Syllabus

BCSC 280: Syllabus

Fall 2025

Meetings: Tuesdays & Thursdays 3:25pm – 4:40pm, Bausch & Lomb 315

Instructor:
Coraline Rinn Iordan, Ph.D.,
she/her
Office Hours: By appointment

Course Description

An interdisciplinary tour of human cognition with a special focus on large-scale neural representations in the human brain. Topics will include categorization, semantics, attention, memory, language, and cognitive control, with an emphasis on cutting-edge research that lies at the intersection of neuroscience, psychology, and computer science. The course will provide introductions to several neuroimaging (fMRI, MEG, EEG) and neural manipulation methodologies (TMS, tDCS, neurofeedback) and involve discussions of advanced machine learning analysis methods (multivariate pattern recognition algorithms, deep neural networks, Hidden Markov Models). The class will consist of lectures and student-led seminar discussions.

Course Structure

Lectures (18): Most of the class will consist of lectures on cognitive neuroscience topics with an emphasis on cutting-edge research that lies at the intersection of neuroscience, psychology, and computer science. Most lectures will include brief, high-level descriptions of investigative methodologies (e.g., fMRI, EEG, TMS, etc.) and computational analysis + modeling techniques (e.g., SVM, HMM, etc.).

Seminars (8): Throughout the semester, each student will lead at least one of 8 seminar discussions centered on assigned papers. For their assigned article, seminar leaders will spend 40-45 min. at the beginning of class summarizing the following:

  • The experimental question(s) addressed
  • The experimental approach(es) used
  • The results of the experiment(s)

All other students must come to class prepared to:

  • Evaluate the quality of the data (e.g., Do the experiments include the appropriate controls? Could an experiment have been conducted differently to answer the question at hand?)
  • Evaluate the quality and appropriateness of the computational analyses employed (i.e., Critically analyze how computational tools and models can inform or hinder understanding of neural processes and human behavior)
  • Evaluate the conclusions made by the authors. For example: are there alternative explanations or conclusions for the data? How strongly are the conclusions relying on whether the underlying assumptions of the computational methods are correct / upheld?
  • Evaluate the major implications of the findings in the article as they relate to the field of study.

The seminar leaders will also be responsible for moderating student discussion, providing their own evaluations of the above points, keeping the discussion topic on track, and helping the class to arrive at a unified point of view (if possible) regarding the impact and implications of the current study.

Please email the Dr. Iordan with your top three preferred seminar dates (in order of preference) no later than Sunday, August 31. All efforts will be made to accommodate student choices. If that’s not possible given everyone’s stated preferences, the seminar date assignments will be selected in class on Tuesday, September 02 by rolling a die.

Guest Lectures (2): Dr. Iordan will be out of the office between Friday, November 14 – Friday, November 21. As such, we will have two guest lectures on Tuesday, November 18 and Thursday, November 20. Speakers and topics will be announced as soon as they become available.

Materials: The course syllabus and assignment instructions are posted on the course Blackboard page. After each lecture, slides will be posted on Blackboard. Additional references on each topic, method, and technique discussed in class may also be posted on Blackboard. The latter are posted for informational purposes only and are not required reading (although seminar leaders may find those pertaining to their topic useful to skim).

Course Requirements:

  • Lectures:
    • attendance is strongly encouraged
    • the session will not be recorded
    • slides will be made available after class, but may contain incomplete information
  • Seminars:
    • attendance and active participation are mandatory
    • please contact the instructor in advance if you believe you cannot attend a session
  • Co-leading a seminar:
    • plan to read the assigned papers at least one week in advance of your presentation
    • be prepared to answer questions while presenting, rehearse your slides in advance
    • you are strongly encouraged to read additional papers from the assigned paper’s citation list, from the list of papers that cite it, and/or from the additional papers posted on the course Blackboard related to the assigned paper’s topic(s)
  • Seminar write-ups:
    • if you’re presenting, you are strongly encouraged to start drafting your write-up as you’re putting together your presentation / slides
    • if you are not presenting, be precise and concise in your impression write-up
    • students must adhere to the page and word limits for their assignments
  • Quizzes:
    • if you must leave class early, please let the instructor know in advance, if possible
  • Final paper:
    • start thinking about your preferred topic early (a month or more, if possible)
    • neuromodulation topics will be introduced in class beginning November 28; students are encouraged to start drafting potential experiment that involve neuromodulation ideas at that time
    • review the expectations, structure, and evaluation rubric carefully and adhere to the specified format and page limit in your write-up

Academic misconduct

All assignments, tests, and activities associated with this course must be performed in accordance with the University of Rochester's Academic Honesty Policy and the Student Code of Conduct.

