TU Berlin

Neural Information ProcessingFunctional Imaging Methods: Source Separation Techniques

Neuronale Informationsverarbeitung

Page Content

to Navigation

Functional Imaging Methods: Source Separation Techniques

Lupe

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.

Acknowledgement: Research was funded by DFG, Wellcome Trust, and Technische Universität Berlin.

Selected Publications:

Blind Signal Separation from Optical Imaging Recordings with Extended Spatial Decorrelation
Citation key Schiessl2000b
Author Schießl, I. and Stetter, M. and Mayhew, J. and McLoughlin, N. and Lund, J. and Obermayer, K.
Pages 573 – 577
Year 2000
ISSN 0018-9294
DOI 10.1109/10.841327
Journal IEEE Transactions on Biomedical Engineering
Volume 47
Number 5
Publisher IEEE
Abstract Optical imaging is the video recording of two-dimensional patterns of changes in light reflectance from cortical tissue evoked by stimulation. We derived a method, extended spatial decorrelation (ESD), that uses second order statistics in space for separating the intrinsic signals into the stimulus related components and the nonspecific variations. The performance of ESD on model data is compared to independent component analysis algorithms using statistics of 4th and higher order. Robustness against sensor noise is scored. When applied to optical images, ESD separates the stimulus specific signal well from biological noise and artifacts.
Bibtex Type of Publication Selected:sources
Link to publication Link to original publication Download Bibtex entry

Navigation

Quick Access

Schnellnavigation zur Seite über Nummerneingabe