Intrinsic dimension of neural activity: comparing artificial and biological neural networks
Jacopo Fadanni, Giacomo Gasparotto, Rosalba Pacelli, Marco Dal Maschio, Marco Salamanca, Marica Albanesi, Pietro Rotondo, Michele Allegra · Bernstein Conference 2024
Artificial recurrent neural networks (RNNs) have become a customary research tool in theoretical neuroscience, being used as models of biological neural networks performing cognitive tasks. While RNNs are not generally intended as faithful, biologically realistic models of neuronal activity, there is a broad expectation that RNN dynamics may provide good models at the level of neural population dynamics. According to several authors, in both cases population activity should organize into low-dimensional manifolds encoding the relevant task variables (1). However, strong tests of this hypothesi