Prob. Inference of Short-Term Synaptic Plasticity in Neocort. Microcircuits (Costa et al. 2013)

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Accession:149914
" ... 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."
Reference:
1 . Costa RP, Sjostrom PJ, van Rossum MC (2013) Probabilistic Inference of Short-Term Synaptic Plasticity in Neocortical Microcircuits Front. Comput. Neurosci. [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse;
Brain Region(s)/Organism:
Cell Type(s):
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Gap Junctions:
Receptor(s):
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Simulation Environment: MATLAB;
Model Concept(s): Short-term Synaptic Plasticity;
Implementer(s): Costa, Rui Ponte [ruipontecosta at gmail.com];
 
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