Brain-inspired recurrent spiking neural networks for multiscale dynamic representation with manifolds.
Understanding how network structure shapes neural population dynamics and representation of external inputs is a key issue in neuroscience. This study proposes a modeling framework for recurrent spiking neural networks (RSNN) and elucidates dynamical computation mechanism of RSNN by linking input dimensionality, networ...