Jörn Diedrichsen

photo of Dr Diedrichsen.

Professor

Office: Middlesex College 415
Tel:519-661-2111 ext. 86994
Email: jdiedric@uwo.ca

Personal Web Page: www.diedrichsenlab.org
Research Group: Computational Brain Sciences
Social Media: @diedrichsenlab

 The Diedrichsen Lab works on the development and application of modern Data Science techniques for the analysis of neuroscientific data such as human functional imaging, neuronal recording, and behavioral data. He received his graduate degrees in Neuroscience and Statistics from UC Berkeley, and is leading the development of the Data Science program at Western University.

Research Interests

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.

 

Selected Publications

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

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

  3. 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.

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

  5.  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. 

  6.  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

 

Teaching

Courses taught in 2020/21:
  • CS4414B: Introduction to Data Science

  •  IS2002B: Big Data and Mathematical Modelling

Awards

  • 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)