels. Most of our participants were trainees in academic programs (40 graduate students, 12 postdocs), but we also had 2 faculty members, 6 research staff, and 2 medical residents (note that all of these counts include 4 participants who were admitted to the course but declined to, or could not, attend). We had nearly equal numbers of male and female participants (30F, 33M), and 11 participants came from traditionally underrepresented backgrounds. 43 participants were from institutions or organizations based in the United States, with the remainder coming from 14 different countries around the world.

The disciplinary backgrounds and expertise levels of participants are a bit harder to estimate for various reasons, but our sense is that the majority (perhaps two-thirds) of participants received their primary training in non-computational fields (psychology, neuroscience, etc.). This was not necessarily by design–i.e., we didn’t deliberately favor applicants from biomedical fields over applicants from computational fields–and primarily mirrored the properties of the initial applicant pool. We did impose a hard requirement that participants should have at least some prior expertise in both programming and neuroimaging, but subject to that constraint, there was enormous variation in previous experience along both dimensions–something that we see as a desirable feature of the course (more on this below).

We intend to continue to emphasize and encourage diversity at Neurohackademy, and we hope that all of our participants experienced the 2018 edition as a truly inclusive, welcoming event.

Who taught?

We were fortunate to be able to bring together more than 20 instructors with world-class expertise in a diverse range of areas related to neuroimaging and data science. “Instructor” is a fairly loose term at Neurohackademy: we deliberately try to keep the course non-hierarchical, so that for the most part, instructors are just participants who happen to fall on the high-experience tail of the experience distribution. That said, someone does have to teach the tutorials and lectures, and we were lucky to have a stellar cast of experts on hand. Many of the data science tutorials during the first phase of the course were taught by eScience staff and UW faculty kind enough to take time out of their other duties to help teach participants a range of core computing skills: Git and GitHub (Bernease Herman), R (Valentina Staneva and Tara Madhyastha), web development (Anisha Keshavan), and machine learning (Jake Vanderplas), among others.

In addition to the local instructors, we were joined for the tutorial phase by Kirstie Whitaker (Turing Institute), Chris Gorgolewski (Stanford), Satra Ghosh (MIT), and JB Poline (McGill)–all veterans of the course from previous years (Kirstie was a participant at the first edition!). We’re particularly indebted to Kirstie and Chris for their immense help. Kirstie was instrumental in helping a number of participants bridge the (large!) gap between using git privately, and using it to actively collaborate on a public project. As one of the participants elegantly put it:

Chris shouldered a herculean teaching load, covering Docker, software testing, BIDS and BIDS-Apps, and also leading an open science panel. I’m told he even sleeps on occasion.

We were also extremely lucky to have Fernando Perez (Berkeley)–the creator of IPython and leader of the Jupyter team–join us for several days; his presentation on Jupyter (videos: part 1 and part 2) was one of the highlights of the course for me personally, and I heard many other instructors and participants share the same sentiment. Jupyter was a critical part of our course infrastructure (more on that below), so it was fantastic to have Fernando join us and share his insights on the fascinating history of Jupyter, and on reproducible science more generally.

As the course went on, we transitioned from tutorials focused on core data science skills to more traditional lectures focusing on sample applications of data science methods to neuroimaging data. Instructors during this phase of the course included Tor Wager (Colorado), Eva Dyer (Georgia Tech), Gael Varoquaux (INRIA), Tara Madhyastha (UW), Sanmi Koyejo (UIUC), and Nick Cain and Justin Kiggins (Allen Institute for Brain Science). We continued to emphasize hands-on interaction with data; many of the presenters during this phase spent much of their time showing participants how to work with programmatic tools to generate the kinds of results one might find in papers they’ve authored (e.g., Tor Wager and Gael Varoquaux demonstrated tools for neuroimaging data analysis written in Matlab and Python, respectively).

The fact that so many leading experts were willing to take large chunks of time out of their schedule (most of the instructors hung around for several days, facilitating extended interactions with participants) to visit with us at Neurohackademy speaks volumes about the kind of people who make up the neuroimaging data science community. We’re tremendously grateful to these folks for their contributions, and hope they’ll return to teach at future editions of the institute.

What did we cover?

The short answer is: see for yourself! We’ve put most of the slides, code, and videos from the course online, and encourage people to interact with, learn from, and reuse these materials.

Now the long(er) answer. One of the challenges in organizing scientific training courses that focus on technical skill development is that participants almost invariably arrive with a wide range of backgrounds and expertise levels. At Neurohackademy, some of the participants were effectively interchangeable with instructors, while others were relatively new to programming and/or neuroimaging. The large variance in technical skill is a feature of the course, not a bug: while we require all admitted participants to have some prior programming background, we’ve found that having a range of skill levels is an excellent way to make sure that everyone is surrounded by people who they can alternately learn from, help out, and collaborate with.

