Optical recording techniques have become a widespread technique for measuring the activity of neural populations. Typically, the optical signal is generated by a mixture of sources, where only some of them are related to the optical signal which is correlated with the neural activity of interest. In addition, the signal-to-noise ratio is often very low, in particular, for single condition maps or and / short recording sequences. In this project we investigated whether recently blind source separation techniques (ICA, extended spatial decorrelation, generalized linear models, etc.) can be properly extended to cope with abovementioned challenges. For optical imaging of intrinsic signals we found, that second order methods based on spatial decorrelation algorithms provided the best results. Methods were applied to optical recording data using intrinsic signals as well as to calcium imaging data. <br /><br />Acknowledgement: Research was funded by DFG, Wellcome Trust, and Technische Universität Berlin.