A biologically plausible neural network for Slow Feature Analysis

1 code implementation • NeurIPS 2020 • David Lipshutz, Charlie Windolf, Siavash Golkar, Dmitri B. Chklovskii

Furthermore, when trained on naturalistic stimuli, SFA reproduces interesting properties of cells in the primary visual cortex and hippocampus, suggesting that the brain uses temporal slowness as a computational principle for learning latent features.

Hippocampus Time Series +1