Titlebook: Computational Neuroscience; A First Course Hanspeter A Mallot Textbook 20131st edition Springer International Publishing Switzerland 2013 A

灯泡

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

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

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

,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

curettage

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

投票

没血色

Innocence

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