Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems
Encoding in Balanced Networks: Revisiting Spike Patterns and Chaos in Stimulus-Driven Systems
Highly connected recurrent neural networks often produce chaotic dynamics, meaning their precise activity is sensitive to small perturbations. What are the consequences for how such networks encode streams of temporal stimuli? On the one hand, chaos is a strong source of randomness, suggesting that small changes in stimuli will be …