Topic: synaptic-level noise

Stable neural representations are essential for consistent behavior and learning, but recent findings on representational drift challenge our understanding of how individual neurons contribute to stable brain computations over time. While representational drift has been observed across multiple brain regions, its relationship to structural connectivity and homeostatic statistics remains unclear [1]. To address this, we explored how drift interacts with structural recurrency and noise in a recurrent neural network (RNN) model. By simulating synaptic-level noise through random connectivity manip