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Independence and Coherence in Temporal Sequence Computation across the Fronto-Parietal Network

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Figshare2026-02-17 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Independence_and_Coherence_in_Temporal_Sequence_Computation_across_the_Fronto-Parietal_Network/30188239
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The dataset contains large-field-of-view two-photon calcium imaging recordings of neural activity from six mice, along with the processed data used for the paper's figures. During the experiments, each mouse received water rewards at alternating intervals of 6 and 12 seconds. A single trial is defined as the combination of one 6-second and one 12-second intervalThe neural activity files include the following information:Neural activity dataSpatial coordinates of each neuronLick data indicating whether the mouse licked the spoutRecording areasGC008, WT161: Neural activity in M2 and PPC was recorded in separate fields of view.Other mice: Neural activity was recorded from multiple regions, including M2, M1, sensory, RSD, PPC, vision, and others.Data structuretime_neuron: A structure array. Each field corresponds to a brain region and contains a matrix of size “time × cells.”time_neuron_trial: Similar to the above, but segmented into trials (18 seconds each), forming a “time × cells × trials” matrix.neuron_coordinate: A structure array. Each field corresponds to a region and contains a cell array, with one entry per cell. Each entry is an (n × 2) matrix listing the (x, y) pixel coordinates of all pixels belonging to that neuron in the imaging data.Lick-related datalick_binary_time: A binary time series (1 for lick, 0 for no lick).lick_binary_trial: The above segmented into trials.lickrate_time: Time series converted to licking frequency (Hz).lickrate_trial: The above segmented into trials.Additional data (for mice other than GC008 and WT161)totalimage: The mean image of the entire imaging session.hmreffinal: Data indicating the locations of each brain region.The remaining data files contain the underlying data for the figures in the paper. Each dataset is saved in either Excel or .mat format. For the analysis and simulation scripts, please refer to the following GitHub repository.https://github.com/hiroto726/TwinRNN
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2026-02-17
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