That said, the wide range of backgrounds does present some organizational challenges: introductory sessions often bore more advanced participants, while advanced sessions tend to frustrate newcomers. To accommodate the range of skill levels, we tried to design the course in a way that benefits as many people as possible (though we don’t pretend to think it worked great for everyone). During the first two days, we featured two tracks of tutorials at most times, with simultaneously-held presentations generally differing in topic and/or difficulty (e.g., Git/GitHub opposite Docker; introduction to Python opposite introduction to R; basic data visualization opposite computer vision).

Throughout Neurohackademy, we deliberately placed heavy emphasis on the Python programming language. We think Python has a lot going for it as a lingua franca of data science and scientific computing. The language is free, performant, relatively easy to learn, and very widely used within the data science, neuroimaging, and software development communities. It also helps that many of our instructors (e.g., Fernando Perez, Jake Vanderplas, and Gael Varoquaux) are major contributors to the scientific Python ecosystem, so there was a very high concentration of local Python expertise to draw on. That said, while most of our instruction was done in Python, we were careful to emphasize that participants were free to work in whatever language(s) they like. We deliberately include tutorials and lectures that featured R, Matlab, or JavaScript, and a number of participant projects (see below) were written partly or entirely in other languages, including R, Matlab, JavaScript, and C.

We’ve also found that the tooling we provide to participants matters–a lot. A robust, common computing platform can spell the difference between endless installation problems that eat into valuable course time, and a nearly seamless experience that participants can dive into right away. At Neurohackademy, we made extensive use of the Jupyter suite of tools for interactive computing. In particular, thanks to Ariel’s heroic efforts (which built on some very helpful docs, similarly heroic efforts by Chris Holdgraf, Yuvi Panda, and Satra Ghosh last year), we were able to conduct a huge portion of our instruction and collaborative hacking using a course-wide Jupyter Hub allocation, deployed via Kubernetes, running on the Google Cloud. This setup allowed Ariel to create a common web-accessible environment for all course participants, so that, at the push of a button, each participant was dropped into a Jupyter Lab environment containing many of the software dependencies, notebooks, and datasets we used throughout the course. While we did run into occasional scaling bottlenecks (usually when an instructor demoed a computationally intensive method, prompting dozens of people to launch the same process in their pods), for the most part, our participants were able to drop into a running JupyterLab instance within seconds and immediately start interactively playing with the code being presented by instructors.

Surprisingly (at least to us), our total Google Cloud computing costs for the entire two-week, 60-participant course came to just $425. Obviously, that number could have easily skyrocketed had we scaled up our allocation dramatically and allowed our participants to execute arbitrarily large jobs (e.g., preprocessing data from all ~1,200 HCP subjects). But we thought the limits we imposed were pretty reasonable, and our experience suggests that not only is Jupyter Hub an excellent platform from a pedagogical standpoint, but it can also be an extremely cost-effective one.

What did we produce?

Had Neurohackademy produced nothing at all besides the tutorials, slides, and videos generated by instructors, I think it’s fair to say that participants would still have come away feeling that they learned a lot (more on that below). But a major focus of the institute was on actively hacking on the brain–or at least, on data related to the brain. To this effect, the last 3.5 days of the course were dedicated exclusively to a full-blown hackathon in which participants pitched potential projects, self-organized into groups, and then spent their time collaboratively working on a variety of software, analysis, and documentation projects. You can find a list of most of the projects on the course projects repository (most link out to additional code or resources).

As one might expect given the large variation in participant experience, project group size, and time investment (some people stuck to one project for all three days, while others moved around), the scope of projects varied widely. From our perspective–and we tried to emphasize this point throughout the hackathon–the important thing was not what participants’ final product looked like, but how much they learned along the way. There’s always a tension between exploitation and exploration at hackathons, with some people choosing to spend most of their time expanding on existing projects using technologies they’re already familiar with, and others deciding to start something completely new, or to try out a new language–and then having to grapple with the attendant learning curve. While some of the projects were based on packages that predated Neurohackademy, most participants ended up working on projects they came up with de novo at the institute, often based on tools or resources they first learned about during the course. I’ll highlight just three projects here that provide a representative cross-section of the range of things people worked on:

1. Peer Herholz and Rita Ludwig created a new BIDS-app called Bidsonym for automated de-identification of neuroimaging data. The app is available from Docker Hub, and features not one, not two, but three different de-identification algorithms. If you want to shave the faces off of your MRI participants with minimal fuss, make friends with Bidsonym.

2. A group of eight participants ambitiously set out to develop a new “O-Factor” metric intended to serve as a relative measure of the openness of articles published in different neuroscience-related journals. The project involved a variety of very different tasks, including scraping (public) data from the PubMed Central API, computing new metrics of code and data sharing, and interactively visualizing the results using a d3 dashboard. While the group was quick to note that their work is preliminary, and has a bunch of current limitations, the results look pretty great–though some disappointment was (facetiously) expressed during the project presentations that the journal Nature is not, as some might have imagined, a safe house where scientific datasets can hide from the prying public.

