The example Wolpert uses is when you used to tune a radio there would be a

The example wolpert uses is when you used to tune a

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The example Wolpert uses is when you used to tune a radio there would be a crack noise on the station that you wanted to hear. That crack sound is the noise, in this case it is something that corrupts the signal. 4. Discuss the theory Wolpert uses to convince us that the brain goes through a great deal of effort to reduce the negative consequences of noise and variability. a. Wolpert uses the Bayesian decision theory, which is a popular framework in machine leaning and statistics. It is a way to think about how the brain handles uncertainty. The idea of the theory is that you make an inference then act on it.
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In this case inference is beliefs. In the Bayesian decision theory, there are two sources of information that you can use to create your belief. There are two types of data in this case. There is sensory input and then there's another source of information which is prior knowledge. You gain knowledge through life in memories, and the point about the Bayesian decision theory is it gives you the mathematics of the best way to combine the knowledge from your memories with sensory evidence to create new beliefs. 5. Wolpert says that there's one very clear example in which a sensation you generate feels very different than if another person generated it. Please explain this example and how Wolpert explored it and whether he saw the experiment as a success or not.
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  • Winter '19
  • Jane Smith

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