CNS*2023 workshop, Leipzig, 18th-19th July,

Workshop on
Optimality, evolutionary trade-offs, Pareto theory and degeneracy in neuronal modeling

by
Alexander Bird (Justus-Liebig University, Giessen & Ernst Strüngmann Institute, Frankfurt)
Philipp Norton (Humboldt University, Berlin)
Peter Jedlicka (Justus-Liebig University, Giessen & Ernst Strüngmann Institute, Frankfurt)
Susanne Schreiber (Humboldt University, Berlin)

Nervous systems, like any evolved structure, encounter unavoidable trade-offs between multiple tasks. They must fulfil their fundamental computational functions whilst consuming as little energy as possible and remaining robust to potential environmental changes. These tasks are often in direct opposition to one another, and a general quantification of the relative importance of individual optimisation targets is non-trivial. The problem is complicated by the degeneracy seen across neurons and circuits, where multiple different combinations of components can lead to similar functional behaviours. Pareto optimality might provide a useful framework to analyse neurobiological systems from biophysically detailed cells to large-scale network structures that combine high-dimensional parameter spaces with high-dimensional objective spaces. Pareto, or multi-objective, optimality can, for example, help to identify geometrically simple subspaces of neuronal models that cannot be improved upon for all relevant objectives. This workshop aims to discuss applications of Pareto optimality to the trade-offs encountered by diverse nervous systems. The talks and discussions will also address the trade-off between functional effectiveness and energetic efficiency and the concept of metabolically efficient information processing.
Hosted at the CNS*2023 Meeting, Leipzig
Date: July 18th-19th, 2023.
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Inspired by Pallasdies et al (2021) and Jedlicka et al (2022)