Mathematical Modeling podcasts

Ellen Zapata-Webborn discusses how mathematical research can help predict household energy use. The episode connects patterns in smart-meter data, human behaviour and the demands of electricity systems, illustrating how quantitative models can inform practical energy questions.

Gaute Einevoll talks with Tatjana Tchumatchenko about a mechanistic mathematical model of how neurons minimize energy use by deciding whether ion-channel proteins are produced locally in dendrites or in the soma. The model’s predictions agree with experimental findings.

Ulrich Sperhake and Seppe Staelens explain hypothetical boson stars and how researchers use mathematical modelling to investigate them. The discussion connects these unusual compact objects to black holes, gravity and gravitational-wave observations.

David Dahmen examines how differences between individual neurons affect network function and when homogeneous models miss important behaviour.

Tilo Schwalger discusses population-level descriptions of neural dynamics and how mean-field models can be derived from underlying network mechanisms.

Taylor Sparks and Oklahoma State University researcher Jake Bair discuss the history and methods of phase-field modelling. They explain how diffuse interfaces represent material transitions and support simulations of crack growth and dendritic structures. The episode links listeners to NIST’s Phase Field Community Hub for further technical resources.

Hosted by Taylor Sparks

Richard Gao discusses fitting spiking-network models to experimental data and dealing with different parameter combinations that explain similar observations.

Hans Ekkehard Plesser discusses reproducibility in computational research through a decade of work with the Potjans-Diesmann cortical network model.

Sara Solla discusses how low-dimensional descriptions can reveal structure in recordings from large populations of motor-cortex neurons.

Polina Shichkova discusses models of brain metabolism, including energy supply and the cellular processes that maintain neuronal function.

Nicolas Brunel discusses excitation-inhibition balance and mathematical explanations of irregular activity in cortical networks.

Tim Vogels discusses the interaction of excitatory and inhibitory plasticity and its implications for learning and stable network activity.

Eirik Valseth discusses mathematical models of weather and storm surges and the computations used to make forecasts. Conversation in Norwegian.

Etay Hay discusses building neuron models that support multiple research questions and exploring their use in clinical problems.

Hermann Cuntz discusses computational explanations of dendritic branching and the construction of synthetic neuronal morphologies.

Gaute Einevoll reflects on his academic career and explains his research in mathematical neuroscience, brain physics and neurotechnology. Anniversary solo episode in Norwegian.

Viktor Jirsa discusses linking brain models across scales and using individualized whole-brain simulations in the Virtual Brain Twin project.

Pawel Herman discusses models of working memory and the mechanisms that can maintain information over short timescales.

Avrama Blackwell discusses computational models of chemical signalling inside neurons and their relationship to cellular information processing.

Anton Arkhipov discusses the Allen Institute's detailed mouse visual-cortex models and the experimental measurements supporting them.