Noisy Adaptation Generates Lévy Flights in Attractor Neural Networks

no code implementations • NeurIPS 2021 • Xingsi Dong, Tianhao Chu, Tiejun Huang, Zilong Ji, Si Wu

To elucidate the underlying mechanism clearly, we first study continuous attractor neural networks (CANNs), and find that noisy neural adaptation, exemplified by spike frequency adaptation (SFA) in this work, can generate Lévy flights representing transitions of the network state in the attractor space.

Retrieval