PSYC 347: Computational Models of Human Social Behavior and Neuroscience

TR: 11:00am-12:15pm, Online/Remote

The goal of computational modeling in behavioral and psychological science is using mathematical models to characterize behavioral (or neural) data. Over the past decade, this practice has revolutionized social psychological science (and neuroscience) by allowing researchers to formalize theories as constrained mathematical models and test specific hypotheses to explain unobservable aspects of complex social cognitive processes and behaviors.

This course comprises lecture-based, discussion-based, and lab-based instruction. At least one-third of class sessions will be hands-on. We will discuss relevant book chapters and journal articles, and work with simulated and real data using the Python programming language (no prior programming experience necessary) as we survey some selected areas of research at the intersection of computational modeling and social behavior. These selected topics will span a broad set of social psychological abilities including (1) learning from and for others, (2) learning about others, and (3) social influence on decision-making and mental states.

Together, we will expand your skillset for conducting research in psychological science, cognitive science, neuroscience, and/or data science. Although some background in psychology, research methods, and/or programming will be helpful, students with all levels of experience are welcome to enroll.

Why read this syllabus?

The syllabus is your go-to resource document for the course. If you want to know about the requirements for the class, how you will be graded, or additional resources, you can find that information here. If you have questions about the policies for the class, you can find the answers here. In addition, the syllabus is a contract between you and me – by remaining in the class, you are agreeing to this contract. And you should always read a contract before agreeing to it! So please be sure to read the syllabus fully.

Required materials

Only a working computer (or laptop) with a webcam/microphone and reliable internet service are required! Although you can use other devices such as smartphones and tablets for some online coursework, please note that some tools do not work on tablets or smartphones. Book chapters, journal articles, and software are freely accessible and/or openly licensed to all students (no purchase required). Why? Because everyone should have access to educational experiences and resources, and open educational resources work to eliminate barriers to this goal. Students can access all materials on Canvas or on the course webpage. If there are any changes made to this syllabus, an email will be sent out accordingly.

We will use the following technological tools/applications on a regular basis. Please reach out to the instructor if you believe this will be an issue.

  • Web conferencing: Zoom, webcam/microphone

  • Web interfacing: Course website, Canvas

  • Scientific programming: Python, Jupyter Notebook, Google Colaboratory

Important course information

Course assignments will be posted on Canvas, which include the course readings, videos, and links to the assignments you will need to complete each week. You’ll need to be able to upload and download files, view streaming video, and use applications such as Google Docs, Jupyter Notebook, Google Colaboratory, Slack, etc.

Be sure you have set your notifications in Canvas so that you receive announcements, Canvas mail, discussion board posts, etc. I will post announcements regularly to communicate with the class. The minimum requirements to use Canvas can be found in this Canvas guide.

Class meetings and office hours will be held on Zoom. You will need a microphone and webcam (you need not always have your webcam on, but you will want to be able to be visible at times). These sessions will be recorded and recordings will be posted on Canvas (including video, audio, and chat). By participating in class, you are giving permission for your participation to be recorded and posted online for other students to view. If that is a concern for you, please let me know.

Students located in certain countries may face challenges participating in some academic enterprises due to fear of censorship, retaliation, or sanction. Some individuals have reported that following best security practices related to Zoom, NetID accounts, and device hygiene are sufficient to assuage those fears. Other individuals have reported that the use of Virtual Private Networks (VPNs) may better address some of these challenges. I cannot provide or recommend specific VPNs for student use; students are encouraged to research available options and determine whether they can lawfully and reasonably make use of such a technological solution in their jurisdiction. If this is a concern for you, please feel free to let me know so we can strategize how to best address this issue.

Who am I?

My name is Shawn Rhoads (call me Shawn). I use the following pronouns: he/him/his. I am a PhD candidate conducting psychological and neuroscience research on interpersonal perception, shared or vicarious experience, and prosocial decision-making. I love learning about the human brain and social behavior. I also enjoy listening to electronic music, drinking dark-roast coffee, and writing code in Python (both in and out of the lab). You can find me on Twitter: @ShawnRhoads56

This is the course I wish I had as an undergraduate student. I am committed to helping you learn, and succeed! If you have any questions about the course or about psychology, please don’t hesitate to ask via email. I will try to answer email promptly (within a day or two), but I get a lot of email and sometimes forget that I haven’t answered yet, so if you need an answer and haven’t heard back from me, feel free to email again. My office hours will be held on Zoom on Mondays from 2:30-4pm, please email me if you plan to show up. My email is sr1209(at)georgetown(dot)edu.

