Calculus for Cognitive Scientists

Part I. Introductory Matter

1. Introduction
James K. Peterson

Part II. Quantitative Tools

2. Graham–Schmidt Orthogonalization
James K. Peterson

3. Numerical Differential Equations
James K. Peterson

Part III. Deriving the Cable Model

4. Biological Molecules
James K. Peterson

5. Ion Movement
James K. Peterson

6. Lumped and Distributed Cell Models
James K. Peterson

7. Time Independent Solutions to Infinite Cables
James K. Peterson

8. Time Independent Solutions to Finite and Half-Infinite Space Cables
James K. Peterson

Part IV. Excitable Neuron Models

9. A Primer on Series Solutions
James K. Peterson

10. Linear Partial Differential Equations
James K. Peterson

11. Simplified Dendrite—Soma—Axon Information Processing
James K. Peterson

12. The Basic Hodgkin–Huxley Model
James K. Peterson

Part V. Summing It All Up

13. Final Thoughts
James K. Peterson

Part VI. Advise to the Beginner

14. Background Reading
James K. Peterson

Avainsanat: Engineering, Computational Intelligence, Theoretical, Mathematical and Computational Physics, Mathematical Models of Cognitive Processes and Neural Networks, Artificial Intelligence (incl. Robotics), Computer Imaging, Vision, Pattern Recognition and Graphics