NEUR 415, Theoretical Neuroscience, Spring 2003

Lectures, first 13 by Cox, next 13 by Gabbiani



Single Cell Models

Goal: Achieve a quantitative understanding of this cartoon

Attitude: "teaching physiology without a mathematical description of the underlying dynamical processes is like teaching planetary motion to physicists without mentioning or using Kepler's laws; you can observe that there is a full moon every 28 days, but without Kepler's laws you cannot determine when the next total lunar or solar eclipse will be" (Keener & Sneyd)
  1. Membrane conductance, capacitance & resting potential

    Notes. The first Assignment is due Tuesday January 21, in class.
  2. Linear ordinary differential equations, exact and numerical methods

    Notes
  3. The (patch) Hodgkin-Huxley Equations

    Notes The second Assignment is due Tuesday January 28, in class.
  4. Phase-Plane Methods for Reduced Systems

    Notes
  5. The Compartmental Passive Fiber

    Notes The third Assignment is due Tuesday February 4, in class.
  6. The Continuum Passive Fiber

    Notes The fourth Assignment is due Tuesday February 11, in class.
  7. Appending a Soma and adding branches

    Notes The fifth Assignment is due Tuesday February 18, in class.
  8. The Synapse

    Notes The sixth Assignment is due Tuesday February 25, in class.
  9. AMPA & NMDA receptors

    Notes
  10. Spinal Calcium & Synaptic Plasticity

    Notes

Neuronal Coding

  1. Quantal hypothesis and models of synaptic release

    Lecture material.
  2. Spontaneous activity and quantification of neuronal variability

    Lecture material and seventh assignment plus supporting material.
  3. Integration of synaptic inputs in dendritic trees

    Lecture material and eigth assignment plus supporting material. Assignment due Thursday, April 3, in class.
  4. Simplified models of neuronal activity

    Lecture material and assignment 9. Due Thursday, April 10, in class.
  5. Encoding of stimuli by instantaneous firing rate

    Lecture material and assignment 10. Due Thursday, April 17, in class.
  6. Models of V1 simple and complex cells

    Lecture material and assignment 11. Due Thursday, April 24, in class.
  7. Reverse-correlation methods for receptive field estimation

    Lecture material
  8. Detection of motion and ROC analysis


    and
  9. Encoding of time-varying stimuli and linear estimation methods

    Lecture notes
  10. Final Exam

    Final Exam Description