Filtering of the boating party.

Renoir's "Luncheon of the Boating Party" offers a good example of compelling visual art. The woman near the center is a particular focal point, and one which evokes perhaps the strongest responses in many viewers. I've been playing with visual frequency filters for my research recently, and have found that her face produces a similar effect to that observed in the smile of the Mona Lisa by Margaret Livingstone in her work "Vision and Art: The Biology of Seeing".

If you look at versions of the woman filtered for high:


and low frequencies:


the high frequency images appeared to us to show a much happier face looking toward the other revelers at the luncheon, with the low frequency ones evoking a wistful or even sad individual looking straight out from the painting at the viewer.

Now, we're always building expectations. Even over the short period of time while we fixate our eyes on an object in the periphery. We expect to see a more detailed version of whatever we saw out of the corner of our eye just a few milliseconds before. In the case of this painting a viewer looking anywhere around the edges (i.e. at the other people partaking of the luncheon), the incongruous image of a sad person staring wistfully straight out of the image while surrounded by a jovial social scene would be enough to draw the eye. At the end of the saccade to the center of the painting, their brains would expect to encounter a detailed version of the sad woman previously seen in a low-frequency filtered way out of the corner of their eye.

These expectations would be violated however. Not hugely or strongly enough to really cause a double-take, but just a moment of uncertainty. The woman they are now looking at is smiling and appears to be far more engaged in the goings on than an observer would have previously thought.

The rest of the painting seems to be designed to take advantage of this, using long diagonal lines to draw the eye outward from her face in a spiral to the point where she appears to be a somber and detached figure in the middle of revelry, whose unexpected happiness helps to resolve this larger-scale schematic incongruity which led the viewer to focus on her.

CADIE

I've been spending a lot of time today wistfully tracing google's CADIE narrative across all their different products, and am now just sitting at her blog, listening to the music and feeling oddly nostalgic for the present.

http://cadiesingularity.blogspot.com/

Literature Search

Yesterday midterms ended. That's right, yesterday. They were spread out over about 1/3 of the semester, which had definite ups and downs.

In any case, after an evening of remembering what free time felt like, today has been the day that I launch into literature searches for my end-of-semester projects. Two of my four classes have only projects and no final exams, so they need to be good. Luckily, they both promise to be really interesting as well.

In my working memory and general frontal-lobe stuff class, I'm trying to work up a proposal regarding forward modeling and prediction...basically, how parts of our brains learn what to expect, and what happens when expectations are violated. I think unexpected reward is at the basis of why we feel good when looking at or hearing certain things which are considered "beautiful", and this will hopefully help me get a better understanding of how that occurs.

For my course in vision models the project is perhaps a bit more ambitious - I'm doing the preliminary work for an experiment to look at the relationship between eye movement patterns when viewing visual artwork, EEG mismatch negativity (MMN) responses, and the rules of visual design which say certain things create tension and draw the eye. If tension involves the violation of expectations, then a visual MMN response should be generated, which could signal for attention and cause a saccade to the point which violated expectations. There are some really interesting papers already on this topic, which I'll try to post later on today.

It's fantastic to have time to explore this stuff again, and really go where I want to go instead of worrying about finishing a problem set or what I need to know for a test!

What I've been working on recently

As a quick update, these are the things that have really been capturing my interest recently:

- Perception of line ends
- The effect of the retina's resolution gradient (fovea->periphery) on perception of motion and form
- Mismatch Negativity
- Forward modeling and the circuitry of the hippocampus and cerebellum
- Broca's Area and ERAN/ELAN ERP's
- Dopamine systems and the conditions for unexpected reward
- The interaction of working memory with forward modeling and predictions
- The impact of elements of visual composition on saccades

Midterms have been keeping me busy, but I'm gearing up for end-of-semester projects, which all promise to be very exciting. I'll write more soon!

I still can't believe I'm actually here.

The first couple weeks of classes have passed now. Two weeks of it being my job to sit around and learn fascinating things as fast as I can. It's amazing.

I'm starting to at least see the routine that things will settle into, and the good news is that it looks very survivable. I have a couple base rules that I've managed to hold on to so far:
- Work is not done in my apartment. There's a cafe downstairs, parks nearby, and I have a cube in a grad office at the department, which is where I'm parking myself every weekday morning at about 9:30 AM.
- Work with deadlines is not done on the weekend. I can laze around and organize my notes from the previous week, or read papers that interested me but weren't assigned. But the weekend is my time and I'm making sure everything that needs to be done for Monday is done by the time it rolls around.

I don't know how long those rules will last, but I know that I'm working an average of 12 pretty solid hours per weekday day right now, which means that there's still a moderate amount of wiggle room before I have to break into weekend activities. This is good, because I'm visiting New York every other weekend as part of a trading off weekends visitation plan with my girlfriend in Brooklyn.

Speaking of work, I should acquaint everyone with the sources from which it flows. I'm taking 4 courses. Three 500 level and one 700 level. I don't know how it works in other departments, but in this one the 700 level courses are more focused on current topics (closer to a seminar), and the 500 are supposedly more focused on established information. In reality, we left the realm of "established true answer" about 10 minutes into the first lecture, but that's just because there is so little about the brain that has been truly established as definite.

So the classes are as follows:

Introduction to Cognitive and Neural Modeling
Vision Models
Speech and Hearing models
Planning and Timing models

I was sitting in on a computational neuroscience course as well (which is more based on the physiology/electrical activity of individual neurons), but when I found out I have to take it for credit next fall it unfortunately became something that gets put off until then.