3. Emily Wood, Rebecca Martin, and Rosa Li worked on tools to facilitate mixed-model analysis of fMRI data using R. Following a talk by Tara Madhyastha  on her Neuropointillist R framework for fMRI data analysis, the group decided to create a new series of fully reproducible Markdown-based tutorials for the package (the original documentation was based on non-public datasets). The group expanded on the existing installation instructions (discovering some problems in the process), created several tutorials and examples, and also ended up patching the neuropointillist code to work around a very heavy dependency (FSL).

You can read more about these 3 projects and 14 others on the project repository, and in some cases, you can even start using the tools right away in your own work. Or you could just click through and stare at some of the lovely images participants produced.

So, how did it go?

It went great!

Admittedly, Ariel and I aren’t exactly impartial parties–we wouldn’t keep doing this if we didn’t think participants get a lot out of it. But our assessment isn’t based just on our personal impressions; we have participants fill out a detailed (and anonymous) survey every year, and go out of our way to encourage additional constructive criticism from the participants (which a majority provide). So I don’t think we’re being hyperbolic when we say that most people who participated in the course had an extremely educational and enjoyable experience. Exhibit A is this set of unsolicited public testimonials, courtesy of twitter:

The organizers and instructors all worked hard to build an event that would bring people together as a collaborative and productive (if temporary) community, and it’s very gratifying to see those goals reflected in participants’ experiences.

Of course, that’s not to say there weren’t things we could do better; there were plenty, and we’ve already made plans to adjust and improve the course next year based on feedback we received. For example, some suggestions we received from multiple participants included adding more ice-breaking activities early on in the course; reducing the intensity of the tutorial/lecture schedule the first week (we went 9 am to 6 pm every day, stopping only for an hourlong lunch and a few short breaks); and adding designated periods for interaction with instructors and other participants. We’ve already made plans to address these (and several other) recommendations in next year’s edition, and expect it to looks slightly different from (and hopefully better than!) Neurohackademy 2018.

Thank you!

I think that’s a reasonable summary of what went on at Neurohackademy 2018. We’re delighted at how the event turned out, and are happy to answer questions (feel free to leave them in the comments below, or to email Ariel and/or me).

We’d like to end by thanking all of the people and organizations who helped make Neurohackademy 2018 a success: NIMH for providing the funding that makes Neurohackademy possible; the eScience Institute and staff for throwing their wholehearted support behind the course (particularly our awesome course coordinator, Rachael Murray); and the many instructors who each generously took several days (and in a few cases, more than a week!) out of their schedule, unpaid, to come to Seattle and share their knowledge with a bunch of enthusiastic strangers. On a personal note, I’d also like to thank Ariel, who did the lion’s share of the actual course directing. I mostly just get to show up in Seattle, teach some stuff, hang out with great people, and write a blog post about it.

Lastly, and above all else, we’d like to thank our participants. It’s a huge source of inspiration and joy to us each year to see what a group of bright, enthusiastic, motivated researchers can achieve when given time, space, and freedom (and, okay, maybe also a large dollop of cloud computing credits). We’re looking forward to at least three more years of collaborative, productive neurohacking!

unconference in Leipzig! no bathroom breaks!

Südfriedhof von Leipzig [HDR]

Many (most?) regular readers of this blog have probably been to at least one academic conference. Some of you even have the misfortune of attending conferences regularly. And a still-smaller fraction of you scholarly deviants might conceivably even enjoy the freakish experience. You know, that whole thing where you get to roam around the streets of some fancy city for a few days seeing old friends, learning about exciting new scientific findings, and completely ignoring the manuscripts and reviews piling up on your desk in your absence. It’s a loathsome, soul-scorching experience. Unfortunately it’s part of the job description for most scientists, so we shoulder the burden without complaining too loudly to the government agencies that force us to go to these things.

This post, thankfully, isn’t about a conference. In fact, it’s about the opposite of a conference, which is… an UNCONFERENCE. An unconference is a social event type of thing that strips away all of the unpleasant features of a regular conference–you know, the fancy dinners, free drinks, and stimulating conversation–and replaces them with a much more authentic academic experience. An authentic experience in which you spend the bulk of your time situated in a 10′ x 10′ room (3 m x 3 m for non-Imperialists) with 10 – 12 other academics, and no one’s allowed to leave the room, eat anything, or take bathroom breaks until someone in the room comes up with a brilliant discovery and wins a Nobel prize. This lasts for 3 days (plus however long it takes for the Nobel to be awarded), and you pay $1200 for the privilege ($1160 if you’re a post-doc or graduate student). Believe me when I tell you that it’s a life-changing experience.

