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In simple perceptual decisions the brain has to identify a stimulus based on noisy sensory samples from the stimulus. Basic statistical considerations state that the reliability of the stimulus information, i.e., the amount of noise in the samples, should be taken into account when the decision is made. However, for perceptual decision making experiments it has been questioned whether the brain indeed uses the reliability for making decisions when confronted with unpredictable changes in stimulus reliability. We here show that even the basic drift diffusion model, which has frequently been used to explain experimental findings in perceptual decision making, implicitly relies on estimates of stimulus reliability. We then show that only those variants of the drift diffusion model which allow stimulus-specific reliabilities are consistent with neurophysiological findings.
Previous theoretical and experimental work on optimal decision-making was restricted to the artificial setting of a reliability of the momentary sensory evidence that remained constant within single trials. The work presented here describes the computation and characterization of optimal decision-making in the more realistic case of an evidence reliability that varies across time even within a trial. It shows that, in this case, the optimal behavior is determined by a bound in the decision maker's belief that depends only on the current, but not the past, reliability. We furthermore demonstrate that simpler heuristics fail to match the optimal performance for certain characteristics of the process that determines the time-course of this reliability, causing a drop in reward rate by more than 50%. Papers published at the Neural Information Processing Systems Conference.
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.
Consumer Reports said that it would no longer recommend Microsoft's Surface laptops and tablets because of "poor predicted reliability" compared to other brands, based on its surveys. Now Microsoft has responded, with a statement saying that it is "disappointed" in the decision and providing some of its own data. We are proud of our products and the amazing things our customers are doing with them. We stand firmly behind the quality and reliability of the Surface family of devices, and I can confidently tell you there has never been a better time to buy a Surface. The company says it has "learned a lot" while building Surface devices, with 1-2 failure and actual return rates for the Surface Pro 4 and Surface Book that are "significantly" lower than the 25 percent number CR found.