On reproducibility of modeling and 10 years with the Potjans-Diesmann network model - with Hans Ekkehard Plesser - #37

About this episode

The episode discusses the importance of reproducibility in scientific research, particularly in computational neuroscience, featuring guest Hans Ekkehard Plesser.

Reproducibility is key for scientific progress. If research results cannot be reproduced and trusted, other researchers cannot build on them. Reproducibility is a challenge also in computational neuroscience, and today's guest has worked on how this can be remedied, for example, through standardized model description and model sharing. He also recently organised a workshop celebrating a decade with the (reproducible) Potjans-Diesmann neural network model, which has become an important community tool.

People in this episode

Host: Gaute Einevoll

Guest: Hans Ekkehard Plesser

Topics covered

• reproducibility
• computational neuroscience
• modeling
• neural networks
• scientific progress
• standardized model description

Keywords

• reproducibility
• computational neuroscience
• Potjans-Diesmann
• neural network model
• scientific progress
• model sharing
• standardized model description

Mentioned in this episode

Organizations: Potjans-Diesmann, Theoretical Neuroscience Podcast

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