When THREE or 3 makes 3 harder to RSVP: Negative priming in rapid serial visual presentation

William James famously said that the world is “one great blooming, buzzing confusion” to an infant whose sensory apparatus is “assailed by eyes, ears, nose, skin, and entrails at once.” As adults, we continue to be assailed by stimuli, but out attentional apparatus permits us to deal with the blooming and buzzing confusion quite well. […]

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What’s in the eyes of a dog? Understanding canine vision

Sir Winston Churchill once made the following statement: “I am fond of pigs. Dogs look up to us. Cats look down on us. Pigs treat us as equals.” While Sir Churchill’s perspective may be indicating the direction of a partnership, it also reminds us that we must be mindful of the biases and assets that […]

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Being fooled (or not) by Hyperrealistic masks: When “Five blimps” can reveal the Dark Knight

In October 2010, an elderly white man boarded an Air Canada flight bound from Hong Kong to Vancouver. During the flight, this passenger visited the bathroom and emerged an Asian man in his early 20s. No, this wasn’t an episode of Scooby Doo, this was an actual case where a hyperrealistic mask was used to […]

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Do my eyes deceive me or is this a cold? Using eye movement to evaluate symptom processing

There are a number of factors that make us fundamentally human. We eat. We sleep. We experience emotions. And unfortunately at some point, we all become sick. Where we tend to diverge is how we process and treat our sicknesses. Some people run immediately to the doctor’s office, or if you are anything like me, […]

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The ABC in #BayesInPsych: Approximating likelihoods in simulation models

(This post was co-authored with Brandon Turner). Sharon Bertsch McGrayne’s 2012 book, The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy, traces the difficulties that statisticians and empirical researchers alike have had in embracing Bayesian methods. Despite the obvious […]

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#BayesInPsych: Spiking a slab with sleepless pillow talk and prior inequalities

I recently finished reading Suzanne Buffam’s, A Pillow Book. This is a book of non-fiction poetry about thoughts and musings that may enter the mind as one drifts off to sleep, ranging from the historical consideration of pillows to comprehensive lists of sleeping aids. I’ve spent more than a few nights drifting off to sleep considering […]

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We often know more than we think: Using prior knowledge to avoid prior problems #BayesInPsych

One of the unique features of Bayesian statistical and computational modelling is the prior distribution. A prior distribution is both conceptually and formally necessary to do any sort of Bayesian modelling. If we are estimating the values of model parameters (e.g., regression coefficients), we do this by updating our prior beliefs about the parameter values […]

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The four horsemen of #BayesInPsych

I see four benefits to the use of Bayesian inference:  Inclusion of prior information.  Regularization.  Handling models with many parameters or latent variables.  Propagation of uncertainty. Another selling point is a purported logical coherence – but I don’t really buy that argument so I’ll forget that, just as I’ll also set aside philosophical objections against […]

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From classical to new to real: A brief history of #BayesInPsych

The #BayesInPsych Digital Event kicked off yesterday and as the leading Guest Editor of the special issue of Psychonomic Bulletin & Review, I take this opportunity to provide more context for this week’s posts. The simple act of deciding which among competing theories is most likely—or which is most supported by the data—is the most […]

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