Here is a good tutorial on how to email your professor:

Course goals

  • Understand the following: what are computational models, why use computational models, when to use computational models, and how models are fit to data

  • Survey selected topics on social behavior through readings, discussions, and labs (e.g., Jupyter Notebook tutorials using Python)

  • Learn how to write code for data science using the Python programming language and Jupyter Notebooks

  • Fit mathematical models to data and evaluate their performance

  • Interpret the results of social behavioral experiments

  • Gain a richer understanding of how computational modeling advances psychological science and neuroscience

Meeting these goals

Computational modeling of behavior is an exciting, emerging practice in psychological science and neuroscience, but it is also challenging to learn at times. In order to keep up and get the most out of the class, you must be willing to do the work of active learning. You should commit to studying at least 6-9 hours per week (outside of class time) for this class. Remember, this is your education. I am here to help you learn and to evaluate your progress, but I cannot make you learn—that’s on you. It takes commitment and effort on your part to learn, but with some forethought, the process can be fun.

Here are some tips and tricks to help you succeed:

  • First, identify what you need to learn. Identify the main points and key ideas in the readings, as well as the relevant evidence and methodologies.

  • You’ll need to complete the assigned readings before class. This is important, because we’ll be doing activities in class that involve applying material from the readings. If you haven’t done the assigned readings, you won’t be prepared to do the class activities. You will also need to write responses to the readings for each class which will require completing the assigned readings.

  • Effective reading is more than just flipping pages and having the words move past your eyes, though. You need to actively engage in the process of reading. The key to learning is actively processing and organizing the material. As you read, identify the main points and key questions in each section. Take notes in your own words. Highlighting is not as effective as note-taking, particularly when you take notes in your own words, summarizing and restating the concepts and ideas in the readings (rather than just re-writing what is in the text). Think about what you are reading and relate it to what you already know. Try applying the ideas to your own life, which will make the material more interesting as well as help you learn and remember.

  • Space out your learning and studying. Set up a schedule that involves doing some reading, learning, reviewing, and writing for this class every day or so (being sure that you have allocated about 6-9 hours total per week) and stick to your schedule.

  • Work on understanding the material, not just memorizing it. You may have had classes in the past that focused mostly on your ability to memorize facts and definitions, but I am much more interested in your ability to understand and apply the material. Don’t just memorize definitions. Conducting research is never that simple. Work on understanding concepts well enough to describe them in your own words and identify examples of the concepts.

  • Come to every class on time and ready to participate. Participating in class activities will help you learn the material, so it is best that you attend every class, if possible. We’ll discuss and apply the material. You’ll get to ask questions about any material that you found confusing. Studies find that students who attend class regularly tend to get better grades (Credé et al., 2010; Alexander & Hicks, 2016). There will also be points given for class participation, so missing class will mean that you miss the opportunity to earn those points.

  • Identify trouble spots and get help. When you don’t understand something, ask for help. If something is unclear to you, ask a question; most likely, there are other students who have the same question. If you don’t understand something in the readings, come see me and ask me about it. It is not a good strategy to just wait and hope that enlightenment will come to you—often, it doesn’t. This is another good reason to keep up with the readings and to learn actively—both of these will allow you to identify trouble spots early and fix them. It is also important to get help early and not to wait until the last minute.

  • Learn by doing. About one-third of this class involves hands-on exercises (e.g., writing and executing code in Python). These exercises were developed to supplement and augment your learning experience. If something discussed in class wasn’t clear, it’s possible that implementing something yourself will be helpful.

  • Help each other. This is a class about social behavior. I don’t expect you to work alone, especially on the coding exercises. As you help one another, think about some of the psychological and computational processes at play (which we will learn about throughout the semester).

Creating an online space that fosters learning

To create a classroom space where we can all effectively learn, each of us needs to commit to focusing on the learning activities and minimizing distractions. Anyone who isn’t focused on the class activities is not only depriving themselves of the opportunity to learn, but is also distracting other students and creating a climate that hinders other students’ learning. In other words, when you are doing something that is not related to the class activity, you are not learning and you are making it harder for other students to learn. So each of us needs to make an ongoing commitment to creating a distraction-free classroom where we can all focus on learning. That means:

  • Mute your sound when you aren’t speaking. Having random background noise is distracting, so when you aren’t speaking, stay muted.

