Theoretical Neuroscience Podcast

Gaute Einevoll and Mihai Petrovici discuss how neuromorphic hardware can support artificial intelligence and efficient brain simulation. They contrast high-frequency arithmetic on conventional silicon with the rich dynamics and millisecond spikes of biological neurons, and explore brain-inspired systems for emulating neural dynamics and studying computation in spiking networks. Petrovici is a senior researcher at the University of Bern. The conversation was recorded on 18 June 2026 and released on 23 September 2026; the publisher’s audio runs 1 hour, 41 minutes and 46 seconds.

Hosted by Gaute Einevoll

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.

Ad Aertsen reflects on Valentino Braitenberg's contributions to neuroscience, including anatomy, synthetic psychology and theories of neural computation.

Timothy O'Leary discusses how neurons preserve functional identity despite molecular turnover and how related processes may contribute to changing representations.

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

Katherine Nagel discusses how fruit flies navigate using odour and how ring models can explain the short-term memory involved.

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

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.

Anthony Burkitt, Nada Yousif and Esra Neufeld discuss how computational research can inform neurotechnology for clinical use.

Christof Koch discusses collaborative tests designed by proponents of competing consciousness theories and what the findings imply for those accounts.

Nicole Rust examines the relationship between basic neuroscience discoveries and progress toward treatments for brain disorders.

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

Mazviita Chirimuuta and Terrence Sejnowski discuss how researchers choose appropriate simplifications when constructing explanations of brain function.

Markus Covert discusses comprehensive bacterial cell simulations and what whole-cell modelling could contribute to future studies of neurons.

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

Kenneth Harris discusses what simultaneous recordings from many cells reveal about visual information encoded by neuronal populations.