Syllabus

BCSC 280: Syllabus

Fall 2023

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

Instructor:
Marius Cătălin Iordan, Ph.D.
he/she/they

Office Hours

By appointment in Meliora 308

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, fNIRS) 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.

Lectures

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.).

For the final lecture (December 12), students are encouraged to propose a topic or question that was not addressed in class during the semester by emailing the instructor on or before Friday, December 01. A few such topics will be selected and briefly discussed during the last lecture of the semester.

Seminars

Throughout the semester, we will have 8 seminar discussions centered on assigned papers, each led by two students. For their assigned article, seminar leaders will spend 20-25 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)

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.

Each student will co-lead one seminar during the semester in a group of 2.

Please email the instructor with your top three preferred seminar dates (in order of preference) no later than Tuesday, September 05. 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 September 07 by rolling a die.

Guest Lectures

Cătălin will be traveling to the Psychonomic Society Annual Meeting between November 13 – November 20. As such, we will have two guest lectures on Tuesday, November 14 and Thursday, November 16. 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

Course Learning Objectives

  1. Develop an in-depth understanding of foundational and state-of-the-art findings in major subtopics 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) and neuromodulation methodologies (TMS, tDCS, neurofeedback).
  3. Demonstrate a working understanding, including their strengths and limitations, of advanced computational techniques for measuring information content in human neural patterns of activity (MVPA, CNNs, HMMs).
  4. Explain how information about perceived external stimuli and internal mental states is encoded in and decodable from neural patterns of activity in the human brain.
  5. 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.
  6. Develop (or improve) the ability propose novel questions to advance current state-of-the-art in a sub-topic of human cognitive neuroscience.
  7. Generate an appropriate investigation plan (experimental design, measurements, analysis) for a novel scientific question in the subfield of human cognitive neuroscience that includes a neuromodulation and/or a computational component.
  8. Interpret and evaluate new knowledge (e.g., scientific publications) related to human cognitive neuroscience from the perspective of how information is encoded in and decodable from neural patterns of activity in the human brain.
  9. Demonstrate improved ability to communicate both orally and in writing about interdisciplinary and computational aspects, as well as broader implications of, new findings in human cognitive neuroscience.

Evaluation

Seminar Leadership: 30%

  • Presentation & moderation (when co-leading seminar discussion): 10%
    • Present assigned paper for 20-25 min.
    • Moderate discussion, answer questions, keep topic on track, help unify points of view
  • Write-up (when co-leading seminar discussion): 20%
    • Write-up: 3-4 pages; critique paper 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 Wednesday, December 20, 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.

Inclusive Class Policy

Please know that this classroom respects and welcomes students of all backgrounds and abilities— including their race, ethnicity, religion, gender identification, sexual orientation, socio-economic status, political affiliation, and national identity. As members of an inclusive learning community, we will strive to model the speech and behaviors conducive to authentic open discussion of frequently complex issues. Like all courses, this course also has its entry point into debate. It is important to understand that students need not embrace the course position in order to be successful in it. You are encouraged to speak up in class for optimal sharing and reflection on a diversity of individual perspectives, and I invite you to talk with me about any concern or situation that affects your ability to fully participate in class activities or to complete your work successfully

Disability Resources

We encourage you to talk with the instructor about any concern or situation that affects your ability to complete your academic work successfully. Students requiring accommodations should contact the Office of Disability Resources in Taylor Hall (email: disability@rochester.edu, website; phone: 585-276-5075).