  • Pay attention to the class activities. This will maximize your learning and foster a positive learning environment for others. I know that it is very easy to zone out or do other activities while participating in online classes, but it will hinder your learning and your enjoyment of our class activities. It also means that you won’t contribute as meaningfully to class discussions, so you will be depriving other students of their opportunity to learn from you. I will do my best to make our class sessions engaging. Please do your best to stay focused on class activities. If I can help in keeping you focused during class, let me know.

  • Participate actively. Everyone will get the most out of our classes if we all commit to active participation. Listen actively. Share your questions, thoughts, and ideas. Every semester, one of the consistent themes of peer feedback is that students want to hear from their classmates. That doesn’t mean you should dominate the conversation, but do speak up when you have something to contribute. You can do so in a variety of ways:

    • Use the “raise hand” button in Zoom. I’ll see that and call on you. Note that I may not see this if I am sharing my screen, though.

    • Unmute your sound and just speak up. That can be challenging in a large class, as it might hard to know when to break in, but this works well in the breakout sessions with your team. And if there is a moment when you have a question and I haven’t seen your raised hand, do feel free to just speak up.

    • Post in the chat. Zoom has a chat function—click on the chat icon on the bottom menu and you’ll get a chat space on the right menu. You can type comments, questions, and ideas there. The default is that they will go to everyone in class, but you can also send them to just one person. I will try to monitor the chat, but sometimes it is hard to juggle leading discussion and monitoring the chat, so if I miss something, feel free to raise your hand or just speak up.

    • We will also use other technologies to share ideas, such as shared Google Docs and Slack.

We also need to create a safe space for learning. You may have some of your prior beliefs and assumptions challenged—that is what education is often about, after all. So we need to support each other and behave respectfully at all times. That doesn’t mean we can’t disagree with each other, though! Discussions often involve different points of view and disagreement between individuals, even heated disagreements, at times. It is these differences that can make discussions interesting and worthwhile and often lead to a deeper understanding of the issues. You are always welcome to disagree with someone else’s comments, provided you do so in a scholarly, thoughtful manner. If you disagree with someone else’s comment, make your point of view clear without maligning the other person.

  • Treat every member of the class with respect, even if you disagree with their opinion. Listen carefully when others are speaking.

  • Treat every opinion or idea as open to examination (including your own).

  • Reasonable minds can differ in their perspectives, opinions, and conclusions. We will ground our discussions in scientific evidence, but people may interpret the evidence in different ways.

  • You will not be graded on whether I or your peers agree with your opinions, but only on the evidence and reasoning that you use to support your points.

  • Respect other students’ privacy by keeping their comments confidential. If someone shares personal information or experiences, this needs to remain within this class—do not discuss them with anyone else outside of the class.

Please be nice and respectful to everyone in class, and adhere to the Georgetown Code of Conduct. These rules of classroom conduct are vital to creating and maintaining a positive learning environment in class. Persistent failure to adhere to guidelines of classroom conduct may result in a failing grade or being dropped from the course.

I value our diverse student body and am committed to fostering an equitable classroom environment. I invite you, if you wish, to tell me how you want to be referred to both in terms of your name and your pronouns (he/him, she/her, they/them, etc.). Additionally, it is your choice whether you disclose how you identify in terms of your gender, race, class, sexuality, religion, and dis/ability, among all aspects of your identity. I will do my best to address and refer to all students accordingly, and I ask you to do the same for all of your fellow students.


I will assess your learning primarily through written assignments and class participation. Your written work should of course be logical, well-written, thoughtful, and free from mechanical spelling and grammatical errors (I strongly recommend that you proofread and spell-check your assignments!). Grades will be based on meeting the criteria of the assignments, quality of ideas, originality, accuracy, and quality of writing.

You will earn points based on your assignments. Final grades will be assigned according to the following scale:

450 – 500 total points


435 - 449 total points


415 - 434 total points


400 - 414 total points


385 - 399 total points


365 - 384 total points


350 - 364 total points


335 - 349 total points


300 - 334 total points


250 - 299 total points


249 or fewer total points


Late Submissions

For assignments that are submitted late, the maximum obtainable grade will be reduced by 10% for each day it is late. For instance, if an assignment that is three days late receives 9/10 points, the student will receive 6.3/10 points instead.

