Data from: "Functional Parcellation of Mouse Visual Cortex Using Statistical Techniques Reveals Response-Dependent Clustering of Cortical Processing Areas"

<b>Abstract</b>The visual cortex of the mouse brain can be divided into ten or more areas that each contain complete or partial retinotopic maps of the contralateral visual field. It is generally assumed that these areas represent discrete processing regions. In contrast to the conventional input-output characterizations of neuronal responses to standard visual stimuli, here we asked whether six of the core visual areas have responses that are functionally distinct from each other for a given visual stimulus set, by applying machine learning techniques to distinguish the areas based on their activity patterns. Visual areas defined by retinotopic mapping were examined using supervised classifiers applied to responses elicited by a range of stimuli. Using two distinct datasets obtained using wide-field and two-photon imaging, we show that the area labels predicted by the classifiers were highly consistent with the labels obtained using retinotopy. Furthermore, the classifiers were able to model the boundaries of visual areas using resting state cortical responses obtained without any overt stimulus, in both datasets. With the wide-field dataset, clustering neuronal responses using a constrained semi-supervised classifier showed graceful degradation of accuracy. The results suggest that responses from visual cortical areas can be classified effectively using data-driven models. These responses likely reflect unique circuits within each area that give rise to activity with stronger intra-areal than inter-areal correlations, and their responses to controlled visual stimuli across trials drive higher areal classification accuracy than resting state responses.<br><br><b>About this dataset:</b>1. This dataset was collected from five adult mice (&gt;8 weeks old) of either sex. These mice expressed GCaMP6f or GCaMP6s in excitatory neurons of the forebrain. Data from each mouse is attached as a zip file named M1.zip through M5.zip 2. Retinotopic mapping of the visual cortex was first performed using periodic moving bars with checker-board texture. The boundaries of the 6 core visual areas were defined. These boundary information can be found in "retinotopy.mat" file inside each zip file. These retinotopically defined boundaries were considered as ground truth for delineating visual areas based on responses to different visual stimuli.3. Different visual stimuli were presented multiple times in a block design. The attached zip files contains the averaged responses in file called "data.mat". In addition we also collected resting state responses for few mice. 4. Further details on how this dataset was collected can be found in the manuscript<br><br><b>How to use the data:</b>A demo on how use this dataset to get results discussed in the paper is given here: http://bit.ly/3nPuiFv