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@@ -2,12 +2,10 @@
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Data sets accompanying Liu et al., Nature Communications 2017: Inference of neuronal functional circuitry with spike-triggered non-negative matrix factorization.
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-**Data: Salamander retinal ganglion cells under finely structured spatio-temporal white noise**
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+### Data: Salamander retinal ganglion cells under finely structured spatio-temporal white noise
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-Contact:
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-Tim Gollisch
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-Email: tim.gollisch@med.uni-goettingen.de
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-Website: https://www.retina.uni-goettingen.de/
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+Contact:
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+Tim Gollisch, Email: tim.gollisch@med.uni-goettingen.de, Website: https://www.retina.uni-goettingen.de/
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This repository contains the main data that was analyzed in the paper
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@@ -17,7 +15,7 @@ The data set contains five multielectrode-array recordings of retinal ganglion c
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If you plan to use this data for a publication, please inform us about it and don’t forget to cite the original paper as well as the source of the data (DOI coming soon).
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-**Structure of the data**
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+### Structure of the data
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For each of the 5 recordings, the data are contained in a single binary Matlab file (.mat). When loaded into Matlab, it yields two three-dimensional arrays, named spk1 and spk2. spk1 contains the spike counts from the non-repeated white-noise sequences; spk2 the ones from the frozen noise.
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@@ -29,7 +27,7 @@ Thus spk1(3,100,7) yields the spike count in the 33-ms bin of cell number 3 in t
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(A good way to start familiarizing yourself with the data could be to compute PSTHs for the frozen noise by taking the responses of a single cell and averaging over trials. There should be fairly sparse peaks of activity (depending on the particular cell), which shows that the responses appear locked to particular time points in the frozen noise. The PSTHs for the non-repeated noise, of course, should be rather flat, except for fluctuations from finite data and for the very beginning of the PSTH, which is still influenced by the frozen noise).
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-**Reconstructing the stimulus**
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+### Reconstructing the stimulus
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To related the ganglion cell responses to the visual stimulus, one needs to recreate the applied sequence of binary white-noise patterns that were used to stimulate the retina. This can be done with the supplied Matlab script “recreate_spatiotemporal_white_noise_stimulus.m”. The comments in the script explain the usage and the format of the obtained stimulus sequence. In brief, the script successively computes the 1500 frames for each 50-sec trial of non-repeated noise and provides this sequence as a matrix in the form y-times-x-times-time (dimensions of 150x200x1500). These matrices are then saved into separate files, one for each trial. (But you can, of course, change this data handling according to your liking.) In the end, the script also provides the frozen noise in the same format for saving to disk.
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