Nonlinear fusion is optimal for a wide class of multisensory tasks
Marcus Ghosh, Gabriel Béna, Volker Bormuth, Dan F. M. Goodman
The paper demonstrates that nonlinear fusion outperforms linear fusion in multisensory integration tasks when sensory signals are statistically dependent, and shows that spiking neural networks can approximate this nonlinear algorithm.
PLoS Computational Biology · Jul 5, 2024Peer-reviewedNeuroscience