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Neuroscience Seminar Series - Gasper Tkacik

Spanning the arc between optimality theories and data

Date
Tuesday, June 2, 2020 14:00 - 15:00
Speaker
Gasper Tkacik (IST Austria)
Location
https://istaustria.zoom.us/j/94819824190?pwd=TEsvSzdYUmYxRzlQVlNiVVlOYms0Zz09
Series
Seminar/Talk
Tags
Neuroscience Data Talk
Contact
Url

Ideas about optimization are at the core of how we approach biological complexity. Quantitative predictions about biological systems have been successfully derived from first principles in the context of efficient coding, metabolic and transport networks, evolution, reinforcement learning, and decision making, by postulating that a system has evolved to optimize some utility function under biophysical constraints. Yet as normative theories become increasingly high-dimensional and optimal solutions stop being unique, it gets progressively hard to judge whether theoretical predictions are consistent with, or "close to", data. I will illustrate these issues using efficient coding applied to simple neuronal models as well as to a complex and realistic biochemical reaction network. As a solution, we developed a statistical framework which smoothly interpolates between ab initio optimality predictions and Bayesian parameter inference from data, while also permitting statistically rigorous tests of optimality hypotheses.

Webinar ID: 948 1982 4190

Password: 283739


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