Extra Credit

You may earn extra credit up to 3% to your total grade. There are three ways to obtain extra credit: (1) participate in a research study through the Georgetown Research Volunteer Program, (2) refer someone to participate in a research study through the Georgetown Research Volunteer Program and submit a one-page reflection after interviewing them about their experience, and/or (3) submit a one-page reflection from the optional reading list. Completing each earns one extra credit point. For example, you may obtain 2 research participation credits and complete 1 article reflection for a total of 3 extra credit points. You may also obtain a total of 3 research participation credits.


Please visit the Assignments page for the most updated list of assignments and due dates.

Attendance [5 points]: Students will be deducted .04% of their final grade for each unexcused absence. Please email me if you are unable to attend class for any reason to be excused (no need to disclose reason).

Class Contributions (Participation) [70 points]: Students can contribute to class sessions by: asking questions, answering questions, adding comments, thoughts, or opinions to the discussion, helping classmates, offering ideas or suggestions, etc. I expect students to take advantage of online forums (e.g., Canvas, Slack) to ask questions related to course readings, mathematical models, general Python programming, Jupyter Notebook, course exercises, assignments, Canvas, Zoom, or accessing materials. I also expect student to help each other by responding to these questions.

Reading Responses [65 points]: For each reading assignment, students will submit a brief response (1 page, single-spaced). This is not an article summary; you have to explore your own idea(s) about the readings. These must be submitted by 5:00pm on the day before class on Canvas. To receive full credit, these must show close reading and thoughtful engagement with the assigned readings for that day. A high-quality Reading Response provides in-depth, thoughtful exploration of one or more ideas, clearly relates these ideas to the readings in a way that indicates close and careful reading, and is well-written (strong paragraph structure, clear and cogent use of language, free from spelling and grammar errors). Some ideas for reading responses:

  • Identify aspects of the reading with which you disagree and discuss why they are problematic.

  • Discuss what most surprised you about the material in the readings and why you found it surprising.

  • Discuss potential applications of the material in the readings – ways in which it applies to your own life or ideas for how to use the material in the readings to improve the quality of life more broadly.

  • Limitations of the theories or research discussed in the readings and how these should qualify our conclusions.

  • Ideas for new studies or theories in the field.

  • Implications of the research with regard to current social or political issues.

  • Was their evidence enough for their claims? What else would you have liked to see?

Article Presentation [50 points]: Students will sign up to present one research article (15-25 minutes) and lead the class discussion (30 minutes). These should include:

  • A brief overview of the paper (i.e., a powerpoint presentation)

  • Discussion/Interpretation of figures when possible/relevant (e.g., no need to interpret figures of brain images)

  • Discussion points or questions (similar to the ones for your reading responses). These points should include a discussion of the “computational model” (or models), including:

    • What model was used?

    • Has it been used in previous papers before?

    • Why this model?

    • What are the parameters in the model? what are the correlates of these parameters?

Jupyter Notebook Exercises [105 points, 25 points for #1-3, 30 points for #4]: Students will complete four coding exercises based on selected course topics throughout the semester.

Project Proposal - Round 1 [25 points]: Students will submit a 250-300 word abstract describing their research question, hypotheses, and study idea along with an outline of the relevant content (i.e., summary of points for the following sections: Introduction, Experimental Design, Intellectual Merit, Broader Impacts, and Conclusion). They should set up a meeting with the instructor (during office hours) to determine a final project. Upon completion of this assignment, students will receive feedback and suggestions on how to improve their study and should incorporate this feedback into their proposal (Round 2).

Annotated Bibliography [25 points]: Students will choose 7-10 research articles and summarize the research questions, methods, and results of each paper (behavior only). Students should also include 2-3 sentences on each paper’s relevance to their final project.

Project Proposal - Round 2 [75 points]: Students will expand their 250-300 word abstract based on feedback from the instructor. Their project proposal should be 2-3 pages (in NSF GRFP format) on a hypothetical research study.

Project Presentation [80 points]: This presentation will be the “final exam” of this course. Students will present their project proposal to the class (5-8 minutes each) and determine 2-3 questions for a quick class discussion (3 minutes).

Academic integrity

I take academic integrity very seriously. Each student is responsible for performing academic work that holds to the highest standards of honesty. Cheating and plagiarism are unacceptable and disrespectful – not only to me, but to the other students who did the work of learning. Besides, the person who cheats is not only lying, but is also denying themselves the necessary learning.

