Fundamentals of Computational Neuroscience 3rd Edition

Capture the brain’s logic with Fundamentals of Computational Neuroscience, 3rd Edition by Thomas Trappenberg — a definitive, accessible guide that bridges biology, mathematics, and computation for students, researchers, and engineers worldwide.

From the first page you’re drawn into clear explanations of how single neurons encode information, how synapses shape learning, and how networks give rise to perception and behavior. Trappenberg’s balanced approach introduces core mathematical tools — differential equations, probability, linear algebra — while grounding them in biological realism and practical modeling techniques. Chapters cover neuronal dynamics, synaptic plasticity, population coding, oscillations, and modern neural network models, making the text ideal for graduate and advanced undergraduate courses as well as for professionals entering neuro-inspired machine learning.

Readers benefit from lucid examples, intuitive visuals, and problem sets designed to build real computational intuition. The 3rd Edition reflects contemporary advances in computational neuroscience without overwhelming newcomers, positioning you to engage with current research and applications across neuroscience labs, engineering departments, and tech teams developing biologically inspired AI.

Whether you’re studying at a university in North America, Europe, Asia, or building skills for industry, this edition is a practical, rigorous companion. Elevate your understanding of how brains compute — add Fundamentals of Computational Neuroscience, 3rd Edition by Thomas Trappenberg to your library today and start turning complex neural theory into usable models.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.