Theoretical Neuroscience Podcast
The podcast focuses on topics in theoretical/computational neuroscience and is primarily aimed at students and researchers in the field.
- Update frequency
- every 22 days
- Average duration
- 96 minutes
- Episodes
- 31
- Years Active
- 2023 - 2025
On synaptic learning rules for spiking neurons - with Friedemann Zenke - #11
Today’s AI is largely based on supervised learning of neural networks using the backpropagation-of-error synaptic learning rule. This learning rule relies on differentiation of continuous activation …
On large-scale modeling of mouse primary visual cortex - with Anton Arkhipov - #10
Over the last ten years or so, the MindScope project at the Allen Institute in Seattle has pursued an industrylab-like approach to study the mouse visual cortex in unprecedented detail using electrop…
On origins of computational neuroscience and AI as scientific fields - with Terrence Sejnowski (vintage) - #9
Today’s guest is a pioneer both in the fields of computational neuroscience and artificial intelligence (AI) and has had a front seat during their development.
His many contributions include, for ex…
On reverse engineering of the roundworm C.elegans - with Konrad Kording - #8
Today’s guest has argued that the present dominant way of doing systems neuroscience in mammals (large-scale electric or optical recordings of neural activity combined with data analysis) will be ina…
On topological data analysis and Hopfield-like network models - with Carina Curto - #7
Over the last decade topological analysis has been established as a new tool for analysis of spiking data.
Today’s guest has been a pioneer in adapting this mathematical technique for use in our fiel…
On central pattern generators in the spinal cord - with Henrik Lindén - #6
Not all interesting network activity occurs in cortex. Networks in the spinal cord, the long thin tubular structure extending downwards from the neck, is responsible for setting up rhythmic motor act…
On how vision works - with Li Zhaoping - #5
We know a lot about of how neurons in the primary visual cortex (V1) of mammals respond to visual stimuli.
But how does the vast information contained in the spiking of millions of neurons in V1 give…
On multi-area cortex models - with Sacha van Albada - #4
A key goal of computational neuroscience is to build mathematical models linking single-neuron activity to systems-level activity.
The guest has taken some bold steps in this direction by developing …
On the neural code - with Arvind Kumar - #3
It is widely thought that spikes (action potentials) are the main carrier of information in the brain.
But what is the neural code, that is, what aspects of the spike trains carry the information? Th…
On biophysics of computation – with Christof Koch - #2
Starting from the pioneering work of Hodgkin, Huxley and Rall in the 1950s and 60s, we have a well-founded biophysics-based mathematical understanding of how neurons integrate signals from other neur…
On models of the mind - with Grace Lindsay - #1
The book “Models of the Mind” published in 2021 gives an excellent popular account of the history and questions of interest in theoretical neuroscience.
I could think of no other person more suitable…