Memory models often emphasize the need to encode novel patterns of neural activity
imposed by sensory drive. Prior learning and innate architecture likely restrict neural …

Accurate detection and quantification of spike transmission between neurons is essential for
determining neural network mechanisms that govern cognitive functions. Using point …

Synapses preferentially respond to particular temporal patterns of activity with a large
degree of heterogeneity that is informally or tacitly separated into classes. Yet, the precise …

Synapses contain a limited number of synaptic vesicles (SVs) that are released in response
to action potentials (APs). Therefore, sustaining synaptic transmission over a wide range of …

Whether, when, and how causal interactions between neurons can be meaningfully studied
from observations of neural activity alone are vital questions in neural data analysis. Here …

Detecting synaptic connections using large-scale extracellular spike recordings presents a
statistical challenge. Although previous methods often treat the detection of each putative …

Synapses are highly stochastic transmission units. A classical model describing this
stochastic transmission is called the binomial model, and its underlying parameters can be …

Experimental evidence in both human and animal studies demonstrated that deep brain
stimulation (DBS) can induce short-term synaptic plasticity (STP) in the stimulated nucleus …

Short-term synaptic dynamics differ markedly across connections and strongly regulate how
action potentials communicate information. To model the range of synaptic dynamics …

Synapses change on multiple timescales, ranging from milliseconds to minutes, due to a
combination of both short-and long-term plasticity. Here we develop an extension of the …