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Theoretical Neuroscience Podcast: Daily Summaries Delivered
by Gaute Einevoll
The podcast focuses on topics in theoretical/computational neuroscience and is primarily aimed at students and researchers in the field.
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The most recent episodes — sign up to get AI-powered summaries of each one.
- 1 weeks ago2h 17m
On the relationship between structure and function in cortical networks - with Michael Reimann - #46
Detailed reconstructed neuronal morphologies are now widely available, but how do you wire them up in a network? The shape of the neurons provides a key constraint: synapses only can occur when presynaptic axon terminals are physically close to postsynaptic dendrites. Today's guest has used this and other principles to construct large-scale cortical model networks and to study the relationship between the anatomical connectivity and function of such networks.
- Sep 23, 20261h 41m
On neuromorphic computing - with Mihai Petrovici - #45
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- Aug 26, 20261h 43m
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 energy, and the guest's group has developed a mechanistic mathematical model to investigate how neurons can reduce this cost by optimizing where proteins are synthesized within the cell—locally or at more distant sites. The model's predictions agree with experimental findings, suggesting that energy optimization is a fundamental operating principle of neurons.
- Jul 25, 20261h 10m
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 Germany, where he made seminal contributions to neuroanatomy, synthetic psychology, and theories for cerebellar, fly vision and cortical function. He was celebrated at the recent Braitenberg*100 symposium which I attended together with today's guest. Ad Aertsen is an outstanding computational neuroscientist and worked with Braitenberg back in the days.
- Jun 20, 20261h 43m
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 the timescale of days. Today's guest has proposed that neuronal identities are stored in the specific protein production rules, which are regulated by intracellular calcium signaling. And how can animals reliably perform a learned task for weeks, even when the underlying neural representation drifts over time, so-called representational drift?
- May 23, 20261h 29m
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.
- Apr 25, 20261h 25m
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 suggested to encode stimulus orientations 30 years and was observed in fruit-fly compass neurons 10 years ago. But how does odor input come into the picture to set the compass course? The group of the guest has studied the question with a host of different experimental and theoretical methods.
- Mar 28, 20262h 18m
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 populations. Despite their popularity, most mean‑field models have been heuristic and not systematically derived from the underlying 'microscopic' dynamics of individual neurons. Today's guest has made important contributions towards remedying this situation.
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About Theoretical Neuroscience Podcast
The podcast focuses on topics in theoretical/computational neuroscience and is primarily aimed at students and researchers in the field.
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