Perturbing low dimensional activity manifolds in spiking neuronal networks.
Emil WärnbergArvind KumarPublished in: PLoS Comput. Biol. (2019)
Keyphrases
- low dimensional
- manifold learning
- high dimensional
- neuronal networks
- high dimensional data
- dimensionality reduction
- euclidean space
- feature space
- principal component analysis
- low dimensional manifolds
- dimension reduction
- data points
- higher dimensional
- low dimensional spaces
- embedding space
- feed forward
- vector space
- bio inspired
- lower dimensional
- multidimensional scaling
- data sets
- linear subspace
- hebbian learning
- machine learning
- manifold structure
- input space
- pattern recognition
- human activities
- basal ganglia
- underlying manifold
- face recognition
- high dimensional image space