ePoster · Computational Neuroscience
Sequence learning under biophysical constraints: a re-evaluation of prominent models
Barna Zajzon, Younes Bouhadjar, Tom Tetzlaff, Renato Duarte, Abigail Morrison · Bernstein Conference 2024
Perceiving causality, anticipating events, choosing an action or understanding language - all facets of complex behavior are anchored in time and rely on representing, recognizing and expressing temporally patterned sequences. Established approaches in the cognitive sciences formulate these processes in terms that involve the manipulation of sequentially organized time-discrete (symbolic) representations. While we understand fairly well how artificial systems perform on different aspects of the problem, existing models of biological (specifically spiking) networks that use biophysically realis