Titlebook: Why Brains Don‘t Compute; Dale Purves Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Natur

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filial

Exploit

AnglesAnother challenge in rationalizing geometrical percepts empirically is the way we perceive angles made by two straight lines that meet at a point. Like the apparent length of lines measured with a ruler, intuition suggests that angles should scale directly with measurements made with a protractor. This is not, however, what we see.

abduction

最高峰

Color PsychophysicsPerhaps the ultimate challenge for any theory of color vision is rationalizing the complex relationships of hue, saturation, and lightness seen by observers as these parameters are varied. This chapter provides some examples of how empirical ranking can explain these perceptual functions, whereas algorithmic computation cannot.

分解

博识

Dale PurvesExamines the key differences between how brains and machines process information.Addresses how experience generated by the brain is related to our physical world.Encourages readers to consider the con

使闭塞

偏离

Codingent, programming. In addition to the logical, mathematical, and electronic advances that led to today’s computational devices, the ways of getting information into, through, and out of computers are fundamental. For present purposes, the key question is whether nervous systems also need a code and if so, what is it.

外面

Resurrection of Neural Networks mathematical feedback technique called “back propagation.” This advance introduced a way of continuously modifying the weights of network connections based on feedback from the network outputs. Enthusiasm for this approach continues unabated today because, at least in part, this is what brains seem to be doing.