The dynamics of memory context dependent updating who is beck oliver dating

The main dynamical assumption is the asymptotic equipartition (Shannon-Mc Millan-Breiman) property of information theory.

This, along with Egorov's Theorem on uniform convergence, lets me build a sieve-like structure for the prior.

The asymptotics of Bayesian updating with mis-specified models or priors, or non-Markovian data, are far less well explored.

Here I establish sufficient conditions for posterior convergence when all hypotheses are wrong, and the data have complex dependencies.

An appendix sketches connections between these results and the replicator dynamics of evolutionary theory.

“A good metaphor is something even the police should keep an eye on.” – G. Lichtenberg Although the brain-computer metaphor has served cognitive psychology well, research in cognitive neuroscience has revealed many important differences between brains and computers.

Similarly, there does not appear to be any central clock in the brain, and there is debate as to how clock-like the brain’s time-keeping devices actually are.Much is now known about the consistency of Bayesian updating on infinite-dimensional parameter spaces with independent or Markovian data.Necessary conditions for consistency include the prior putting enough weight on the correct neighborhoods of the data-generating distribution; various sufficient conditions further restrict the prior in ways analogous to capacity control in frequentist nonparametrics.For example, one of the primary mechanisms of information transmission appears to be the rate at which neurons fire – an essentially continuous variable.Similarly, networks of neurons can fire in relative synchrony or in relative disarray; this coherence affects the strength of the signals received by downstream neurons.

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Difference # 3: The brain is a massively parallel machine; computers are modular and serial An unfortunate legacy of the brain-computer metaphor is the tendency for cognitive psychologists to seek out modularity in the brain.

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