I have a tendency to listen to music at least 10 out of my 15 waking hours a day. Given so much time devoted to listening to music, I’ve curated quite a collection of playlists built around whatever work I happen to be struggling with at the time. There’s quite a variety so if you’re interested, I hope you can find something new to enjoy.
Inspired by my cognitive neuroscience course taught by the wonderful Dr. Ellen Lau. Somewhat mix of classic and modern shoe-gaze, very dreamy sort of semester it seems.
Yet another product of cognitive neuroscience. I feel like I spent a lot of time thinking about predictive coding both in the brain and what conclusions we can draw from large neural networks as well. Is there any useful connection that can be drawn there? Idk ask Sathvik Nair
CRAYFISH GIANT MOTOR SYNAPSES
To be honest, I’m not even sure where to start with this one. It all began with a required foundational readings course in my neuroscience and cognitive science program. It leaned on the neuroscience side of things and I can honestly say I know more than I want about ganglion cells in cicadas. But here we are. The vibes? Well you’ll have to listen and find out.
I can say with confidence, I have no idea what harmonic grammar is still. However, this playlist stemmed out of a seminar taught by Drs. Naomi Feldman and Juan Uriagereka where we were looking at different “Algorithms for implementing cognitive computations” and it was fantastic. We explored lots of different cognitive models and read through much of Paul Smolenksy and Géraldine Legendre’s “The Harmonic Mind”. It really gives a backing to understanding the theoretical basis of Optimality Theory and would definitely recommend it.
Not much to add here. It’s pretty self-explanatory, this was the semester I was taking Probability Theory. It’s also on the pop-ier side so that’s fun!
Also stemmed out of that algorithms seminar!
Also self-explanatory. I was really struggling this semester it seems.
This was the semester I took linear algebra, lots of transformations. Matrix multiplication, eigen decomposition, and so on.
An obvious reference to MMNs as they are used in speech research mainly. This really came out of an idea I was thinking about with respect to understanding phonetic category structure in second-language listeners that unfortunately didn’t get far. Maybe I’ll come back to this someday. Musically, lots of electronic bordering on hyper-pop, inspired by Yaeji’s newest release at the time and of course, Arca and Park Hye Jin.
An honorary mention here are my fellowship application playlists. I listened to a lot of Japanese city pop while working on the NDSEG, a government military fellowship that was ultimately unsuccessful.
Another research statement (for the Ford fellowship I think).