Sunday, June 03, 2012

sum.. sum.. summm... summation?

ok, so i'm working on this classification image paper, and it's going really well, and i'm pretty happy about it. i feel like i've got a good handle on it, i'm writing it in one big shot, the analyses are all good, the data are fine, it's all under control. i'm pretty happy about this one. i keep telling myself that, and then noticing that i keep telling myself that. i guess it's in contrast to the blur adaptation paper, which was such an ordeal (took 2 years, basically), and then the magnification paper, which just isn't much fun. i feel myself moving down that priority list - hey, i should do a post on the priority spreadsheet! i made some nice plots in there!

anyways, the CI paper, it's going well, but i'm constantly on the lookout for problems. so tonight, i finally thought of one. not a crucial, deep problem, but a problem with how i've calculated some of the modeling stuff, a serious enough problem that i'll probably have to redesign a bit of it before doing the final runthroughs. i'm writing this entry so i can just sort of kick off thinking of how to solve the problem. here it is, right plain as day in this little cluster of plots from last year's poster, which has become this fine little paper:

the problem is spatial summation - or, the problem is that you don't see anything about spatial summation in those plots. for the main models, i have a CSF that was measured using test-field-sized images. the thresholds measured must reflect a sort of spatial summation, then. the problem is, i've been using those thresholds to set the baseline thresholds for the models, and then summing over the spatial responses. i had kind of had an inkling that i was being lazy there, but had overlooked how obviously stupid that is. i haven't tested the models on the threshold tasks, but i think that they would necessarily get much lower thresholds than the humans; spatial summation should give you a lower overall threshold than you would get for any single location. i need to think of a quick way to solve this, because i don't want to wind up estimating the model CSF through simulations...

and the simulations then raise the problem of noise, and how many samples should there actually be, etc etc... i guess there are benefits to doing things the simple way first, but i think i've run myself into a weird little corner here. gonna need to talk to somebody about this, probably..

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