Neuronal dynamics : from single neurons to networks and models of cognition / Wulfram Gerstner [and three others].
Gerstner, Wulfram| Call Number | 612.8 |
| Author | Gerstner, Wulfram, author. |
| Title | Neuronal dynamics : from single neurons to networks and models of cognition / Wulfram Gerstner [and three others]. |
| Physical Description | 1 online resource (xi, 577 pages) : digital, PDF file(s). |
| Notes | Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
| Summary | What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience. It covers classical topics, including the Hodgkin-Huxley equations and Hopfield model, as well as modern developments in the field such as Generalized Linear Models and decision theory. Concepts are introduced using clear step-by-step explanations suitable for readers with only a basic knowledge of differential equations and probabilities, and are richly illustrated by figures and worked-out examples. End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study. The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study. |
| Subject | NEUROBIOLOGY. Neural networks (Neurobiology) COGNITIVE NEUROSCIENCE. |
| Multimedia |
Total Ratings:
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| Summary | What happens in our brain when we make a decision? What triggers a neuron to send out a signal? What is the neural code? This textbook for advanced undergraduate and beginning graduate students provides a thorough and up-to-date introduction to the fields of computational and theoretical neuroscience. It covers classical topics, including the Hodgkin-Huxley equations and Hopfield model, as well as modern developments in the field such as Generalized Linear Models and decision theory. Concepts are introduced using clear step-by-step explanations suitable for readers with only a basic knowledge of differential equations and probabilities, and are richly illustrated by figures and worked-out examples. End-of-chapter summaries and classroom-tested exercises make the book ideal for courses or for self-study. The authors also give pointers to the literature and an extensive bibliography, which will prove invaluable to readers interested in further study. |
| Notes | Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
| Subject | NEUROBIOLOGY. Neural networks (Neurobiology) COGNITIVE NEUROSCIENCE. |
| Multimedia |