All students are expected to maintain the highest standards of academic and personal integrity in pursuit of their education at Georgetown. Cheating harms the University community in many ways. For example, honest students are frustrated by the unfairness of cheating that goes undetected and students who cheat can skew the grading curve in a class, resulting in lower grades for students who worked hard and did their own work.

Academic dishonesty, including plagiarism, in any form is a serious offense, and students found in violation are subject to academic penalties that include, but are not limited to, failure of the course, termination from the program, and revocation of degrees already conferred. All students are expected to fully adhere to the policies and procedures of Georgetown’s Honor System and to take the Honor Code Pledge:

In pursuit of the high ideals and rigorous standards of academic life I commit myself to respect and to uphold the Georgetown University honor system: To be honest in every academic endeavor, and to conduct myself honorably, as a responsible member of the Georgetown community as we live and work together.

Over and above the honor code, in this course we will seek to create an engaged and passionate learning environment, characterized by respect and courtesy in both our discourse and our ways of paying attention to one another.

The core of academic integrity is that you submit your own work and not submit someone else’s work as your own. In the case of written assignments, that means that you need to provide appropriate citations for any sources you use (including the text and assigned readings). Citing your sources gives credit to those authors for the work they did; it also means that the reader knows where you got your information and can evaluate the quality of your sources. If you don’t cite your sources, you are essentially stealing someone else’s work and pretending it is your own. In the case of a scientific paper, it also makes your work less credible, because the reader is looking for scientific evidence to support your points.

When you use someone else’s exact words, you need to put quotation marks around them and provide a complete citation (including page number). Without quotation marks, you are claiming that these are your words, which means you are stealing someone else’s writing and pretending it is your own. Just changing a word or two in a sentence does not make it your own writing. You would need to completely rephrase the sentence to make it a paraphrase that doesn’t require quotation marks (though it would still need a citation to give credit to the writers for their ideas).

In other words, academic integrity in a written assignment means that:

  • All of your writing is your own. Having someone else write your paper, buying a paper online, or using someone else’s words or ideas without citation is plagiarism.

  • Any sources you use are fully, completely, and consistently cited. That means that you need to provide full citations for the source at the end of the paper, as well as in-text citations that make it clear where the ideas or quotes came from. Failing to provide full and complete citations constitutes plagiarism. This includes citing the textbook and/or other assigned readings if you use them in your writing assignment.

  • Any direct quotations are marked with quotation marks, as well as a correct and complete citation. If you are using someone else’s words, put quotations around them and provide an in-text citation to indicate the source (and the page number).

It is best to get in the habit of having academic integrity, because the consequences for cheating and plagiarism can be very high, both in college and in your career. Stealing someone else’s work is a terminal offense in the workplace; there are any number of examples of professionals who have lost their jobs because of a lack of integrity and honesty in their work. If you have any questions about academic integrity or how to provide appropriate citations, please ask. You can learn more about plagiarism, paraphrasing, and the need to credit at

All submissions must be your original work. Any submission suspected of plagiarism will be immediately referred to the Honor Council for investigation and possible adjudication. All students are expected to follow Georgetown’s honor code unconditionally. If you have not done so, please read the honor code material located online at the Honor Council website.


If you experience sexual violence, identity-based harm, or any other personal crisis at any point during the course, please do not hesitate to reach out to (1) help you catch up with course material or (2) put you in contact with the appropriate resources and services. Here are some resources that you can also refer to:

I am committed to supporting survivors of sexual misconduct, including relationship violence and sexual assault. Due to federal law, I must report any disclosures of sexual misconduct to the Title IX Office. I want to be able to protect you as best as I can, and in this case, it would be to report the survivor’s story to the appropriate authorities.

Did you know that Georgetown University has its own food pantry? They have non-perishable food and personal hygiene products. During the period of online instructions, they relocated to McShain Kitchen, adjacent to McShain Large. You just need your GoCard to access. If you encounter any problems getting in, contact GUPD at 202-687-4343.


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 Risenhuber’s Computational Neuroscience course, Dr. Robert C. Wilson’s Modeling the Mind course, Dr. Luke J. Chang’s DartBrains Jupyter Book, the research conducted in Dr. Abigail A. Marsh’s Laboratory on Social and Affective Neuroscience, and the countless conversations with my colleagues about the selected topics.