Recent work has revealed that the neural activity patterns correlated with sensation,
cognition, and action often are not stable and instead undergo large scale changes over …

Large-scale recordings of neural activity over days and weeks have revealed that neural
representations of familiar tasks, precepts and actions continually evolve without obvious …

Hippocampal activity is critical for spatial memory. Within a fixed, familiar environment,
hippocampal codes gradually change over timescales of days to weeks—a phenomenon …

How an established behavior is retained and consistently produced by a nervous system in
constant flux remains a mystery. One possible solution to ensure long-term stability in motor …

The brain displays a remarkable ability to sustain stable memories, allowing animals to
execute precise behaviors or recall stimulus associations years after they were first learned …

In the biological nervous system, the integration and cooperation of parallel system of
receptors, neurons, and synapses allow efficient detection and processing of intricate and …

Time and experience are independent determinants of representational drift in CA1: Neuron
Skip to Main Content Advertisement Neuron This journal offers authors two options (open access …

Artificial neural networks have revolutionized machine learning in recent years, but a
complete theoretical framework for their learning process is still lacking. Substantial …

Neurons in sensory areas encode/represent stimuli. Surprisingly, recent studies have
suggested that, even during persistent performance, these representations are not stable …

Advances in artificial intelligence enable neural networks to learn a wide variety of tasks, yet
our understanding of the learning dynamics of these networks remains limited. Here, we …