Okay, I exaggerate a bit. Most of those things aren’t true. Here’s one explanation of what an unconference actually is:

An unconference is a participant-driven meeting. The term “unconference” has been applied, or self-applied, to a wide range of gatherings that try to avoid one or more aspects of a conventional conference, such as high fees, sponsored presentations, and top-down organization. For example, in 2006, CNNMoney applied the term to diverse events including Foo Camp, BarCamp, Bloggercon, and Mashup Camp.

So basically, my description was accurate up until the part where I said there were no bathroom breaks.

Anyway, I’m going somewhere with this, I promise. Specifically, I’m going to Leipzig, Germany! In September! And you should come too!

The happy occasion is Brainhack 2012, an unconference organized by the creative minds over at the Neuro Bureau–coordinators of such fine projects as the Brain Art Competition at OHBM (2012 incarnation going on in Beijing right now!) and the admittedly less memorable CNS 2007 Surplus Brain Yard Sale (guess what–turns out selling human brains out of the back of an unmarked van violates all kinds of New York City ordinances!).

Okay, as you can probably tell, I don’t quite have this event promotion thing down yet. So in the interest of ensuring that more than 3 people actually attend this thing, I’ll just shut up now and paste the official description from the Brainhack website:

The Neuro Bureau is proud to announce the 2012 Brainhack, to be held from September 1-4 at the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.

Brainhack 2012 is a unique workshop with the goals of fostering interdisciplinary collaboration and open neuroscience. The structure builds from the concepts of an unconference and a hackathon: The term “unconference” refers to the fact that most of the content will be dynamically created by the participants — a hackathon is an event where participants collaborate intensively on science-related projects.

Participants from all disciplines related to neuroimaging are welcome. Ideal participants span in range from graduate students to professors across any disciplines willing to contribute (e.g., mathematics, computer science, engineering, neuroscience, psychology, psychiatry, neurology, medicine, art, etc“¦). The primary requirement is a desire to work in close collaborations with researchers outside of your specialization in order to address neuroscience questions that are beyond the expertise of a single discipline.

In all seriousness though, I think this will be a blast, and I’m really looking forward to it. I’m contributing the full Neurosynth dataset as one of the resources participants will have access to (more on that in a later post), and I’m excited to see what we collectively come up with. I bet it’ll be at least three times as awesome as the Surplus Brain Yard Sale–though maybe not quite as lucrative.

 

 

p.s. I’ll probably also be in Amsterdam, Paris, and Geneva in late August/early September; if you live in one of these fine places and want to show me around, drop me an email. I’ll buy you lunch! Well, except in Geneva. If you live in Geneva, I won’t buy you lunch, because I can’t afford lunch in Geneva. You’ll buy yourself a nice Swiss lunch made of clockwork and gold, and then maybe I’ll buy you a toothpick.

in which I apologize for my laziness, but not really

I got back from the Cognitive Neuroscience Society meeting last week. I was planning to write a post-CNS wrap-up thing like I did last year and the year before that, but I seem to have misplaced the energy that’s supposed to fuel such an exercise. So instead I’ll just say I had a great time and leave it at that. What happens in Chicago stays in Chicago, etc. etc.

Also, I really appreciate all the people who came up to me at CNS and said nice things about this blog–it’s nice to know that someone actually reads this (puzzling, mind you, because I’m not sure why anyone reads this, but nice nonetheless). A couple of people encouraged me to blog more often, so I’m making an effort to do that, though the most likely outcome will be miserable failure. Either that or I’ll just start pasting random YouTube videos in this space. Like this one:

p.s. on re-reading that, it kind of make it sound like I was swarmed by adoring fans at CNS. To clarify: “all the people” means, like, four people, and the “nice things” were really more like lukewarm “oh yeah, your blog’s not totally awful” sentiments.

p.p.s. I’ve noticed that a lot of my shorter posts take the form of “I was going to write about X, but I’m not actually going to write about X.” I think this is because I’m very lazy but still want partial credit for having good intentions. Which is kind of ridiculous.

CNS 2011: a first-person shorthand account in the manner of Rocky Steps

Friday, April 1

4 pm. Arrive at SFO International on bumpy flight from Denver.

4:45 pm. Approach well-dressed man downtown and open mouth to ask for directions to Hyatt Regency San Francisco. “Sorry,” says well-dressed man, “No change to give.” Back off slowly, swinging bags, beard, and poster tube wildly, mumbling “I’m not a panhandler, I’m a neuroscientist.” Realize that difference between the two may be smaller than initially suspected.

