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Theoretical Neuroscience Podcast
VetenskapLife Science

On the philosophy of simplification in computational neuroscience - with Mazviita Chirimuuta and Terrence Sejnowski - #29

1 tim 24 min•21 juni 2025

Computational neuroscientists rely on simplification when they make their models. But what is the right level of simplification?

When should we, for example, use a biophysically detailed model and when a simplified abstract model when modelling neural dynamics? What are the problems of simplifying too much, or too little? 

 This was the topic of the panel discussion between a science philosopher (MC), author of the recent book "The Brain Abstracted", and an experienced modeler (TS) at the FENS Regional Meeting in Oslo in June 2025. 

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On modeling neural population activity with mean-field models - with Tilo Schwalger - #39
•2 tim 19 min
On extracting spiking network models from experiments - with Richard Gao - #38
•1 tim 36 min
On reproducibility of modeling and 10 years with the Potjans-Diesmann network model - with Hans Ekkehard Plesser - #37
•1 tim 29 min
On low-dimensional manifolds in motor cortex - with Sara Solla - #36
•2 tim 5 min
On modeling metabolic networks in the brain – with Polina Shichkova - #35
•1 tim 32 min
On balanced neural networks - with Nicolas Brunel - #34
•1 tim 39 min
On computational neurotechnology for the clinic - with Anthony Burkitt, Nada Yousif & Esra Neufeld - #33
•1 tim 1 min
On IIT and adversarial testing of consciousness theories - with Christof Koch - #32
•2 tim 18 min
On how to cure brain diseases - with Nicole Rust - #31
•2 tim 13 min
On co-dependent excitatory and inhibitory plasticity - with Tim Vogels - #30
•1 tim 31 min

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