" ... As a solution (for Short Term Plasticity (STP) inference), we introduce a Bayesian formulation, which yields the posterior distribution over the model parameters given the data. First, we show that common STP protocols yield broad distributions over some model parameters. Using our result we propose a experimental protocol to more accurately determine synaptic dynamics parameters. Next, we infer the model parameters using experimental data from three different neocortical excitatory connection types. This reveals connection-specific distributions, which we use to classify synaptic dynamics. Our approach to demarcate connection-specific synaptic dynamics is an important improvement on the state of the art and reveals novel features from existing data."
Model Type: Synapse
Model Concept(s): Short-term Synaptic Plasticity
Simulation Environment: MATLAB
Implementer(s): Costa, Rui Ponte [ruipontecosta at gmail.com]
References:
Costa RP, Sjöström PJ, van Rossum MC. (2013). Probabilistic inference of short-term synaptic plasticity in neocortical microcircuits. Frontiers in computational neuroscience. 7 [PubMed]