English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Synapses change on multiple timescales, ranging from milliseconds to minutes,due to a combination of both short- and long-term plasticity. Here we developan extension of the common Generalized Linear Model to infer both short- andlong-term changes in the coupling between a pre- and post-synaptic neuron basedon observed spiking activity. We model short-term synaptic plasticity usingadditive effects that depend on the presynaptic spike timing, and we modellong-term changes in both synaptic weight and baseline firing rate using pointprocess adaptive smoothing. Using simulations, we first show that this modelcan accurately recover time-varying synaptic weights 1) for both depressing andfacilitating synapses, 2) with a variety of long-term changes (includingrealistic changes, such as due to STDP), 3) with a range of pre- andpost-synaptic firing rates, and 4) for both excitatory and inhibitory synapses.We then apply our model to two experimentally recorded putative synapticconnections. We find that simultaneously tracking fast changes in synapticweights, slow changes in synaptic weights, and unexplained variations inbaseline firing is essential. Omitting any one of these factors can lead tospurious inferences for the others. Altogether, this model provides a flexibleframework for tracking short- and long-term variation in spike transmission.

Tracking fast and slow changes in synaptic weights from simultaneously observed pre- and postsynaptic spiking