Non-negative matrix factorization as a principle for recurrent processing in an oscillating neural network: problems and directions of solution

Non-negative Matrix Factorization (NMF) for its restriction of computation to positive vectors and components appears to be biologically plausible. In my talk I will argue that NMF even may serve as an example of how a recurrent neural network which employs spike-timing dependent neural plasticity and synaptic adaptation might work. Resulting problems and directions for their solution will be presented.