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Full Description
This book is designed as an introduction to neural dynamics through an intuitive exploration of fundamental "dynamic motifs" - the recurring dynamical concepts essential for understanding computational neuroscience. This concise, hands-on guide bridges the gap between mathematics and neuroscience, providing clear explanations of the key dynamical systems concepts that appear repeatedly in the computational/mathematical neuroscience literature.
Key Features:
Geometric and intuitive descriptions that minimize mathematical formality while preserving clarity Interactive "Explorations" that reinforce concepts through computer-based exercises Complete solutions to all Explorations, allowing for self-guided learning
Accessible approach suitable for both experimental neuroscientists and mathematicians
Focused coverage of essential concepts that serve as building blocks for understanding complex neural models
This book serves as an ideal entry point into computational neuroscience for two distinct audiences: experimental neuroscientists seeking to understand computational techniques for collaboration, and mathematicians or mathematics students looking to apply their knowledge to neuroscience. Through its unique combination of concise text and hands-on exploration, readers will quickly develop the knowledge and skills needed to navigate the computational neuroscience literature with confidence.
Contents
1 Introduction. 2 Excitability. 3 Bistability. 4 Saddle-node bifurcations. 5 Periodicity. 6 Coalescence of stable and unstable limit cycles. 7 The birth/death of tonic spiking with zero frequency. 8 Bursting oscillations. 9 Mean field models. 10 Additional resources. 11 Appendices. 12 Solutions to Explorations.
