Computational Cognitive Neuroscience

  1. Students must complete the departmental common graduate curriculum in Psychology, including courses, research requirements and mentored teaching experiences.
  2. Students must take PSYC 43030 Introduction to Python Programming in the Behavioral Sciences (offered in 2024-25); this requirement will be waived if student has sufficient programming experience.
  3. Two Core Neuroscience courses. From the four options below, students should complete two courses.
    • CPNS 30000 Cellular Neurobiology
    • CPNS 30107 Behavioral Neuroscience
    • CPNS 30116 Survey of Systems Neuroscience
    • CPNS 34231 Methods in Computational Neuroscience
  4. Three advanced courses, one of which will be required to be a breadth course outside of the student’s main discipline. These courses will also fulfill the breadth courses required as part of the common graduate curriculum. Eligible courses will include all graduate level seminars taught by faculty in the Psychology Department, as well as a list of courses in other departments that are deemed relevant for the computational cognitive neuroscience curriculum. These outside courses will provide additional opportunities for computational and analytic training.

    Below is a list of the “advanced courses” in computational cognitive neuroscience students can choose from (note this is not a complete list):
  • PSYC 31900 The Neuroscience of Narratives. (Leong)
  • PSYC 33910 Hormones, Brains, and Behavior (Prendergast)
  • PSYC 34133 Neuroscience of Seeing. (Wei, Maunsell, Sherman, Shevell)
  • PSYC 34810 Neuroeconomics. (Bakkour)
  • PSYC 37400 Long Term Memory.  (Gallo)
  • PSYC 37250 Foundations of Neuroscience: Historical Perspectives.  (Kay)
  • PSYC 41210 Psychophysiology: Methods, Concepts and Applications.  (Norman)
  • PSYC 42350 Advanced Topics in Human Neuroimaging.  (Bainbridge, Rosenberg)
  • PSYC 42570 Integrating the Real World into Perception and Memory.  (Bainbridge)
  • PSYC 42950 Memory and Decision Making.  (Bakkour)
  • PSYC 43110 Affective Neuroscience. (Norman)
  • PSYC 43130 Stress and the Social Brain. (Norman)
  • PSYC 43760 Sensitive Periods: How the Timing of Experience Alters Its Effect (London)
  • PSYC 43780 Basics of Conducting EEG and ERP Research.  (Vogel)
  • PSYC 43921 Current Topics in Working Memory.  (Awh)
  • PSYC 44550 Cognitive Neuroscience Core Course. (Awh/Vogel)
  • PSYC 45500 Cognitive and Social Neuroscience of Aging.  (Gallo)
  • PSYC 46050 Principles of Data Science and Engineering for Laboratory Research.  (Yu)
  • PSYC 46650 Genes and Behavior. (London)

  Other computational courses not taught in Psychology (not a complete list):

  • MACS 30121 - Computer Science with Social Science Applications 1
  • MACS 30000 - Perspectives on Computational Analysis
  • MACS 30123 - Large-Scale Computing for the Social Sciences
  • MACS 30500 - Computing for the Social Sciences
  • MACS 30124 - Computational Analysis of Social Processes
  • MACS 33002 - Introduction to Machine Learning
  • MACS 40100 - Big Data & Society
  • MACS 40400 - Computation and the Identification of Cultural Patterns
  • MACS 40800 - Unsupervised Machine Learning
  • MACS 51000 - Introduction to Causal Inference
  • MACS 31300 - AI Applications in the Social Sciences
  • MACS 37000 - Thinking with Deep Learning for Complex Social & Cultural Data Analysis
  • MACS 40101 - Social Network Analysis
  • CMSC 30900: Computers for Learning
  • CMSC 33281: Topics in Human Robot Interaction
  • CMSC 35300: Mathematical Foundations of Machine Learning
  • CMSC 35200-1: Deep Learning Systems
  • TTIC 31210: Advanced Natural Language Processing
  • TTIC 31230: Fundamentals of Deep Learning
  • TTIC 31220 - Unsupervised Learning and Data Analysis
  • TTIC 31020 - Introduction to Machine Learning
  • TTIC 31250: Introduction to the Theory of Machine
  • TTIC 31040: Introduction to Computer Vision
  • CPNS 34231 Methods in Computational Neuroscience (Kaufman)
  • BIOS 24232 Computational Approaches to Cognitive Neuroscience
  • CPNS 32111 Modeling and Signal Analysis for Neuroscientists
  • PSYC 36210 Mathematical Methods for Biological Sciences 1
  • PSYC 36211 Mathematical Methods for Biological Sciences 2