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@@ -2,13 +2,13 @@
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## Summary
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-Here we provide the complete data for the article 2022 article: 'State-dependent pupil dilation rapidly shifts visual feature representations'.
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+Here we provide the complete data for the article Franke, Willeke et al. Nature 2022 'State-dependent pupil dilation rapidly shifts visual feature representations'.
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-The data consists of 50 individual datasets (i.e. scans) of calcium activity of L2/3 neurons in mouse V1. All datasets were acquired through two-photon imaging.
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+The data consists of 50 individual datasets (i.e. recording scans) of calcium activity of L2/3 neurons in mouse V1. All datasets were acquired using two-photon imaging of awake, head-fixed mice.
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## Downloading the data
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#### Using the web browser
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-When clicking the `download` button at the top right, a the whole repository will be downloaded as a zipped file. However, large datafiles will be skipped and a placeholder is downloaded instead. To download the large data files in the sub-directories (either `.h5` or `.zip`), download the files individually from the web interface by clicking on them in the repository browser.
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+When clicking the `download` button at the top right, the whole repository will be downloaded as a zipped file. However, large datafiles will be skipped and a placeholder is downloaded instead. To download the large data files in the sub-directories (either `.h5` or `.zip`), download the files individually from the web interface by clicking on them in the repository browser.
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# Repository structure
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@@ -17,7 +17,7 @@ The datasets are divided into sub-directories based on the experimental paradigm
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**Imagenet scans** contain the neuronal activity in response to colored naturalistic images.
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-We used these scans as the training data for deep convolutional neural networks to learn an *in-silico* model of the recorded neuronal population.
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+We used these scans for training deep convolutional neural networks to learn an *in-silico* model of the recorded neuronal population.
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**Dotmap scans**: A sparse noise paradigm for mapping receptive fields of visual neurons. We used these scans to confirm the predictions from our *in-silico* analysis.
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