Unsupervised Thinking
a podcast about neuroscience, artificial intelligence and science more broadly

Wednesday, November 30, 2016

Episode 15: "Just-So" Stories of Bayesian Modeling in Psychology

In the late 1700s, English minister Thomas Bayes discovered a simple mathematical rule for calculating probabilities based on different information sources. Since then Bayesian models for describing uncertain events have taken off in a wide variety of field, not the least of which is psychology. This Bayesian framework has been used to understand far-reaching psychological processes, such as how humans combine noisy sensory information with their prior beliefs about the world in order to come to decisions on how to act.

But not everyone is riding the Bayesian train. In this episode, we discuss a published back and forth between scientists arguing over the use and merits of Bayesian modeling in neuroscience and psychology. First, though, we set the stage by describing Bayesian math, how it is used in psychology, and the significance of certain terms such as "optimal" (it may not mean what you think it does) and "utility". We then get into the arguments for and against Bayesian modeling, including its falsifiability and the extent to which Bayesian findings are overstated or outright confused. Ultimately, it seems the expansive power of Bayesian modeling to describe almost anything may in fact be its downfall. Do Bayesian models give us insight on animal brains and behaviors, or just a bunch of "just-so" stories?

We read:
Bayesian Just-So Stories in Psychology and Neuroscience

How the Bayesians Got Their Beliefs (and What Those Beliefs Actually Are):
Comment on Bowers and Davis (2012)

Is That What Bayesians Believe? Reply to Griffiths, Chater, Norris, and Pouget (2012)

And referenced a previous episode, the Unreasonable Effectiveness of Mathematics.

To listen to (or download) this episode, (right) click here.

As always, our jazzy theme music "Quirky Dog" is courtesy of Kevin MacLeod (incompetech.com) 

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