Computational Social Neuroscience Lab

The Society for Personality and Social Psychology (SPSP) was kind enough to ask me a few casual questions about my career for their monthly Member Spotlight feature.

Check it out here:  https://spsp.org/member-spotlight/rob-chavez

There is so much interesting work going on in the lab these days! Here are our lab members’ posters for the Social and Affective Neuroscience Society 2021 meeting.

 

Self-Esteem Modulates Self/Other Neural Pattern Correspondence
During Interpersonal Perception
Moriah Stendel
(poster award winner)

 

Valence Modulates Self/Other Recapitulation Effect
During Interpersonal Perception
Faith Collins

 

Disentangling Neural Activation to Self and Others
Using Structural Connectivity
Youri Benadjaoud

 

 

Peer Perceptions of Neuroticism and their Influence on
Friendship and the Brain
Ryan Conaghan

I joined UC Berkeley graduate students Smriti Mehta and Paul Connor on their podcast More of a Comment than a Question to discuss the intersection of neuroscience and social psychology and about the variety of views one can have about the goals of that marriage.

You can find the interview wherever you get your podcasts or here: https://www.buzzsprout.com/1207223/6712774

There are plenty of places to track trends in state-by-state COVID-19 data, but I find many of them to be a bit messy or bloated for just getting a quick snapshot of what’s going on with the information I care about. So, I wrote a no-frills web app that automatically pulls up-to-date data from covidtracking.com API and makes plots of the things I want to see. You can find this app here:

https://robchavez.shinyapps.io/shiny/

If you are interested in tinkering with the code or using it as a template for your own R Shiny app, you can find the code for it here:
https://github.com/robchavez/misc_scripts/blob/master/app.R

There are countless numbers of applications which involve large amounts of sparse data in all scientific and commercial domains. To that end, our own Dale Tovar has created and implemented the GXCS format, which is a novel storage scheme for ultra-large sparse arrays and tensors. One of the advantages of the new format is that it takes up much less storage space in many of the scenarios encountered in practice. For example, unlike the commonly used COO format where storage size increases strongly as both a function of the number of axes and the number of nonzero values, GXCS increases in storage size primarily as a function of the number of nonzero values. The software includes conversions to and from different formats. This will help greatly speed up analyses for anyone who uses it. 

In even bigger news, GXCS is written in the Python and has been incorporated in to pydata/sparse library which is replacing the defacto sparse matrix library in SciPy in a couple of years!

Amazing work and huge congrats to Dale!

Our own Ali Mattek wrote this fascinating piece on formal modeling and systems analogies in psychology.  The widely admired statistician Andrew Gelman linked to it on his popular blog saying, “It reminds me a bit of the writings of Paul Meehl.” High praise. 

You can read Ali’s piece here:

Using structural connectivity and predictive modeling methods to relate personality and mental health variables is one of the projects we have going on in the lab. Here is my talk on some preliminary efforts on this project from the Computational Preconference at the 2019 Social & Affective Neuroscience Society meeting in Miami, FL.

My colleague Sanjay Srivastava was gracious enough to let me write a guest post on his blog about some of my musings on the relationship between neuroscience and psychology. Here, I try to make the case that neuroscience and psychology can be mutually informative to one another in ways that are sometimes unappreciated.

You can find the post here:

This is your Brain on Psychology – This is your Psychology on Brain (a guest post by Rob Chavez)

In the Spring of 2018, I taught a graduate seminar called Data Science Methods for Psychology. This course was indented to introduce students to topics, concepts, and workflows that are commonplace in “data science” more generally but are less formally discussed in Psychology.  Each week, a pair of students would lead a tutorial session on a given topic before assigning a “mini-hackathon” project for the rest of the class to complete over the coming week. These presentations were consistently excellent, and I thought I would share them as widely as possible for others interested in learning from them. Find them in my GitHub site in the link below:

UO Psychology Data Science Gallery

This is the inaugural post of the CSN lab. If you’ve made it this far, thank you for  your interest in our work. We hope to continue to use this blog/news section for updates on the lab, ‘pop’ summaries of our work, and links to personal and other academically relevant blogs.

Thanks again, and stay tuned.

-Rob