Stable fixed points

…can exhibit a manifold of global fixed points capable of implementing sophisticated input-output mappings, which we characterize analytically. Learning from extensive datasets is achieved through the stabilization of fixed points via a fully distributed and local learning process, implemented at the single-neuron level. This simple mechanism yields performance comparable to that of conventional feedforward deep neural networks train

Synaptic and representational drift describe the dynamic changes in neuronal connections and activity over time. However, the relationship between these two processes remains elusive. Here, we integrated representational dynamics and synaptic drift into a firing rate model to explore the influence of synaptic drift on representational drift.In mouse auditory cortex, neuronal populations respond to stimuli in a clustered manner (Aschauer et al., 2022). Our model, comprising inhibitory and excitatory neurons, reproduces these response patterns, especially under inhibition-dominated conditions. W