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

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Manage episode 489991155 series 3562348
Content provided by Gaute Einevoll. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Gaute Einevoll or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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.

  continue reading

30 episodes

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iconShare
 
Manage episode 489991155 series 3562348
Content provided by Gaute Einevoll. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Gaute Einevoll or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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.

  continue reading

30 episodes

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