Comp. Neuro

Summary

Presentation I gave in 9.29, the computational neuroscience class at MIT. They attempted to build a model that could use the information obtained from recordings in the prefrontal cortex and other areas of a monkey brain to predict their behavior based on the 'state' their neuron groups were in.

For my computational neuroscience class, we had to present a paper and explain its methods and findings (along with possible applications) to the class. Below is my presentation.

-biafra
bahanonu [at] alum.mit.edu

additional articles to journey through:

mexico project, final presentation
29 january 2011 | science

I spent January 2011 in Cuernavaca, Mexico and worked on a project to model the Notch and JAK/STAT signaling pathways. This is part of one [...]presentation, which I gave in Spanish.

¿qué es la calle?
24 may 2013 | short story | spanish

Había terminado y salé para mi cocina. Tenía hambre pero este día no había comida dentro de mi despensa. Me fui y caminé hacienda[...] la Tport—una máquina que puede transportar una persona a otro lugar sin energía y tiempo. Cuando entré la máquina, toqué algunos botónes y esperé. Pero nada ocurrió y lo hice las mismas acciones otra vez—y nada ocurrió.

How would the disappearance of streets affect the social fabric? This short story briefly (in castellano!) explores a world in which instantaneous, free transport is possible. Meant mainly to practice my spanish, i plan to follow-up with a more detail story in the future.

singapore: final report
16 september 2012 | singapore

Before finishing my adventures in Singapore, I was asked to put together a final report describing my experiences and where the program cou[...]ld improve. Rather than bore you with details, I've included a link to download the report. This is a draft form and I'll update the link with a finished version in the future.

satellite-based videos: eastern europe during the russia-ukraine conflict
30 november 2022 | satellite

To visualize the nighttime lights of Eastern Europe, with a focus on times before and after the ongoing Russia-Ukraine conflict, I updated [...]my geoSatView R code originally built to view forest fires in the west coast of the United States to use satellite data from VNP46A1 and other datasets collected from the Suomi NPP VIIRS satellite.

I then created higher-quality movies in MATLAB by using the VNP46A2 Black Marble dataset collected by the same satellite, which has reduced cloud and other artifacts due to additional data processing. This allowed me to quantitate a permanent reduction in nighttime lights within Ukraine (in line with my initial hypothesis) and identify a multi-stage reduction of nighttime lights in Kiev's outer neighborhoods/metropolitan area that was greater than that seen in the city core/center. This highlights the utility of public satellite data to quickly test hypotheses and visualize large-scale changes.

I will go over how the Black Marble dataset is collected and processed along with how I created the movies and the advantages/disadvantages of each data source.

Using this platform and codebase, in follow-up posts I will look at 2021 Texas power crisis during the winter storms, vegetation changes in deforested areas or after conservation efforts, and other events.

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