Analysis of Neural Data - download pdf or read online

By Robert E. Kass, Uri T. Eden, Emery N. Brown

ISBN-10: 1461496012

ISBN-13: 9781461496014

ISBN-10: 1461496020

ISBN-13: 9781461496021

Continual advancements in info assortment and processing have had a huge effect on mind examine, generating information units which are usually huge and intricate. through emphasizing a couple of basic ideas, and a handful of ubiquitous options, Analysis of Neural Data presents a unified therapy of analytical tools that experience develop into crucial for modern researchers. in the course of the booklet rules are illustrated with greater than a hundred examples drawn from the literature, starting from electrophysiology, to neuroimaging, to behaviour. by way of demonstrating the commonality between numerous statistical techniques the authors give you the an important instruments for gaining wisdom from assorted sorts of info. geared toward experimentalists with purely high-school point arithmetic, in addition to computationally-oriented neuroscientists who've restricted familiarity with facts, Analysis of Neural Data serves as either a self-contained creation and a reference work.

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1978). 5 All models are wrong, but some are useful. The simple representation in Fig. 7 is incomplete and may be somewhat misleading. Most importantly, while it is true that there are standard procedures for model assessment, some of which we will discuss in Chapter 10, there is no uniformly-applicable rule for what constitutes a good fit. Statistical models, like scientific models, are abstractions and should not be considered perfect representations of the data. ” Neither model is perfectly accurate—in fact, every scientific model fails4 under certain conditions.

The relative frequency of data higher than the median is about the same as that of corresponding data lower than the median by an equal amount. Symmetric and unimodal data distributions are easier to describe concisely with probability distributions and the normal distribution, discussed in Chapter 5, is1 unimodal and symmetrical (it is often called “the bell-shaped curve”). It is very rare to find a set of data that, on close inspection, may be described accurately by a normal distribution, but it is common to find unimodal and symmetric data distributions that are roughly normal-looking.

S. with a pair of cards showing identical green line drawings of a house, except that on one of the cards bright red flames were depicted on the left side of the house. S. both cards, one above the other (the one placed above being selected at random), and asked her to choose which house she would prefer to live in. She thought this was silly “because they’re the same” but when forced to make a response chose the non-burning house on 14 out of 17 trials. This would seem to indicate that she did, in 10 1 Introduction fact, see the left side of the drawings but was unable to fully process the information.

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Analysis of Neural Data by Robert E. Kass, Uri T. Eden, Emery N. Brown

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