text: The claimed results of  "combining transformations" in the context of RC was done in the works of Herbert Jaeger on conceptors [1],  which also should be cited here. The argument of biological plausibility is not justified.  The authors  use an echo-state neural network with standard tanh activations, which is as far away from real neuronal signal processing than  ordinary RNNs used in the field, with the difference that the recurrent weights are not trained.   If the authors want to make the case of biological plausibility, they should use spiking neural networks. The experiment on MNIST seems artificial, in particular transforming the image into a time-series and thereby imposing an artificial temporal structure.  The assumption that column_i is obtained  by information  of column_{i-k},..,column_{i-1} is not true for images.  To make a point, the authors should use a datasets with related sets of time-series data, e.g EEG or NLP data. In total this paper does not have enough novelty for acceptance  and the experiments are not well chosen for this kind of work.  Also the authors overstate the claim of biological plausibility  (just because we don't train the recurrent weights does not make a method biologically plausible). [1] H. Jaeger (2014): Controlling Recurrent Neural Networks by Conceptors. Jacobs University technical report Nr 31 (195 pages)