6:30 pm. Hear loud knocking on hotel room door. Open door to find roommate. Say hello to roommate. Realize roommate is extremely drunk from East Coast flight. Offer roommate bag of coffee and orange tic-tacs. Roommate is confused, asks, “are you drunk?” Ignore roommate’s question. “You’re drunk, aren’t you.” Deny roommate’s unsubstantiated accusations. “When you write about this on your blog, you better not try to make it look like I’m the drunk one,” roommate says. Resolve to ignore roommate’s crazy talk for next 4 days.

6:45 pm. Attempt to open window of 10th floor hotel room in order to procure fresh air for face. Window refuses to open. Commence nudging of, screaming at, and bargaining with window. Window still refuses to open. Roommate points out sticker saying window does not open. Ignore sticker, continue berating window. Window still refuses to open, but now has low self-esteem.

8 pm. Have romantic candlelight dinner at expensive french restaurant with roommate. Make jokes all evening about ideal location (San Francisco) for start of new intimate relationship. Suspect roommate is uncomfortable, but persist in faux wooing. Roommate finally turns tables by offering to put out. Experience heightened level of discomfort, but still finish all of steak tartare and order creme brulee. Dessert appetite is immune to off-color humor!

11 pm – 1 am. Grand tour of seedy SF bars with roommate and old grad school friend. New nightlife low: denied entrance to seedy dance club because shoes insufficiently classy. Stupid Teva sandals.

Saturday, April 2

9:30 am. Wake up late. Contemplate running downstairs to check out ongoing special symposium for famous person who does important research. Decide against. Contemplate visiting hotel gym to work off creme brulee from last night. Decide against. Contemplate reading conference program in bed and circling interesting posters to attend. Decide against. Contemplate going back to sleep. Consult with self, make unanimous decision in favor.

1 pm. Have extended lunch meeting with collaborators at Ferry Building to discuss incipient top-secret research project involving diesel generator, overstock beanie babies, and apple core. Already giving away too much!

3:30 pm. Return to hotel. Discover hotel is now swarming with name badges attached to vaguely familiar faces. Hug vaguely familiar faces. Hugs are met with startled cries. Realize that vaguely familiar faces are actually completely unfamiliar faces. Wrong conference: Young Republicans, not Cognitive Neuroscientists. Make beeline for elevator bank, pursued by angry middle-aged men dressed in American flags.

5 pm. Poster session A! The sights! The sounds! The lone free drink at the reception! The wonders of yellow 8-point text on black 6′ x 4′ background! Too hard to pick a favorite thing, not even going to try. Okay, fine: free schwag at the exhibitor stands.

5 pm – 7 pm. Chat with old friends. Have good time catching up. Only non-fictionalized bullet point of entire piece.

8 pm. Dinner at belly dancing restaurant in lower Haight. Great conversation, good food, mediocre dancing. Towards end of night, insist on demonstrating own prowess in fine art of torso shaking; climb on table and gyrate body wildly, alternately singing Oompa-Loompa song and yelling “get in my belly!” at other restaurant patrons. Nobody tips.

12:30 am. Take the last train to Clarksville. Take last N train back to Hyatt Regency hotel.

Sunday, April 3

7 am. Wake up with amazing lack of hangover. Celebrate amazing lack of hangover by running repeated victory laps around 10th floor of Hyatt Regency, Rocky Steps style. Quickly realize initial estimate of hangover absence off by order of magnitude. Revise estimate; collapse in puddle on hotel room floor. Refuse to move until first morning session.

8:15 am. Wander the eight Caltech aisles of morning poster session in search of breakfast. Fascinating stuff, but this early in morning, only value signals of interest are smell and sight of coffee, muffins, and bagels.

10 am. Terrific symposium includes excellent talks about emotion, brain-body communication, and motivation, but favorite moment is still when friend arrives carrying bucket of aspirin.

1 pm. Bump into old grad school friend outside; decide to grab lunch on pier behind Ferry Building. Discuss anterograde amnesia and dating habits of mutual friends. Chicken and tofu cake is delicious. Sun is out, temperature is mild; perfect day to not attend poster sessions.

1:15 – 2 pm. Attend poster session.

2 pm – 5 pm. Presenting poster in 3 hours! Have full-blown panic attack in hotel room. Not about poster, about General Hospital. Why won’t Lulu take Dante’s advice and call support group number for alcoholics’ families?!?! Alcohol is Luke’s problem, Lulu! Call that number!

5 pm. Present world’s most amazing poster to three people. Launch into well-rehearsed speech about importance of work and great glory of sophisticated technical methodology before realizing two out of three people are mistakenly there for coffee and cake, and third person mistook presenter for someone famous. Pause to allow audience to mumble excuses and run to coffee bar. When coast is clear, resume glaring at anyone who dares to traverse poster aisle. Believe strongly in marking one’s territory.

8 pm. Lab dinner at House of Nanking. Food is excellent, despite unreasonably low tablespace-to-floorspace ratio. Conversation revolves around fainting goats, ‘relaxation’ in Thailand, and, occasionally, science.

