On how to cure brain diseases - with Nicole R...

While some models aim to explain qualitative features of brain activity, other aim to reproduce experimental data quantitatively. If so, model parameters must be adjusted to make the model predictions fit the experimental data. A complication is that in most neurobiological appli ...  Show more

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, ...  Show more

This book is available open access here. The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience (MIT Press, 2024), Mazviita Chirimuuta argues that the standard ways neuroscientists simplify the human brain to build models for their research purposes mi ...  Show more

Children who are being taught mathematics often balk at the idea of negative numbers, thinking them to be fictional entities, and often only learn later that they are useful for expressing opposite extremes of things, such as considering a debt an amount of money with a negative ...  Show more

Is complexity the new frontier of physics? How should we approach metaphysical uncertainty? What makes a great Physicist? These are just some of the questions covered in this Win-Win episode with the incredible Sean Carroll. Sean is a theoretical physicist and philosopher who ...

In this episode, Kyle does an overview of the intersection of graph theory and computational complexity theory. In complexity theory, we are about the runtime of an algorithm based on its input size. For many graph problems, the interesting questions we want to ask take longer an ...  Show more