Understanding Brain Networks from a Complex Systems Perspective

Understanding the Brain as a Complex System (2023-09-05 ~ 2023-11-28)
Room: 500-304 | Tuesdays 17:00 ~ 19:50 | Syllabus
Speakers: Ziseok Lee, Yunseo Chang, and Taehoon Kim

The seminar is about how we can think about the brain as a highly complex network system

    # In the first half of the seminar, we critically examine the reductionist perspective—which attempts a one-to-one mapping of brain regions to discrete functions—and its limitations, introducing a complex systems framework.

  1. Orientation and Understanding the Anatomical Architecture of the Brain (2023-09-05)

    2. We introduce the overall trajectory of the seminar and gain a foundational understanding of the brain's anatomical architecture.
    Reference : The Entangled Brain Ch.2
    Lecture Materials : OT, Anatomy of the Brain, Session 1. Anatomical Architecture of the Brain, Quiz 1

  2. The Minimal Brain + Cognition (2023-09-12)

    3. We explore the brain's input and output circuits through the 'minimal brain' concept, conduct cognitive experiments, and investigate cognition as it unfolds in the prefrontal cortex. Additionally, we briefly introduce brain network analysis techniques.
    Reference : The Entangled Brain Ch.3, 7
    Lecture Materials : Minimal Brain, Cognition, Quiz 2
    Online Experiments : Wisconsin Card Sorting, Stroop Task

  3. Emotion and Motivation from a Neuroscience Perspective (2023-09-19)

    4. We examine the relationships between the autonomic nervous system and the hypothalamus, fear and the amygdala, and motivation and the midbrain. We also explore temporal difference learning, a basic reinforcement learning algorithm.
    Reference : The Entangled Brain Ch.5, Theoretical Neuroscience Ch.9
    Lecture Materials : Emotion (Part 1), Quiz 3

  4. Emotion and Fear from a Neuroscience Perspective (2023-09-26)

    5. We study how the cingulate gyrus, insula, and orbitofrontal cortex dynamically interact with other regions to weave together emotional states. As a specific example, we examine fear extinction. We also explore nonlinear systems described by simple ordinary differential equations.
    Reference : The Entangled Brain Ch.6, 11
    Lecture Materials : Emotion (Part 2), Unlearning Fear, Matlab Simulation

  5. Complex Systems and Midterm Review (2023-10-10)

    6. By introducing the history of complex systems science, we naturally guide a paradigm shift in students' thinking. We provide a brief overview of complex systems and discuss their ongoing application in neuroscience.
    Reference : The Entangled Brain Ch.12, Chaos (James Gleick, 1987)
    Lecture Materials : Complex System, Quiz 5

    # In the second half of the seminar, we start from the level of single neurons to learn the mathematical modeling of brain networks, accompanied by practical coding exercises.

  6. The Hodgkin-Huxley Model (2023-10-31)

    7. We introduce biological examples of single neurons alongside the Hodgkin-Huxley model.
    Reference : Theoretical Neuroscience Ch.7
    Lecture Materials : Hodgkin-Huxley Model, Quiz 6

  7. NEURON Coding Practice (2023-11-07)

    8. After implementing the Hodgkin-Huxley model through code, we extend the model. Practical exercises are conducted utilizing the Python NEURON library.
    Reference : Theoretical Neuroscience, Differential Equations, Dynamical Systems, and an Introduction to Chaos
    Lecture Materials : Numerical Methods, HH Model Simulation

  8. Entropy, Mutual Information, and Spike Trains (2023-11-14)

    9. We study entropy, mutual information, and spike trains. Applying the concept of information entropy, we understand how information is transferred between neurons via spike trains.
    Reference : Theoretical Neuroscience Ch.4
    Lecture Materials : Entropy and Spike Trains, (Supplement) Information Theory, Quiz 8

  9. Network Theory and Brain Networks (2023-11-21)

    10. We learn the foundational principles of network theory and examine the topological characteristics of brain networks.
    Reference : Networks: An Introduction Part 2 (Newman, 2010), The Entangled Brain Ch.10
    Lecture Materials : Network Theory and Brain Network, Quiz 9

  10. Student Independent Presentations (2023-11-28)

    11. Student presentations are conducted based on class votes for the individual reports they wish to hear. The reports are written by delving deeper into the topics that left the most profound impression on each student during the course.
    Reference : Preparation for Personal Essay/Independent Presentation

Textbooks and References