Resources
My journey into science was made possible by a host of grad students, post-docs, and professors committed to open science and the mentorship of young researchers.
Along the way, I’ve picked up a fair number of resources that I never would have found if they weren’t recommended to me. This list is a compilation of those resources.
If you have any additions you’d like to make, please reach out to me!
Citation Tools
- freecitationchecker goes through your paper and locates your citations and automatically matches them with your references. Anything without a direct match or missing entirely gets flagged. Note that your file must be in .docx format. Created by John Andrew Chwe.
Coding
- This Markdown Cheatsheet is a helpful guide to how to do many of the basics if you’re working with markdown files (e.g. Jupyter Notebook, R Markdown, Quarto Markdown).
Color Palette Generators
- Coolors is a good site for generating color palettes on the fly. It’s fast, flexible, and honestly sometimes I just make palettes for fun.
- ColorBrewer2 is an easy way to make more traditional R color palettes. Unlike Coolors, this has no ads, and a direct checkbox to filter for color-blind friendly palettes.
Data Analysis Tutorials
Behavioral
- Stanford Anthropology’s Social Network Analysis Workshop walks through some social network analyses.
- Dartmouth’s Naturalistic Data Analysis course goes over various techniques for analyzing naturalistic data in Python.
fMRI
- Andy’s Brain Book is an all-round introduction to fMRI analysis using SPM, FSL, and AFNI.
- DartBrains is designed to give an introduction to neuroimaging data analysis (with a focus on functional connectivity and multivoxel pattern analysis).
Data Annotation Tools
Audio
Visual
- Easy OCR (Optical Character Recognition) is designed to extract natural language from images, producing text strings for more easy data processing. As of July 2025, compatible with printed text but not handwritten.
- PARE (Part Attention REgressor) is an occlusion-robust human pose and shape estimator. See arXiv paper here.
- Py-Feat is a Python toolbox designed to annotate facial expressions in terms of facial landmarks, action units, and emotional expression. See arXiv paper here.
Free Icons
- Bootstrap can get you the basics - a bunch of filled and outlined vector graphics in case you need something simple.
- Chojugiga has really cute options if you want up to four consistent characters in your presentation.
- Flaticon has tons of options and makes it easy to get several versions of the same character for presentations.
- I’m told that if you’re willing to make an account you can also change the color of some icons.
 
- Font Awesome is similar to Bootstrap but has some more variety.
- If you’re cheap like me and won’t pay for pro, there aren’t many more options but you might find something to your liking.
 
- The Noun Project is similar to Bootstrap and Font Awesome but has a massive selection.
Open Source
Conference Workshops
- Artificial Neural Networks as Models of the Brain in Cognitive Neuroscience organized by Isil Poyraz Bilgin, Pierre Bellec, and Elizabeth DuPre
- Introduction to the construction of neural network models of the brain (focused in part on decoding/encoding)
- Presented at the 2023 Organization for Human Brain Mapping (OHBM) Conference
 
Datasets
- OpenCogData compiles publicly available cognitive task papers and datasets and is maintained by the NIMH Data Science & Sharing Team.
- If you’re looking for some papers/datasets for a specific cognitive task/topic, this website also has a tagging system so you can filter relatively easily.
 
- SNAP (the Stanford Network Analysis Project) has a collection of publicly available large network datasets.
Textbooks
- Computational Cognitive Neuroscience, 5th Edition by Randall C. O’Reilly, Yuko Munakata, Michael J. Frank, Thomas E. Hazy, and contributors.
- An introductory textbook for how to computationally model cognitive processes (e.g., perception, attention, motor control).
- There’s also a companion set of simulations for you to run as you work your way through the textbook.
- This was used in Michael Frank’s Computational Cognitive Neuroscience course at Brown University as recently as Fall 2024.
 
- Networks, Crowds, and Markets: Reasoning About a Highly Connected World by David Easley and Jon Kleinberg.
- An introductory textbook for the conceptual basis of network analysis.
- This was used in Augustin Chaintreau’s Networks, Crowds, and the Web course at Columbia University as recently as Spring 2025.
 
Other Websites with Resource Lists
- CompSAN or Computational Social Affective Neuroscience has a bunch of tutorials as well as a job board and links to other online resources.
Website Making Tutorials
- This website was made following Sam Csik’s Quarto tutorial which I highly recommend!