Theoretical Neuroscience Podcast

On how energy determines where proteins are produced in neurons - with Tatjana Tchumatchenko - #44

For neurons to function, the appropriate ion-channel proteins must be present where they are needed, including in distal dendrites and axon terminals. This requires ene

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

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 t

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

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 s

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

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

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 chall

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 co

On modeling metabolic networks in the brain – with Polina Shichkova - #35

Neurons need particular sodium and potassium concentration gradients across their membranes to function. These gradients are set up by so-called ion pumps which require e

On balanced neural networks - with Nicolas Brunel - #34

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 st

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

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

On IIT and adversarial testing of consciousness theories - with Christof Koch - #32

In an adversarial collaboration researchers with opposing theories jointly investigate a disputed topic by designing and implementing a study in a mutually agreed unbiase

On how to cure brain diseases - with Nicole Rust - #31

A promise of basic neuroscience research is that the new insights will lead to new cures for brain diseases. But has that happened so far? Today's guest, an accomplishe

On co-dependent excitatory and inhibitory plasticity - with Tim Vogels - #30

Synaptic plasticity underlies several key brain functions including learning, information filtering and homeostatic regulation of overall neural activity. While several

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 biop

On whole-cell modeling of bacteria - with Markus Covert - #28

A future computational neuroscience project could be to model not only the signal processing properties of neurons, but also all processes that keep a neuron alive for, s

On construction and clinical use of multipurpose neuron models - with Etay Hay - #27

Numerous neuron models have been made, but most of them are "single-purpose" in that they are made to address a single scientific question. In contrast, multipurpose neur

On the population code in visual cortex - with Kenneth Harris - #26

With modern electrical and optical measurement techniques, we can now measure neural activity in hundreds or thousands of neurons simultaneously. This allows for the inve

On growing synthetic dendrites – with Hermann Cuntz - #25

The observed variety of dendritic structures in the brains is striking. Why are they so different, and what determine the branching patterns? Following the dictum "if y