灯泡
发表于 2025-3-23 10:34:36
2193-9349 uitive and simple as possible and provides routes of explana.Computational Neuroscience - A First Course. provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level.
滔滔不绝的人
发表于 2025-3-23 15:57:20
Textbook 20131st editionunderstanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey thr
Expertise
发表于 2025-3-23 18:31:14
Superlattices and Other Heterostructuresn-Huxley theory. The propagation of neural signals along axons and dendrites is based on the cable equation which is also discussed in this chapter. Mathematical background is mostly from the theory of dynamical systems.
Vertebra
发表于 2025-3-23 22:13:58
,Neue Trends — Viele Mißverständnisse,th ideas combine in the convolution theorem, stating that the convolution of two functions can also be expressed as the simple product of the respective Fourier transforms. This is also the reason why linear shift-invariant systems are often considered “filters” removing some frequency components from a signal and passing others.
领先
发表于 2025-3-24 03:07:17
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curettage
发表于 2025-3-24 10:30:12
Fourier Analysis for Neuroscientists,th ideas combine in the convolution theorem, stating that the convolution of two functions can also be expressed as the simple product of the respective Fourier transforms. This is also the reason why linear shift-invariant systems are often considered “filters” removing some frequency components from a signal and passing others.
defile
发表于 2025-3-24 14:41:46
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投票
发表于 2025-3-24 18:05:05
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没血色
发表于 2025-3-24 20:12:09
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Innocence
发表于 2025-3-25 00:52:31
https://doi.org/10.1007/978-3-030-18222-9pulation coding where each stimulus is represented by the activities of a group, or population, of neurons. The first part of this chapter explores the consequences of population coding for neural information processing. In the second section, we study the fact that neighboring neurons in the cortic