10 pm. Karaoke at The Mint. Compare performance of CNS attendees with control group of regulars; establish presence of robust negative correlation between years of education and singing ability. Completely wreck voice performing whitest rendition ever of Shaggy’s “Oh Carolina”. Crowd jeers. No, wait, crowd gyrates. In wholesome scientific manner. Crowd is composed entirely of people with low self-monitoring skills; what luck! DJ grimaces through entire song and most of previous and subsequent songs.

2 am. Take cab back to hotel with graduate students and Memory Professor. Memory Professor is drunk; manages to nearly fall out of cab while cab in motion. In-cab conversation revolves around merits of dynamic programming languages. No consensus reached, but civility maintained. Arrival at hotel: all cab inhabitants below professorial rank immediately slip out of cab and head for elevators, leaving Memory Professor to settle bill. In elevator, Graduate Student A suggests that attempt to push Memory Professor out of moving cab was bad idea in view of Graduate Student A’s impending post-doc with Memory Professor. Acknowledge probable wisdom of Graduate Student A’s observation while simultaneously resolving to not adjust own degenerate behavior in the slightest.

2:15 am. Drink at least 24 ounces of water before attaining horizontal position. Fall asleep humming bars of Elliott Smith’s Angeles. Wrong city, but close enough.

Monday, April 4

8 am. Wake up hangover free again! For real this time. No Rocky Steps dance. Shower and brush teeth. Delicately stroke roommate’s cheek (he’ll never know) before heading downstairs for poster session.

8:30 am. Bagels, muffin, coffee. Not necessarily in that order.

9 am – 12 pm. Skip sessions, spend morning in hotel room working. While trying to write next section of grant proposal, experience strange sensation of time looping back on itself, like a snake eating its own tail, but also eating grant proposal at same time. Awake from unexpected nap with ‘Innovation’ section in mouth.

12:30 pm. Skip lunch; for some reason, not very hungry.

1 pm. Visit poster with screaming purple title saying “COME HERE FOR FREE CHOCOLATE.” Am impressed with poster title and poster, but disappointed by free chocolate selection: Dove eggs and purple Hershey’s kisses–worst chocolate in the world! Resolve to show annoyance by disrupting presenter’s attempts to maintain conversation with audience. Quickly knocked out by chocolate eggs thrown by presenter.

5 pm. Wake up in hotel room with headache and no recollection of day’s events. Virus or hangover? Unclear. For some reason, hair smells like chocolate.

7:30 pm. Dinner at Ferry Building with Brain Camp friends. Have now visited Ferry Building at least one hundred times in seventy-two hours. Am now compulsively visiting Ferry Building every fifteen minutes just to feel normal.

9:30 pm. Party at Americano Restaurant & Bar for Young Investigator Award winner. Award comes with $500 and strict instructions to be spent on drinks for total strangers. Strange tradition, but noone complains.

11 pm. Bar is crowded with neuroscientists having great time at Young Investigator’s expense.

11:15 pm. Drink budget runs out.

11:17 pm. Neuroscientists mysteriously vanish.

1 am. Stroll through San Francisco streets in search of drink. Three false alarms, but finally arrive at open pub 10 minutes before last call. Have extended debate with friend over whether hotel room can be called ‘home’. Am decidedly in No camp; ‘home’ is for long-standing attachments, not 4-day hotel hobo runs.

2 am. Walk home.

Tuesday, April 5

9:05 am. Show up 5 minutes late for bagels and muffins. All gone! Experience Apocalypse Now moment on inside, but manage not to show it–except for lone tear. Drown sorrows in Tazo Wild Sweet Orange tea. Tea completely fails to live up to name; experience second, smaller, Apocalypse Now moment. Roommate walks over and asks if everything okay, then gently strokes cheek and brushes away lone tear (he knew!!!).

9:10 – 1 pm. Intermittently visit poster and symposium halls. Not sure why. Must be force of habit learning system.

1:30 pm. Lunch with friends at Thai restaurant near Golden Gate Park. Fill belly up with coconut, noodles, and crab. About to get on table to express gratitude with belly dance, but notice that friends have suddenly disappeared.

2 – 5 pm. Roam around Golden Gate Park and Haight-Ashbury. Stop at Whole Foods for friend to use bathroom. Get chased out of Whole Foods for using bathroom without permission. Very exciting; first time feeling alive on entire trip! Continue down Haight. Discuss socks, ice cream addiction (no such thing), and funding situation in Europe. Turns out it sucks there too.

5:15 pm. Take BART to airport with lab members. Watch San Francisco recede behind train. Sink into slightly melancholic state, but recognize change of scenery is for the best: constitution couldn’t handle more Rocky Steps mornings.

7:55 pm. Suddenly rediscover pronouns as airplane peels away from gate.

