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Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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Data set for "Cell type-specific membrane potential changes in dorsolateral striatum accompanying reward-based sensorimotor learning"

Authors: Sippy, Tanya; Chaimowitz, Corryn; Crochet, Sylvain; Petersen, Carl;

Data set for "Cell type-specific membrane potential changes in dorsolateral striatum accompanying reward-based sensorimotor learning"

Abstract

Data set for: Sippy T, Chaimowitz C, Crochet S, Petersen CCH (2021) Cell type-specific membrane potential changes in dorsolateral striatum accompanying reward-based sensorimotor learning. FUNCTION 2: zqab049. https://doi.org/10.1093/function/zqab049 There are 2 files in this upload: 1. The file named "2021_Sippy_FUNCTION.pdf" is the Open Access pdf of the online publication in FUNCTION. 2. The file named "Sippy_data_code.zip" (~5 GB) is a zipped version of a folder ‘Sippy_data_code’, which contains the data analyzed in the study along with the Matlab codes used to generate the published figures. To access the data and the codes, first unzip the file, add the folder with subfolders to the Matlab path and run the different codes. The current folder must be the main folder (‘Sippy_data_code’). You first need to run ‘AnalyzeDataStructure.m’ and afterwards you can run the other codes. Each code computes and plots the results used in the corresponding figure. Figures are saved in the subfolder ‘Figures’. The subfolder ‘Data’ contains the data structure ‘Data.mat’ to be analyzed, as well as a Matlab file called ‘p_value_colormap.mat’ used to plot the p value color bars in some figures. The subfolder ‘Functions’ contains functions called by the main codes. The subfolder ‘Codes’ contains the following codes: ‘AnalyzeDataStructure.m’: computes the results and saves them as a new data structure called ‘Analyzed_Data’, in the subfolder ‘Results’. ‘Figure_1.m’: computes and plots the results for the panels D, E and F of Figure 1. ‘Figure_2.m’: computes and plots the results for the panels D-G and I-K of Figure 2. ‘Figure_3.m’: computes and plots the results for the panels A-F of Figure 3. ‘SuppFigure_2.m’: computes and plots the results for the panels B, D and F of Supplementary Figure 2. ‘SuppFigure_3.m’: computes and plots the results for the panels A-D of Supplementary Figure 3. ‘SuppFigure_4.m': computes and plots the results for the panels A-C of Supplementary Figure 4. The data structures contain the following fields: ‘Mouse_Name’: name of the mouse. ‘Mouse_RecordingDate’: date of recording (YMD). ‘Mouse_DateOfBirth’: date of birth of the mouse (YMD). ‘Mouse_Sex’: sex of the mouse (F or M). ‘Mouse_Genotype’: genotype of the mouse (strain of the two parents): A2A-Cre = Adora2a-Cre mice; D1-Cre = Drd1a-Cre mice; TdTomato = Lox-Stop-Lox-tdTomato mice; D1TdTomato = Drd1a-tdTomato mice; D2GFP = Drd2-GFP mice. ‘Mouse_Level’: Training level (NAÏVE or EXPERT). ‘Cell_Counter’: cell recorded in a given mouse. ‘Cell_Type’: type of the recorded cell (dSPN, iSPN or TAN). ‘Cell_TargetedBrainArea’: Brain area targeted (DLS). ‘Cell_Recovered’: Indicate cells that have been labelled and anatomically recovered (TRUE). ‘Cell_Coordinates’: Cell coordinates (in mm) relative to bregma (Lateral, AP, Ventro-dorsal) ‘Cell_Fluorescence’: expression of the genetically encoded fluorophore (FALSE or TRUE) and fluorophore (TdTomato or GFP). A neuron recorded in a Drd1a-tdTomato x Drd2-GFP (cf Mouse_Genotype) with Cell_Fluorescence= {TRUE, TdTomato} is considered as a dSPN (cf Cell_Type). ‘Sweep_Counter’: number of the sweep recorded for a given neuron (data were acquired across successive continuous sweeps of 30-300 s). ‘Sweep_Type’: experimental condition during that sweep (characterization = electrophysiological identification of the neurons; behavior = behavioral task). ‘Sweep_MembranePotential’: membrane potential recording (mV) after cutting of the APs. ‘Sweep_CurrentInjected’: current injected into the cell (pA). ‘Sweep_PiezoLick’: voltage signal from the piezo sensor attached to the water spout used to detect licking in behavior sweeps. ‘Sweep_Trial’: voltage command triggering the onset of each trial (both Catch and Stimulus trials) in behavior sweeps. ‘Sweep_WhiskerStim’: voltage command triggering the onset of each whisker stimulus in behavior sweeps. ‘Sweep_Valve’: voltage command triggering the opening of the valve delivering the reward in Hit trials. ‘Sweep_SamplingRate’: sampling rate (sample.s-1) of the recorded signals for each sweep. ‘Sweep_TimeStamp’: time at the beginning of the recorded sweep (H/min/s). ‘Sweep_Reward’: voltage command indicating reward availability during the response window following whisker stimulus in behavior sweeps. ‘Sweep_APThresh’: Threshold (V) used to detect action potentials (AP) during current injection.

{"references": ["Sippy T, Chaimowitz C, Crochet S, Petersen CCH (2021) Cell type-specific membrane potential changes in dorsolateral striatum accompanying reward-based sensorimotor learning. FUNCTION 2: zqab049. https://doi.org/10.1093/function/zqab049"]}

Keywords

licking, mice, whole-cell recording, striatonigral neuron, striatum, dorsolateral striatum, striatopallidal neuron, whisker sensory perception, membrane potential, striatal projection neuron, cholinergic striatal interneuron, reward-based learning

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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