The course readings are fascinating, and my biggest problem during the day so far has been getting caught up in my work and forgetting to eat. Luckily there's a 7-11 and a few restaurants close enough that I can reach them during the breaks in classes. There has certainly been some adjustment to the type of work being done. Over the past few years, people weren't interested in intentionally making something more challenging by withholding relevant data that they had in their possession. (Such as the answers to homework problems) Conversations happen in a very different and much more ambiguous way when one party has to avoid giving out information that the other party is ultimately seeking, and it's led to me misreading what the professor was saying on a couple occasions. Also, I'm very used to reading journal articles in my spare time, and having to put them down when I get to work. I have to keep telling myself that it really is okay to be reading them at my desk :)

Speaking of reading articles, I may have hit upon the perfect solution. I'm pretty good at reading on screens, but for mathematically based articles in particular I need to participate and scribble notes, restatements of equations, etc. So I got a tablet from fujitsu and stuck kubuntu linux on it (there was a bit of a saga where the touchscreen wasn't supported, so I had to write my first ever device driver, but that's mostly sorted now). Xournal is my first step. While reading a paper or in class it lets me write on, highlight, type on, and insert extra pages/images into pdf files. I knew it was working well when I caught myself doodling in the margins of a document during lectures. Combined with free access to a corporatequality scanner (one of those big document stations), I'm attempting to do a paperless grad school experience, and so far it's working out fairly well. I have two pages of unscanned paper on my desk waiting to be scanned and emailed to me tomorrow.

The second step is a little program called TomBoy (or if you use windows, zulupad is roughly equivalent). This is a personal wiki notetaking system, which lets me break out important terms, concepts, papers, people, systems, etc from my scribbled notes or during class. Each item has a title, and any time I type that title in another item, it is automatically hyperlinked (which is great for obscure terms and people's names). And it takes LaTeX input for mathematical formulas. I'm following a semantic tagging system I developed during my neuroanatomy course last autumn, which makes all the notes amenable to dumping into a SPARQL database, from which I can query things like, "all imaging studies published in the last three years which used human subjects and included a working memory test". And it will organize all the notes I've taken on items which match those criteria. Likewise, I could query for all the parts of the brain which help to connect the pons and the motor cortex, presented to me in order of connection from one to the other. It's fantastic, and it can just continue to grow throughout my time here and well beyond.

Anyway, that's where things stand at the moment. Boston is providing wonderful crisp autumn weather, and I'm going to see if I can't get my tablet onto the campus-wide wifi network and go do some readings under a tree by the river.

Exposition

This is the part in the show where the narrator catches you up on everything that's been happening in the character's life between episodes.

- He put in graduate school applications, kept his job during the transition, and aced the neuroanatomy final.
- He didn't sleep much during this period, however.
- He was accepted into both Boston University and University of Rochester, with full funding via research assistantship, which was much better than he was expecting to do.
- There was a long period of somewhat obsessive research on the two schools and the academic traditions that he would be buying into at each, along with visits, interviews, and discussions with current and former students.
- While it came down to the last minute, he accepted Boston University.
- Somewhat burnt out, he then proceeded to spend the next few months enjoying his remaining time in DC and thinking minimally about Grad School, at least until it was time to move.
- The move to Boston went smoothly, thanks to help from friends and family. He found a fantastic apartment in a neighborhood that reminds him very much of DC.

And that gets us up to the start of the semester and the next 5 to 6 years of graduate school.

Busybusybusy

Everything always seems to happen at once. In the next couple weeks I'm facing my neuroanatomy final, graudate school applications (the goal of this whole blog in the first place), and a transition at work -- my group in the company is being bought out, so we all need plan B jobs lined up soon, in case the transition doesn't go smoothly. In addition, I got caught up in the whole facebook/beacon fiasco, with the end result that googling my name is now far more interesting, and I actually have a conspiracy theory about me! You can read it yourself here.

In the meantime, here's what I was planning on posting about a month ago, right before most of the busy times occured:

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

I've been great - neuroanatomy is hard, mostly because I was very used to math and physics and the sort of subject where I didn't need to memorize things if I was good enough at deriving from first principles. Unfortunately, it's hard to do that with the location of cranial nerve nuclei in the pons, so I had to turn to massive rote memorization, which I never liked very much. The course itself, however, is fascinating. We're currently studying the thalamus, which I'm absolutely in love with. Plus, being NIH and therefore a somewhat crazy place, they gave us human brains to take apart and we got to scrub in and observe a brain surgery :)

Other than that I'm agonizing over personal statements, and lining up a third recommendation since the guy I was originally hoping would do it has dropped off the map and can't be reached. I'll be far happier once my applications are all in, and I can go back to doing neural models. I've got a pretty fun system going on with izhekevich models for the neurons and a homebrewed neurotransmitter release/plasticity model (adapted from a few things I found online and a lecture Erwin Neher gave at NIH a few weeks back). It seems to produce a functioning monosynaptic reflex in my AIBO, which is pretty cool :)

Work's been good too - I've taken on hunting the storm worm, which is a hive-structured virtual parasitic organism that moved into an abandoned p2p file sharing network that was left over after edonkey was shut down by the RIAA. It's really advanced in some ways, and hard to study because if the other members of the hive recognize you as an outsider they spread an alarm signal and everyone nearby starts attacking your internet connection. We're attempting to adapt the math from computed tomography to essentially take a CT scan (deriving the internal structure without coming into contact with it - and therefore not triggering an alarm) of the p2p network, though, and it's looking really promising. Our first test is next week on a local network, if all goes well.