8 pm PST – 11:20 MST. The flight’s almost completely empty; I get to stretch out across the entire emergency exit aisle. The sun goes down as we cross the Sierra Nevada; the last of the ice in my cup melts into water somewhere between Provo and Grand Junction. As we start our descent into Denver, the lights come out in force, and I find myself preemptively bored at the thought of the long shuttle ride home. For a moment, I wish I was back in my room at the Hyatt at 8 am–about to run Rocky Steps around the hotel, or head down to the poster hall to find someone to chat with over a bagel and coffee. For some reason, I still feel like I didn’t get quite enough time to hang out with all the people I wanted to see, despite barely sleeping in 4 days. But then sanity returns, and the thought quickly passes.

links and slides from the CNS symposium

After the CNS symposium on building a cumulative cognitive neuroscience, several people I talked to said it was a pity there wasn’t an online repository where all the sites that the speakers discussed could be accessed. I should have thought of that ahead of time, because even if we made one now, no one would ever find it. So, belatedly, the best I can do is put together a list here, where I’m pretty sure no one’s ever going to read it.

Anyway, this is mostly from memory, so I may be forgetting some of the things people talked about, but here’s what I can remember:

Let me know if there’s anything I’m leaving out.

On a related note, several people at the conference asked me for my slides, but I promptly forgot who they were, so here they are.

UPDATED: Russ Poldrack’s slides are now also on the web here.

CNS wrap-up

I’m back from CNS in Montreal (actually, I’m not quite back; I’m in Ottawa for a few days–but close enough). Some thoughts about the experience, in no particular order, and with very little sense:

  • A huge number of registered attendees (basically, everyone from Europe who didn’t leave for Montreal early) couldn’t make it to the meeting because of that evil, evil Icelandic volcano. As a result, large swaths of posterboard were left blank–or would have been left blank, if not for the clever “Holy Smokes! So-and-so can’t be here…” notes taped to them. So that was really too bad; aside from the fact that the Europeans missed out on the meeting, which kind of sucks, there was a fair amount of chaos during the slide and symposium sessions as speakers were randomly shuffled around. I guess it’s a testament to the organizers that the conference went off relatively smoothly despite the loss of a large chunk of the attendance.
  • The symposium I chaired went well, as far as I can tell. Which is to say, no one streaked naked through the hall, no one went grossly over time, the audience hall was full, and the three talks I got to watch from the audience were all great. I think my talk went well too, but it’s harder to say. In theory, you should be able to tell how these things go based on the ratio of positive to negative feedback you get. But since people generally won’t tell you if they thought your talk sucked, you’re usually stuck trying to determine whether people are giving you well-I-didn’t-really-like-it-but-I-don’t-want-you-to-feel-bad compliments, or I-really-liked-it-and-I’m-not-even-lying-to-your-face compliments. In any case, good or bad reception, I think the topic is a really important one, and I’m glad the symposium was well attended.
  • I love Montreal. As far as I’m concerned they could have CNS in Montreal every year and I wouldn’t complain. Well, maybe I’d complain a little. But only about unimportant things like the interior decoration of the hotel lobby.
  • Speaking of which, I liked the Hilton Bonaventure and all, but the place did remind me a lot of a 70s porn set. All it’s missing are some giant ferns in the lobby and a table lined with cocaine next to the elevators. (You can probably tell that my knowledge of 70s porn is based entirely on watching two-thirds of Boogie Nights once). Also, what the hell is on floors 2 through 12 of Place Bonaventure? And how can a hotel have nearly 400 rooms, all on the same (13th) floor!?
  • That Vietnamese place we had lunch at on Tuesday, which apparently just opened up, isn’t going to last long. When someone asks you for “brown rice”, they don’t mean “white rice with some red food dye stirred in”.
  • Apparently, Mike X. Cohen is not only the most productive man in cognitive neuroscience, but also a master of the neuroimaging haiku (admittedly, a niche specialty).
  • Sushi and baklava at a conference reception? Yes please!
  • The MDRS party on Monday night was a lot of fun, though the downstairs room at the bar was double-booked. I’m sure the 20-odd people at salsa dancing night were a bit surprised, and probably not entirely appreciative, when 100 or so drunken neuroscientists collectively stumbled downstairs for a free drink, hung out for fifteen minutes, then disappeared upstairs again. Other than that–and the $8 beers–a good time was had.
  • Turns out that assortment of vegetables that Afghans call an Afghan salad is exactly what Turks call a Turkish salad and Israelis call an Israeli salad. I guess I’m not surprised that everyone in that part of the world uses the same four or five ingredients in their salad, but let’s not all rush to take credit for what is basically some cucumber, tomato, and parsley in a bowl. That aside, dinner was awesome. And I wish there were more cities full of restaurants that let you bring your own wine.

