Back to Search
Start Over
Accurate connection strength estimation based on variational bayes for detecting synaptic plasticity
- Source :
- Neural computation. 27(4)
- Publication Year :
- 2015
-
Abstract
- Connection strength estimation is widely used in detecting the topology of neuronal networks and assessing their synaptic plasticity. A recently proposed model-based method using the leaky integrate-and-fire model neuron estimates membrane potential from spike trains by calculating the maximum a posteriori (MAP) path. We further enhance the MAP path method using variational Bayes and dynamic causal modeling. Several simulations demonstrate that the proposed method can accurately estimate connection strengths with an error ratio of less than 20%. The results suggest that the proposed method can be an effective tool for detecting network structure and synaptic plasticity.
- Subjects :
- Quantitative Biology::Neurons and Cognition
business.industry
Cognitive Neuroscience
Topology (electrical circuits)
Machine learning
computer.software_genre
Connection (mathematics)
Bayes' theorem
Arts and Humanities (miscellaneous)
Synaptic plasticity
Path (graph theory)
Maximum a posteriori estimation
Spike (software development)
Artificial intelligence
business
Algorithm
computer
Mathematics
Causal model
Subjects
Details
- ISSN :
- 1530888X
- Volume :
- 27
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Neural computation
- Accession number :
- edsair.doi.dedup.....ebc2c5dd2d2e717f191923a90871314b