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

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

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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Episoder(43)

On the computational neuroscience legacy of Valentino Braitenberg - with Ad Aertsen - #43

On the computational neuroscience legacy of Valentino Braitenberg - with Ad Aertsen - #43

The prominent and colorful neuroscientist Valentino Braitenberg was born 100 years ago. He co-founded the Max Planck Institute of Biological Cybernetics in Tübingen in Germany, where he made seminal c...

25 Jul 1h 10min

On neuronal identity and representational drift - with Timothy O'Leary - #42

On neuronal identity and representational drift - with Timothy O'Leary - #42

A bursting neuron can maintain its firing-pattern identity throughout an animal's life, even though the ion-channel proteins underlying this identity are turned over on the timescale of days.   Today'...

20 Jun 1h 43min

On functional effects of neuronal heterogeneity - with David Dahmen - #41

On functional effects of neuronal heterogeneity - with David Dahmen - #41

Most neural network models till date have assumed all neurons to be identical, or at least that all neurons within a population are identical. In reality, no two neurons are completely the same. Is th...

23 Mai 1h 29min

On smelling your way to the fruit with ring models - with Katherine Nagel - #40

On smelling your way to the fruit with ring models - with Katherine Nagel - #40

Fruit flies need a short-term (working) memory to keep their direction when they navigate their way to the fruit by smelling. Mean-field ring models was theoretically suggested to encode stimulus orie...

25 Apr 1h 25min

On modeling neural population activity with mean-field models - with Tilo Schwalger - #39

On modeling neural population activity with mean-field models - with Tilo Schwalger - #39

Starting with the work of pioneers like Wilson and Cowan in the 1970s, mean‑field models have become a dominant tool for modeling neural activity at the level of neuronal populations. Despite their p...

28 Mar 2h 18min

On extracting spiking network models from experiments - with Richard Gao - #38

On extracting spiking network models from experiments - with Richard Gao - #38

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...

28 Feb 1h 35min

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

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

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 neuro...

31 Jan 1h 28min

On low-dimensional manifolds in motor cortex - with Sara Solla - #36

On low-dimensional manifolds in motor cortex - with Sara Solla - #36

Historically, the analysis of neural recordings focused on responses of single neurons recorded by single-contact electrodes. Modern electrodes with multiple electrode contacts can instead record spik...

3 Jan 2h 4min

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