  • The talks and posters were great this year. ALL OF THEM. If I had to pick favorites, I guess I really liked the symposium on perceptual decision-making, and several of the posters in the reward/motivation session on Sunday or Monday afternoon. But really, ALL OF THEM WERE GREAT. So let’s all give ourselves giant gold medals with pictures of brains on them. And then… let’s melt down those medals, sell the gold, and buy some scanners with the money.

green chile muffins and brains in a truck: weekend in albuquerque

I spent the better part of last week in Albuquerque for the Mind Research Network fMRI course. It’s a really well-organized 3-day course, and while it’s geared toward people without much background in fMRI, I found a lot of the lectures really helpful. It’s hard impossible to get everything right when you run an fMRI study; the magnet is very fickle and doesn’t like to do what you ask it to–and that assumes you’re asking it to do the right thing, which is also not so common. So I find I learn something interesting from almost every fMRI talk I attend, even when it’s stuff I thought I already knew.

Of course, since I know very little, there’s also almost always stuff that’s completely new to me. In this case, it was a series of lectures on independent components analysis (ICA) of fMRI data, focusing on Vince Calhoun‘s group’s implementation of ICA in the GIFT toolbox. It’s a beautifully implemented set of tools that offer a really powerful alternative to standard univariate analysis, and I’m pretty sure I’ll be using it regularly from now on. So the ICA lectures alone were worth the price of admission. (In the interest of full disclosure, I should note that my post-doc mentor, Tor Wager, is one of the organizers of the MRN course, and I wasn’t paying the $700 tab out of pocket. But I’m not getting any kickbacks to say nice things about the course, I promise.)

Between the lectures and the green chile corn muffins, I didn’t get to see much of Albuquerque (except from the air, where the urban sprawl makes the city seem much larger than its actual population of 800k people would suggest), so I’ll reserve judgment for another time. But the MRN itself is a pretty spectacular facility. Aside from a 3T Siemens Trio magnet, they also have a 1.5T mobile scanner built into a truck. It’s mostly used to scan inmates in the New Mexico prison system (you’ll probably be surprised to learn that they don’t let hardened criminals out of jail to participate in scientific experiments–so the scanner has to go to jail instead). We got a brief tour of the mobile scanner and it was pretty awesome. Which is to say, it beats the pants off my Honda.

There are also some parts of the course I don’t remember so well. Here’s a (blurry) summary of those parts, courtesy of Alex Shackman:

Scott, Tor, and me in Albuquerque
BlurryScott, BlurryTor, and BlurryTal: The Boulder branch of the lab, Albuquerque 2010 edition

building a cumulative science of human brain function at CNS

Earlier today, I received an email saying that a symposium I submitted for the next CNS meeting was accepted for inclusion in the program. I’m pretty excited about this; I think the topic of the symposium is a really important one, and this will be a great venue to discuss some of the relevant issues. The symposium is titled “Toward a cumulative science of human brain function”, which is a pretty good description of its contents. Actually, I stole borrowed that title from one of the other speakers (Tor Wager); originally, the symposium was going to be called something like “Cognitive Neuroscience would Suck Less if we all Pooled our Findings Together Instead of Each Doing our own Thing.” In hindsight, I think title theft was the right course of action.  Anyway, with the exception of my own talk, which is assured of being perfectly mediocre, the line-up is really stellar; the other speakers are David Van Essen, Tor Wager (my current post-doc advisor), and Russ Poldrack, all of whom do absolutely fantastic research, and give great talks to boot. Here’s the symposium abstract:

This symposium is designed to promote development of a cumulative science of human brain function that advances knowledge through formal synthesis of the rapidly growing functional neuroimaging literature. The first speaker (Tal Yarkoni) will motivate the need for a cumulative approach by highlighting several limitations of individual studies that can only be overcome by synthesizing the results of multiple studies. The second speaker (David Van Essen) will discuss the basic tools required in order to support formal synthesis of multiple studies, focusing particular attention on SumsDB, a massive database of functional neuroimaging data that can support sophisticated search and visualization queries. The third and fourth speakers will discuss two different approaches to combining and filtering results from multiple studies. Tor Wager will review state-of-the-art approaches to meta-analysis of fMRI data, providing empirical examples of the power of meta-analysis to both validate and disconfirm widely held views of brain organization. Russell Poldrack will discuss a novel taxonomic approach that uses collaboratively annotated meta-data to develop formal ontologies of brain function. Collectively, these four complementary talks will familiarize the audience with (a) the importance of adopting cumulative approaches to functional neuroimaging data; (b) currently available tools for accessing and retrieving information from multiple studies; and (c) state-of-the-art techniques for synthesizing the results of different functional neuroimaging studies into an integrated whole.

Anyway, I think it’ll be a really interesting set of talks, so if you’re at CNS next year, and find yourself hanging around at the convention center for half a day (though why you’d want to do that is beyond me, given that the conference is in MONTREAL), please check it out!