Theoretical Neuroscience Podcast – Details, episodes & analysis

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Theoretical Neuroscience Podcast

Gaute Einevoll

Science

Frequency: 1 episode/24d. Total Eps: 44

The podcast focuses on topics in theoretical/computational neuroscience and is primarily aimed at students and researchers in the field.

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On balanced neural networks - with Nicolas Brunel - #34

Season 1 · Episode 34

Saturday, November 8, 2025 • Duration 01:38:59

An important discovery that has come out of computational neuroscience, is that cortical neurons in vivo appear to receive so-called balanced inputs.

In the balanced state the excitatory and inhibitory synaptic inputs to a neuron are about equal, and action potentials occur when a fluctuation temporarily makes the excitation dominate.

The theory, for example, explains the observed irregular firing of cortical neurons in the background state.

Today's guest was one of the key developers of the theory in the late 1990s.

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On computational neurotechnology for the clinic - with Anthony Burkitt, Nada Yousif & Esra Neufeld - #33

Season 1 · Episode 33

Saturday, October 11, 2025 • Duration 01:00:36

How can computational neuroscience contribute to developing neurotechnology to help people with brain disorders and disabilities?

This was the topic of a panel debate I hosted at the 34th Annual Computational Neuroscience Meeting in Florence in July this year.

Electric or magnetic recording and/or stimulation are key clinical tools for helping patients, and the three panelists have all used computational methods to aid this endeavor.

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On neuroscience foundation models - with Andreas Tolias - #24

Season 1 · Episode 24

Saturday, February 1, 2025 • Duration 01:31:43

The term "foundation model" refers to machine learning models that are trained on vast datasets and can be applied to a wide range of situations. The large language model GPT-4 is an example.

The group of the guest has recently presented a foundation model for optophysiological responses in mouse visual cortex trained on recordings from 135.000 neurons in mice watching movies.

We discuss the design, validation, use of this and future neuroscience foundation models.

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On human whole-brain models - with Viktor Jirsa - #23

Season 1 · Episode 23

Saturday, January 4, 2025 • Duration 01:55:21

A holy grail of the multiscale approach for physical brain modelling is to link the different scales from molecules, via cells and local neural networks, up to whole-brain models.

The goal of the Virtual Brain Twin project, lead by today's guest, is to use personalized human whole-brain models to aid clinicians in treating brain ailments.

The podcast discusses how such models are presently made using neural field models, starting with neuron population dynamics rather than molecular dynamics.

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On 40 years with the Hopfield network model - with Wulfram Gerstner - #22

Season 1 · Episode 22

Saturday, December 7, 2024 • Duration 01:27:49

In 1982 John Hopfield published the paper "Neural networks and physical systems with emergent collective computational abilities" describing a simple network model functioning as an associative and content-addressable memory.

The paper started a new subfield in computational neuroscience and led to the influx of numerous theoretical scientists, in particular physicists, to the field.

The podcast guest wrote his PhD thesis on the model in the early 1990s, and we talk about the history and present impact of the model.

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On models for short-term memory - with Pawel Herman - #21

Season 1 · Episode 21

Saturday, November 9, 2024 • Duration 01:47:42

The leading theory for learning and memorization in the brain is that learning is provided by synaptic learning rules and memories stored in synaptic weights between neurons.

But this is for long-term memory. What about short-term, or working, memory where objects are kept in memory for only a few seconds?

The traditional theory held that here the mechanism is different, namely persistent firing of select neurons in areas such as prefrontal cortex. But this view is challenged by recent synapse-based models explored by today's guest and others.

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On neuro-AI on the boat - part 2 of 2 - with Cristina Savin, Tim Vogels, Mikkel Lepperød, Paul Middlebrooks - #20

Season 1 · Episode 20

Friday, October 11, 2024 • Duration 01:21:03

In September Paul Middlebrooks, the producer of the podcast BrainInspired, and I were both on a neuro-AI workshop on a coast liner cruising the Norwegian fjords.

We decided to make two joint podcasts with some of the participants where we discuss the role of AI in neuroscience.

In this second part we discuss the topic with Cristina Savin and Tim Vogels and round off with a brief discussion with Mikkel Lepperød, the main organizer of the workshop, about what he learned from the workshop.

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On neuro-AI on the boat - part 1 of 2 - with Ken Harris, Andreas Tolias, Mikkel Lepperød, Paul Middlebrooks - #19

Season 1 · Episode 19

Tuesday, October 8, 2024 • Duration 01:19:26

In September Paul Middlebrooks, the producer of the podcast BrainInspired, and I were both on a neuro-AI workshop on a coast liner cruising the Norwegian fjords.

We decided to make two joint podcasts with some of the participants where we discuss the role of AI in neuroscience.

In this first part we talk with Mikkel Lepperod, the main organizer about the goal of the workshop, and with Ken Harris and Andreas Tolias about how AI has affected their research neuroscientists and their thoughts about the future of neuro-AI.

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On electric brain signals - solo episode - #18

Season 1 · Episode 18

Sunday, September 15, 2024 • Duration 01:48:22

Most of what we have learned about the functioning of the living brain has come from extracellular electrical recordings, like the measurement of spikes, LFP, ECoG and EEG signals.

And most analysis of these recordings has been statistical, looking for correlations between the recorded signals and what the animal/human is doing or being exposed to.

However, starting with the neuron rather than the data, these electrical brain signals can also be computed from biophysics-based forward models, and this is topic of this podcast.

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On dendritic function - with Yiota Poirazi - #17

Season 1 · Episode 17

Saturday, August 17, 2024 • Duration 01:27:39

The most prominent visual characteristic of neurons is their dendrites.

Even more than 100 years after their first observation by Cajal, their function is not fully understood. Biophysical modeling based on cable theory is a key research tool for exploring putative functions, and today's guest is one the leading researchers in this field.

We talk about of passive and active dendrites, the kind of filtering of synaptic inputs they support, the key role of synapse placements, and how the inclusion of dendrites may facilitate AI.

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Theoretical Neuroscience Podcast – Details, episodes & analysis

Podcast details

Recent rankings

Apple Podcasts

Spotify

Shared links between episodes and podcasts

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Apple Podcasts

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Theoretical Neuroscience Podcast – Details, episodes & analysis

Podcast details

Recent rankings

Apple Podcasts

Spotify

Shared links between episodes and podcasts

RSS feed quality and score

Publication history

Latest published episodes

Similar podcasts and content

Related Shows Based on Content Similarities

Apple Podcasts

Spotify

Related Shows Based on Content Similarities