ICA for Optical Recording Data

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Downloads (for use in Matlab)

Usage Example

>> load ica_example_traces.mat
>> plot_traces(mixed_traces)


>> [wts,sph] = runica(mixed_traces,'sphering','off'); % Please see documentation in runica.m for documentation on available parameters.
>> components = wts * mixed_traces;
>> plot_traces(components)


When you run ICA on the example data, components may vary from those shown in order and sign. Example mixed traces are composed of a random linear mixture of intracellular recordings and simulated white noise. The original traces are included in the matfile in the variable original_traces. These traces are also used as an example in Figure 1, Hill, Moore-Kochlacs, et al, 2010 (see below).

Further Papers

  • Hill, E.S; Moore-Kochlacs, C.; Vasireddi, S. K.; Sejnowski, T. J.; Frost, W.N.; Validation of Independent Component Analysis (ICA) for rapid spike sorting of optical recording data, Journal of Neurophysiology, 104, 3721, 2010 (PDF)
  • ICA applied to invertebrate voltage sensitive dye recordings: Brown, G.D., Yamada, S.; Nakashima, M.; Moore-Kochlacs, C,; Sejnowski, T. J.; Independent Component Analysis of Optical Recordings from Tritonia Swimming Neurons, Institute for Neural Computation, University of California at San Diego Technical Report, INC-08-001, 2008 (PDF)
  • Siegel, R. M.; Duann, J.-R.; Jung, T.-P.; Sejnowski, T. J.; Spatio-Temporal Dynamics of the Functional Architecture for Gain Fields in Inferior Parietal Lobule of Behaving Monkey, Cerebral Cortex, 17, 378-390, 2007 (PDF)
  • Brown, G. D.; Yamada, S.; Sejnowski, T. J.; Independent Component Analysis at the Neural Cocktail Party, Trends in Neuroscience, 24(1), 54-63, 2000 (PDF)

Questions? Email Caroline Moore-Kochlacs.

Last update: 4-Jan-11