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 …

Highlights•Generalized integrate-and-fire (GIF) models permit efficient extraction of point
neuron parameters, which reproduce the spiking behavior of multiple cell types and are …

Biological brains possess an unparalleled ability to adapt behavioral responses to changing
stimuli and environments. How neural processes enable this capacity is a fundamental open …

In neural circuits, synaptic strengths influence neuronal activity by shaping network
dynamics, and neuronal activity influences synaptic strengths through activity-dependent …

We propose that ramping time cells in the lateral entorhinal cortex can be produced by
synaptic adaptation and demonstrate this in an integrate-and-fire attractor network model …

The neural dynamics generating sensory, motor, and cognitive functions are commonly
understood through field theories for neural population activity. Classic neural field theories …

The timing of self-initiated actions shows large variability even when they are executed in
stable, well-learned sequences. Could this mix of reliability and stochasticity arise within the …

Attractor networks are an influential theory for memory storage in brain systems. This theory
has recently been challenged by the observation of strong temporal variability in neuronal …

Recurrent neural networks (RNNs) are powerful dynamical models, widely used in machine
learning (ML) and neuroscience. Prior theoretical work has focused on RNNs with additive …

Assemblies of neurons, called concepts cells, encode acquired concepts in human Medial
Temporal Lobe. Those concept cells that are shared between two assemblies have been …