What is it about?

The brain is a predictive machine that continuously anticipates what happens next. A crucial aspect of predictive behavior is to not only anticipate what happens next, but also when. Consider the simple act of a payment by card. After punching in a code and pressing “OK,” we wait for a confirmatory tone so we can remove the card. If the connection is slow, soon we will start wondering if something is off. Based on our past experiences with card transactions, we are prepared to remove the card after a certain interval. This is one of the many examples of how we use past experiences to anticipate future events. A trait that is simply convenient in the case of a payment by card, but essential for an athlete awaiting the starting shot.

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Why is it important?

The puzzle is to explain a wealth of empirical phenomena showing that we tune our temporal expectations based on past experiences under a common theoretical umbrella. What are the underlying cognitive mechanisms giving rise to such expectations? Despite 100 years of research to this topic no theory has succeeded in deciphering the cognitive mechanisms underlying temporal preparation.


I enjoy that this project brings together different domains of Experimental Psychology: ranging from principles of Pavlovian-like classical conditioning, time perception, to episodic memory. In this way, I think we offer an insightful solution to a long-standing theoretical puzzle. It is satisfying to have a cognitive-based explanation of this seemingly effortless, implicit cognitive process that continuously generates predictions of what happens next. Conventional theories do not only fall short in their explanation, but they also lack cognitive interpretability as they rely on abstract, mathematical rules.

Josh Manu Salet
Rijksuniversiteit Groningen

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This page is a summary of: FMTP: A unifying computational framework of temporal preparation across time scales., Psychological Review, April 2022, American Psychological Association (APA), DOI: 10.1037/rev0000356.
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