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Is the right brain hemisphere more analog and Bayesian?

Oliver Schultheiss writes:

I recently commented one of your posts (I forgot which one) with a reference to evidence suggesting that the right brain hemisphere may be in a better position to handle numbers and probabilistic predictions. Yesterday I came across the attached paper by Filipowicz, Anderson, & Danckert (2016) that may be of some interest to you. It suggests at least 2 things:

First, there is actually a lot more research than I knew about that shows that the right hemisphere is better at intuitive statistics. If parts of it are missing, people have severe problems adapting to probability (changes) and making the right guesses. You don’t get that when the left hemisphere is compromised. In fact, the right hemisphere appears to work like a real Bayesian, with prior beliefs and updating as the data come in (s. Figures 7, 8, and 9). In general, it adapts in a graded, analog fashion to incoming information. This in stark contrast to the left hemisphere, which of course is also capable of predicting what happens next, but does so in a much more digital, either/or, black/white manner (or should I say: significant/non-significant manner?). The approach to statistics that you espouse on your blog and in your books (e.g., Regression & other stories) is decidedly one that is more closely aligned to how the right hemisphere deals with probability and uncertainty than the approach of the left hemisphere.

Second, the authors provide a wonderful demonstration of how we deal behaviorally with probability and uncertainty using the game Plinko (for a demo please see here: — but you need PsychPy to run it). It’s illustrated in Figure 7 and requires players to first state their prior beliefs about how a ball will fall through a grid of pins and how often it will end up in a variety of bins underneath the grid. You can then study how people update their beliefs as the data from the first test runs come in. The beauty of this example is, of course, that the actual probability distribution that emerges over time as close to a Gaussian. But that’s not what everybody expects. Some peoples’ priors are bimodal, some believe in a rather jagged kind of distribution, and I guess other priors are possible too. This might be a nice teaching tool for the kind of intuitive Bayesianism our right hemisphere engages in (and which vanishes or becomes distorted after right-hemisphere damage).

Perhaps you’ve already seen either the paper or the Plinko game before. I was very impressed by this review paper, because I hadn’t been aware how much is already known about hemispheric differences in statistical reasoning.

I know nothing about this! But it seems interesting, so I’ll share it. I hadn’t thought about Regression and Other Stories as being a right-brain-style book!

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