The cerebellar clock: predicting the present

Name of applicant

Lau Møller Andersen


Aarhus University


DKK 589,000



Type of grant

Reintegration Fellowships


My project is about how it comes about that humans are so adapt at predicting what is going to happen next and when it is going to happen? Being at a music concert, say, why and how do you know when the next beat of the drum is going to happen, and how are you able to time your clapping exactly with that beat? The common-sense answer tells us that it is due to the regularity of the drum beats leading up to the expected beat, but this just begs the question: how do we recognize it as a regularity at all? In this proposal, I venture the notion that the cerebellum functions as an internal clock for recognizing such regularities and keeping behaviour up to date with the environment.


The functions of the cerebellum are understudied even though evidence is amounting that the cerebellum is widely involved in cognition. Especially its timing aspects have been understudied since most earlier studies have relied on slow imaging modalities such as functional magnetic resonance imaging (fMRI). Learning if and how the cerebellum works as an internal clock monitoring the environment is important both from the perspective of basic science, but also from that of clinical science. Many movement disorders may be related to wrongful prediction of the environment, and present-day neuroscience is permeated by theories about how sensation and prediction may be two sides of the same coin. The results from this project are likely to inform both strands of science, basic and clinical.


The research will be conducted by testing healthy participants in the MEG (magnetoencephalography). Using this tool, I can study the timing aspect very precisely, since MEG measures and tracks changes in brain activity up to more than 5,000 times per second. I will furthermore collaborate with Professor Hämäläinen from Harvard University applying his cutting-edge methods on how to find activity in the cerebellum using MEG. Firstly, I will be using the highly detailed model of the cerebellum he and his group has created. It is based on ultra-high resolution ex vivo data, which allows for more precise source localization. Secondly, I will make use of a technique devised by Prof. Hämäläinen's group that suppresses cortical activity, thus leaving activity originating from the cerebellum.

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