Plagiarism, cheating, and any form of academic misconduct will be reported following the guidelines set by the University. Also, please be respectful when you post your comments/questions on Blackboard and via email to the instructor or fellow students.

Special accommodations

If you need special accommodation (e.g., medical or family emergencies, school-related travel, etc.), please let me know as early as possible. I will do my best to accommodate, but all such requests will be handled on a case-by-case basis and students may be required to provide external documentation. If you can’t take a test or submit an assignment on time for health reasons, documentations are typically required for make-ups or late submissions. Otherwise, late submissions won’t be accepted

Mobile devices

Please silence your mobile devices. No cellphone / smartphone or any other entertainment devices are allowed while class is in session. Laptop / tablet use in class is allowed for notetaking and reading course materials only.

Course Learning Objectives

  1. Develop an in-depth understanding of foundational and state-of-the-art findings in major sub-topics of human cognitive neuroscience, such as categorization, semantics, attention, memory, language, and cognitive control.
  2. Demonstrate a working understanding, including their strengths and limitations, of commonly used human neuroimaging (fMRI, MEG, EEG), neuromodulation methodologies (TMS, tDCS, neurofeedback), and corresponding advanced computational techniques (MVPA, CNNs, HMMs).
  3. Determine whether a proposed set of methodologies (neuroimaging, neuromodulation, computational) is appropriate for investigating a particular scientific question in the subfield of human cognitive neuroscience.
  4. Develop (or improve) the ability propose novel questions to advance current state-of-the-art in a human cognitive neuroscience.
  5. Demonstrate improved ability to communicate both orally and in writing about interdisciplinary and computational aspects, as well as broader implications of, findings in human cognitive neuroscience.

Evaluation

Seminar Leadership: 30%

  • Presentation & moderation (when co-leading seminar discussion): 10%
    • Present assigned papers for 45 min. total
    • Moderate discussion, answer questions, keep topic on track, help unify points of view
  • Write-up (when leading seminar discussion): 20%
    • Write-up: 3-4 pages, choose one of the two papers to critique
    • Evaluate the paper’s strength and adequacy of methods and approach
    • Time to submit: 6d from in-class presentation

Seminar Participation: 30%

  • Participation (when not co-leading seminar discussion): 15%
    • Assessed as ✓-, ✓, ✓+
    • Average below ✓ = half credit; Average at least ✓ = full credit; Average ✓+ = 1% extra credit
    • Lowest score will be dropped (including if student misses seminar)
  • Impressions (when not co-leading seminar discussion): 15%
    • Write-up: 100-200 words
    • Assessed as ✓-, ✓, ✓+
    • Average below ✓ = half credit; Average at least ✓ = full credit; Average ✓+ = 1% extra credit
    • Time to submit: 15.5h before in-class discussion (midnight the day before class)
    • Lowest score will be dropped (including if student does not submit)

Lightning quizzes: 10%

At the end of 12 lecture classes specified on the class calendar, students will be given a problem statement from a published scientific article, and they will be asked to identify:

  1. a reasonable method or methods (e.g., psychophysics, fMRI, EEG) to address the question; and
  2. a plausible computational analysis method or technique that would help answer the question.

Responses are expected to be exceptionally brief (2-5 words), followed by a 1 sentence explanation. Quizzes are closed book, no devices allowed, with a time limit of 5 min. The quizzes will be evaluated as ✓-, ✓, ✓+; Average below ✓ = half credit; Average at least ✓ = full credit; Average ✓+ = 1% extra credit. The lowest score will be dropped (including if student does not submit or misses class).

Final paper: 30%

You will propose a novel experiment that involves using a neuromodulation technique and/or a computational analysis to potentially answer an open question arising from any of the studies/topics discussed in class. Your paper must be approximately 5—6 pages long and include:

  • a clearly stated hypothesis
  • a high-level experimental design (students may propose a modification to an existing design in the assigned paper, e.g., ‘similar to Experiment 2, except we would…”)
  • a computational analysis that would provide evidence for/against the hypothesis you described

The open question must not be already mentioned as a future direction in the study. A detailed description of expectations, structure, and evaluation metrics for the final paper are posted on Blackboard. The final paper is due on Friday, December 13, 11:59pm EST.

Instructions: Detailed instructions for the seminar impressions, seminar moderator write-up, and final paper are posted on the course Blackboard page.

Oopsie: Every student is allowed one unconditional ‘Oopsie’ throughout the class. This can be used to either (1) delay submission of a seminar moderator write-up by 48h; or (2) drop an extra lowest score from a lightning quiz, an impression write-up, or a seminar participation grade (e.g., to make up for an unexpected absence). The ‘Oopsie’ cannot be used to delay the final paper submission.