Jörn Diedrichsen

We develop and apply data analytic techniques to understand how the human brain works. Our work focusses on understanding how the brain learns and produces complex motor skills, such a playing an instrument. We also study how the human cerebellum contributes to mental function across a wide range of cognitive domains. The lab focusses on statistical and computational techniques for the analysis of functional imaging, neuronal recording, and behavioral data.

1. Nettekoven, C., Zhi, D., Shahshahani, L., Pinho, A., Saadon-Grosman, N., Buckner, R., Diedrichsen, J. (2024). A hierarchical atlas of the human cerebellum for functional precision mapping. Nat. Commun., 15(1), 8376.

2. King, M., Shahshahani, L., Ivry, R., Diedrichsen, J. (2023). A task-general connectivity model reveals variation in convergence of cortical inputs to functional regions of the cerebellum. eLife, 12.

3. Berlot, E., Popp, N. J., & Diedrichsen, J. (2020). A critical re-evaluation of fMRI signatures of motor sequence learning. ELife, 9.

4.  Kriegeskorte, N., Diedrichsen, J. (2019). Peeling the onion of brain representations. Annual Review of Neuroscience.

5. King, M., Hernandez-Castillo, C.R., Poldrack, R. A., Ivry, R., Diedrichsen, J. (2019). Functional Boundaries in the Human Cerebellum revealed by a Multi-Domain Task Battery. Nature Neuroscience.

6.  Yokoi, A., Diedrichsen, J. (2019). Neural Organization of Hierarchical Motor Sequence Representations in the Human Neocortex. Neuron. 

7.  Diedrichsen, J., Yokoi, A., & Arbuckle, S. A. (2018). Pattern component modeling: A flexible approach for understanding the representational structure of brain activity patterns. Neuroimage. 180(Pt A), 119-133. 

8.  Diedrichsen, J., & Kriegeskorte, N. (2017). Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. PLoS Comput Biol. 

    

   For a complete list, see: http://www.diedrichsenlab.org/publications.htm

Undergraduate Chair for Data Science

Courses taught:

• Data Science 2000: Introduction to Data Science

• Faculty of Science Award for Excellence in Undergraduate Teaching (2023)

• Fallona Family Interdisciplinary Science Award (2023)

• Western Research Chair for Computational Neuroscience

• Scholar Award for Understanding Human Cognition, James S McDonnell Foundation

• American Psychological Association (APA) Distinguished Scientific Award for Early Career Contribution to Psychology in the area of Perception & Motor Performance (2007)