
Sign up to save your podcasts
Or


In this episode, Elizabeth chats with Dr. Kendrick Kay, an Associate Professor in Radiology at University of Minnesota, Twin Cities. He directs the Computational Visual Neuroscience Laboratory, and aims to understand brain function by combining cognitive neuroscience, functional MRI methods, and computational neuroscience. In this episode, Kendrick shares his work on the groundbreaking Natural Scene Dataset and discusses the behind-the-scenes considerations that went into its creation. He also outlines important points for brain scientists to think about when creating and using large-scale fMRI datasets, and shares parts of his journey as a scientist.
Discussed Papers in Podcast:
Kendrick’s website: http://cvnlab.net
Elizabeth’s: website: imelizabeth.github.io
Elizabeth’s BlueSky: @imelizabeth.bsky.social
Podcast BlueSky @StanfordPsyPod.bsky.social
Podcast Twitter @StanfordPsyPod
Podcast Substack https://stanfordpsypod.substack.com/
Let us know what you thought of this episode, or of the podcast! :) [email protected]
By Stanford Psychology5
44 ratings
In this episode, Elizabeth chats with Dr. Kendrick Kay, an Associate Professor in Radiology at University of Minnesota, Twin Cities. He directs the Computational Visual Neuroscience Laboratory, and aims to understand brain function by combining cognitive neuroscience, functional MRI methods, and computational neuroscience. In this episode, Kendrick shares his work on the groundbreaking Natural Scene Dataset and discusses the behind-the-scenes considerations that went into its creation. He also outlines important points for brain scientists to think about when creating and using large-scale fMRI datasets, and shares parts of his journey as a scientist.
Discussed Papers in Podcast:
Kendrick’s website: http://cvnlab.net
Elizabeth’s: website: imelizabeth.github.io
Elizabeth’s BlueSky: @imelizabeth.bsky.social
Podcast BlueSky @StanfordPsyPod.bsky.social
Podcast Twitter @StanfordPsyPod
Podcast Substack https://stanfordpsypod.substack.com/
Let us know what you thought of this episode, or of the podcast! :) [email protected]

43,673 Listeners

11,130 Listeners

4,275 Listeners

772 Listeners

112,105 Listeners

14,882 Listeners

5,554 Listeners

8,189 Listeners

15,663 Listeners

15,906 Listeners

2,181 Listeners

2,190 Listeners

2,944 Listeners