Learning predictable factors from sequences: it’s not only about slow features
Ashena Gorgan Mohammadi, Manu Srinath Halvagal, Friedemann Zenke · Bernstein Conference 2024
Animals experience the world as a continuous sequence of complex high-dimensional sensory stimuli. They need to build internal models from this ongoing stream of experiences with few supervisory and reinforcement signals. How they accomplish this feat remains unclear. One possibility is that the brain relies on a slowness objective (SO) which stipulates that neuronal representations change little over time$^1$. This allows extracting slowly varying underlying factors from the sensory experience, in some cases, with local plasticity rules$^2$. However, the approach precludes exploiting the rich