CiNet Monthly Seminar

April 20 (Mon.), 2026
14:00-15:30 (JST)
at the Conference Room in the CiNet bldg and online.

For online participation, please sign up [HERE] by noon on April 17.
For on-site particiation, please come to the Conference Room on the 1st floor of the CiNet bldg directly.

If any information is missing, you may not be able to participate. Please do not use an abbreviation for your affiliation.
We will send you the access information on April 17.

ーーーーーーーーーー

Talk title: How do cerebellum and neocortex work together across functional domains?

Jörn Diedrichsen
Professor
University of Western Ontario
Canada

Abstract:
The human cerebellum is engaged in a wide variety of motor and cognitive tasks. How each of the functional regions in the cerebellum interacts with its neocortical counterparts and how it uniquely contributes to function, however, is still unknown. I will present recent work from our lab that addresses this question using a wide-spectrum functional imaging approach, employing large batteries of tasks in single participants to map functional specialization within the cerebellum and the patterns of cortico-cerebellar connectivity in health and disease.

ーーーーーーーーーー

Talk title: Generalized prediction errors in the human cerebellum

Samuel D. McDougle
Assistant Professor
Yale University
USA

Abstract:
One enduring mystery is how exactly the cerebellum supports nonmotor computations in the mind. My lab has begun to explore the idea that cerebellar contributions to nonmotor tasks may involve the same computational principles observed in cerebellar sensorimotor computations. I will present recent neuroimaging results pointing to nonmotor prediction errors in ‘cognitive’ regions of the human cerebellum during learning. We observe these signals in both reinforcement learning (RL) and statistical learning (SL) contexts. In the latter case, we uncover a computational double dissociation between hippocampal versus cerebellar contributions to SL. Moreover, RL and SL teaching signals in the cerebellum appear to share constraints with cerebellar sensorimotor computations, namely a preference for sub-second temporal intervals between associated events. These results expand our understanding of the computational functions of the human cerebellum and blur the lines between motor learning and cognition.

Host : Atsushi Yokoi