Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics
through mechanisms of synaptic plasticity. Inhibitory plasticity can establish …

Many studies have shown that the excitation and inhibition received by cortical neurons
remain roughly balanced across many conditions. A key question for understanding the …

Task-related neural activity is widespread across populations of neurons during goal-
directed behaviors. However, little is known about the synaptic reorganization and circuit …

Biological memory networks are thought to store information by experience-dependent
changes in the synaptic connectivity between assemblies of neurons. Recent models …

Recurrent network models are instrumental in investigating how behaviorally-relevant
computations emerge from collective neural dynamics. A recently developed class of models …

Deep feedforward and recurrent neural networks have become successful functional models
of the brain, but they neglect obvious biological details such as spikes and Dale's law. Here …

Neural computations emerge from local recurrent neural circuits or computational units such
as cortical columns that comprise hundreds to a few thousand neurons. Continuous …

The dynamics of local cortical networks are irregular, but correlated. Dynamic excitatory–
inhibitory balance is a plausible mechanism that generates such irregular activity, but it …

Cortical neurons are characterized by irregular firing and a broad distribution of rates. The
balanced state model explains these observations with a cancellation of mean excitatory …

Neurons mainly communicate through spikes, and much effort has been spent to understand
how the dynamics of spiking neural networks (SNNs) relates to their connectivity …