Abstract:
In this talk I will present our work, based on the development and applications of mathematical methods from Information Theory and Machine Learning, to study how the functions of neural population codes emerge form the interaction of different neurons.

Biosketch:
Stefano Panzeri is full professor and director at the Department of Excellence for Information Processing at the Medical School in Hamburg (UKE). Stefano was trained and researched originally in theoretical physics (string theory) and has worked in computational neuroscience for more than 20 years. His research lies at the interface between theory and experiments and investigates how the functions of the brain originate from the interactions between its elements, the neurons. 

Recommended Article:

1. Runyan, C. A., Piasini, E., Panzeri, S. & Harvey, C. D. Distinct timescales of population coding across cortex. Nature 548, 92-96, doi:10.1038/nature23020 (2017). (Link to Paper)
2. Valente, M. et al. Correlations enhance the behavioral readout of neural population activity in association cortex. Nat Neurosci 24, 975-986, doi:10.1038/s41593-021-00845-1 (2021). (Link to Paper)
3. Panzeri, S., Moroni, M., Safaai, H. & Harvey, C. D. The structures and functions of correlations in neural population codes. Nat Rev Neurosci 23, 551-567, doi:10.1038/s41583-022-00606-4 (2022). (Link to Paper)

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