The most prominent visual characteristic of neurons is their dendrites.
Even more than 100 years after their first observation by Cajal, their function is not fully understood. Biophysical modeling based on cable theory is a key research tool for exploring putative functions, and today’s guest is one the leading researchers in this field.
We talk about of passive and active dendrites, the kind of filtering of synaptic inputs they support, the key role of synapse placements, and how the inclusion of dendrites may facilitate AI.
Links:
- Homepage of Poirazi lab
- Pagkalos, Makarov, Poirazi: “Leveraging dendritic properties to advance machine learning”, Current Opinion in Neurobiology (2024)
- Pagkalos, Chavlis, Poirazi: “Introducing the Dendrify framework for incorporating dendrites to spiking neural networks”, Nature Communications (2023)
- Poirazi & Papoutsi: “Illuminating dendritic function with computational model”, Nature Reviews Neuroscience (2020)
- Kastellakis, Cai, Mednick, Silva, Poirazi: “Synaptic clustering within dendrites: An emerging theory of memory formation”, Progress in Neurobiology (2015)
The podcast was recorded on July 16th, 2024 and lasts 1 hour and 27 minutes.
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