see me flub my powerpoint slides on NIF tv!

 

UPDATE: the webcast is now archived here for posterity.

This is kind of late notice and probably of interest to few people, but I’m giving the NIF webinar tomorrow (or today, depending on your time zone–either way, we’re talking about November 1st). I’ll be talking about Neurosynth, and focusing in particular on the methods and data, since that’s what NIF (which stands for Neuroscience Information Framework) is all about. Assuming all goes well, the webinar should start at 11 am PST. But since I haven’t done a webcast of any kind before, and have a surprising knack for breaking audiovisual equipment at a distance, all may not go well. Which I suppose could make for a more interesting presentation. In any case, here’s the abstract:

The explosive growth of the human neuroimaging literature has led to major advances in understanding of human brain function, but has also made aggregation and synthesis of neuroimaging findings increasingly difficult. In this webinar, I will describe a highly automated brain mapping framework called NeuroSynth that uses text mining, meta-analysis and machine learning techniques to generate a large database of mappings between neural and cognitive states. The NeuroSynth framework can be used to automatically conduct large-scale, high-quality neuroimaging meta-analyses, address long-standing inferential problems in the neuroimaging literature (e.g., how to infer cognitive states from distributed activity patterns), and support accurate ‘decoding’ of broad cognitive states from brain activity in both entire studies and individual human subjects. This webinar will focus on (a) the methods used to extract the data, (b) the structure of the resulting (publicly available) datasets, and (c) some major limitations of the current implementation. If time allows, I’ll also provide a walk-through of the associated web interface (http://neurosynth.org) and will provide concrete examples of some potential applications of the framework.

There’s some more info (including details about how to connect, which might be important) here. And now I’m off to prepare my slides. And script some evasive and totally non-committal answers to deploy in case of difficult questions from the peanut gallery respected audience.

Kahneman on happiness

The latest TED talk is an instant favorite of mine. Daniel Kahneman talks about the striking differences in the way we experience versus remember events:

It’s an entertaining and profoundly insightful 20-minute talk, and worth watching even if you think you’ve heard these ideas before.

The fundamental problem Kahneman discusses is that we all experience our lives on a moment-by-moment basis, and yet we make decisions based on our memories of the past. Unfortunately, it turns out that the experiencing self and the remembering self don’t necessarily agree about what things make us happy, and so we often end up in situations where we voluntarily make choices that actually substantially reduce our experienced utility. I won’t give away the examples Kahneman talks about, other than to say that they beautifully illustrate the relevance of psychology (or at least some branches of psychology) to the real-world decisions we all make–both the trival, day-to-day variety, and the rarer, life-or-death kind.

As an aside, Kahneman gave a talk at Brain Camp (or, officially, the annual Summer Institute in Cognitive Neuroscience, which may now be defunct–or perhaps only on hiatus?) the year I attended. There were a lot of great talks that year, but Kahneman’s really stood out for me, despite the fact that he hardly talked about research at all. It was more of a meditation on the scientific method–how to go about building and testing new theories. You don’t often hear a Nobel Prize winner tell an audience that the work that won the Nobel Prize was completely wrong, but that’s essentially what Kahneman claimed. Of course, his point wasn’t that Prospect Theory was useless, but rather, that many of the holes and limitations of the theory that people have gleefully pointed out over the last three decades were already well-recognized at the time the original findings were published. Kahneman and Tversky’s goal wasn’t to produce a perfect description or explanation of the mechanisms underlying human decision-making, but rather, an approximation that made certain important facts about human decision-making clear (e.g., the fact that people simply don’t follow the theory of Expected Utility), and opened the door to entirely new avenues of research. Kahneman seemed to think that ultimately what we really want isn’t a protracted series of incremental updates to Prospect Theory, but a more radical paradigm shift, and that in that sense, clinging to Prospect Theory might now actually be impeding progress.

You might think that’s a pretty pessimistic message–“hey, you can win a Nobel Prize for being completely wrong!”–but it really wasn’t; I actually found it quite uplifting (if Daniel Kahneman feels comfortable being mostly wrong about his ideas, why should the rest of us get attached to ours?). At least, that’s the way I remember it now. But that talk was nearly three years ago, you see, so my actual experience at the time may have been quite different. Turns out you can’t really trust my remembering self; it’ll tell you anything it thinks it wants me to hear.