On growing synthetic dendrites – with Hermann Cuntz  - #25

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 you understand it, you can build it", the lab of the guest builds dendritic structures in a computer and explore the underlying principles.

Two key principles seem to be to minimize (i) the overall length of dendrites and (ii) the path length from the synapses to the soma.

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Jaksot(45)

On neuromorphic computing - with Mihai Petrovici - #45

On neuromorphic computing - with Mihai Petrovici - #45

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23 Syys 1h 41min

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

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 d...

26 Elo 1h 43min

On the computational neuroscience legacy of Valentino Braitenberg - with Ad Aertsen - #43

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 c...

25 Heinä 1h 10min

On neuronal identity and representational drift - with Timothy O'Leary - #42

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'...

20 Kesä 1h 43min

On functional effects of neuronal heterogeneity - with David Dahmen - #41

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 th...

23 Touko 1h 29min

On smelling your way to the fruit with ring models - with Katherine Nagel - #40

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 orie...

25 Huhti 1h 25min

On modeling neural population activity with mean-field models - with Tilo Schwalger - #39

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 p...

28 Maalis 2h 18min

On extracting spiking network models from experiments - with Richard Gao - #38

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 to make the model predictions...

28 Helmi 1h 35min

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