Artwork for Theoretical Neuroscience Podcast

Theoretical Neuroscience Podcast · May 23 · 1 hr 29 min

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 this due to unavoidable "biological noise" that the nervous system has to cope with, or can it be a useful feature included by design? The guest co-wrote the recent paper "How heterogeneity shapes dynamics and computation in the brain" addressing this question.

0:00-1:29:54

Play in podnod

transcript

No transcript — this publisher did not publish one.

show notes

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 this due to unavoidable "biological noise" that the nervous system has to cope with, or can it be a useful feature included by design?

The guest co-wrote the recent paper "How heterogeneity shapes dynamics and computation in the brain" addressing this question.

more episodes

On the computational neuroscience legacy of Valentino Braitenberg - with Ad Aertsen - #43
July 25 · 1 hr 10 min
On neuronal identity and representational drift - with Timothy O'Leary - #42
June 20 · 1 hr 43 min
On smelling your way to the fruit with ring models - with Katherine Nagel - #40
April 25 · 1 hr 25 min
On modeling neural population activity with mean-field models - with Tilo Schwalger - #39
March 28 · 2 hr 18 min
On extracting spiking network models from experiments - with Richard Gao - #38
February 28 · 1 hr 35 min
On reproducibility of modeling and 10 years with the Potjans-Diesmann network model - with Hans Ekkehard Plesser - #37
January 31 · 1 hr 28 min

All episodes