Computational Models of Human Social Behavior and Neuroscience
Contents
Computational Models of Human Social Behavior and Neuroscienceยถ
Citation
If you use these materials for teaching or research, please use the following citation: Rhoads, S. A. & Gan, L. (2022). Computational models of human social behavior and neuroscience: An open educational course and Jupyter Book to advance computational training. Journal of Open Source Education, 5(47), 146. https://doi.org/10.21105/jose.00146
๐ Course informationยถ
Section: PSYC 347-01 Prerequisites: PSYC 002 - Research Methods and Statistics (or equivalent); No prior programming experience necessary Required materials: Only a working laptop/computer is needed! Book chapters, journal articles, and software are openly available to all students (no purchase required) Dates: January 28 - May 6, 2021 Meetings: Tuesdays and Thursdays from 11am-12:15pm Location: Online Syllabus: Found here Schedule: Found here
๐จโ๐ซ Instructor informationยถ
Instructor: Shawn A Rhoads
Pronouns: he/him/his
Email: sr1209(at)georgetown(dot)edu
Twitter: @ShawnRhoads56
Website: shawnrhoads.github.io
Other instructors are encouraged to adopt, remix, transform, and/or build upon the following materials for educational purposes under a Creative Commons Attribution-ShareAlike 4.0 International License. Information for instructors can be found in the README documentation.
๐๏ธ Tutorials & Exercisesยถ
Module 01 - Scientific Pythonยถ
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Tutorial: Jupyter Notebooks |
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Tutorial: Python Basics |
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Tutorial: Working with Data |
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Module 02 - Introduction to Modelingยถ
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Tutorial: Linear Modeling |
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Tutorial: Nonlinear Modeling |
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Module 03 - Reinforcement Learningยถ
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Tutorial: Two-Armed Bandits |
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Tutorial: Models of Learning |
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Module 04 - Social Learningยถ
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Tutorial: Prosocial Learning |
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๐ Acknowledgmentsยถ
I am grateful to Dr. Deborah Sterns, Joscelin Rocha-Hidalgo, and the Georgetown Center for New Designs in Learning & Scholarship (CNDLS) for allowing me to use their teaching resources throughout the development of this course. I am also grateful to Project Jupyter for making it possible to create and share these materials in a Jupyter Book. I am also grateful to Lin Gan for her contributions and feedback in making enhancements to these materials. The format of this course was largely inspired by the MIND Computational Summer School, Neuromatch Academy, Dr. Maximilian Risenhuberโs Computational Neuroscience course, Dr. Robert C. Wilsonโs Modeling the Mind course, Dr. Luke J. Changโs DartBrains Jupyter Book, the research conducted in Dr. Abigail A. Marshโs Laboratory on Social and Affective Neuroscience, and the countless conversations with my colleagues about the selected topics.
๐ค Contributingยถ
Please visit this page if you would like to help improve and/or expand the content in this Jupyter Book!
โจ Contributorsยถ
Shawn A Rhoads ๐จ ๐ฃ ๐ ๐ ๐ป ๐ค ๐ ๐ง ๐ โ |
Lin Gan ๐ ๐ป ๐ |
The above follows the all-contributors specification (see emoji key).
๐ซ License for this bookยถ
Content in this book (i.e., any .md or .ipynb files in the content/ folder) is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.