Source Data Matamales 2019 aaz5751.rar (32.16 MB)
Source data for manuscript "Local D2- to D1-neuron transmodulation updates goal-directed learning in the striatum" by Matamales M, McGovern A, Mi JD, Mazzone S, Balleine BW & Bertran-Gonzalez J.
datasetmodified on 2019-12-18, 03:37
Complete dataset supporting the findings reported in the manuscript: "Local D2- to D1-neuron transmodulation updates goal-directed learning in the striatum" by Miriam Matamales, Alice E. McGovern, Mi JD, Stuart B. Mazzone, Bernard W. Balleine and Jesus Bertran-Gonzalez.
The authors confirm that all data underlying the findings are fully available without restriction. It includes timestamp data for behavioural experiments as well as quantitative analyses of fluorescence imaging data.
Med-PC software was used to direct the insertion and retraction of the levers, illumination of the light and delivery of the pellets. The software allowed the recording of timestamp events each 10 msec, including the number of lever presses, magazine entries and food pellets delivered throughout the duration of the experiment. A combination of Med State Notation language and customized MATLAB (MathWorks, Natick, MA) scripts were used to retrieve timestamp data. Individual events (left or right lever press, magazine entries, and pellet delivery) that occurred during each training session were recorded. The time at which each event occurred was stamped with a 10 ms resolution.
Fluorescent brain sections were imaged using a spinning disk confocal system equipped with the Diskovery multi-modal imaging platform (Andor Technology) and a Zyla 4.2 sCMOS camera (Andor Technology), that allows fast capture of large mosaic images and high-sensitivity high dynamic range imaging. The Diskovery platform was added to a Nikon Eclipse TiE microscope body with a motorized stage and the Nikon Perfect Focus System, and image acquisition was controlled by Nikon NIS-Elements software. Single high-magnification wide field-of-view images for each brain hemisphere were generated by automatically stitching multiple adjacent frames from within a defined area using the motorized stage. High-resolution mosaics of brain samples obtained with NIS-Elements were quantitatively analyzed using Fiji software. Resulting neuronal data, including position (x, y coordinates), area and mean grey value of the eGFP channel for each detected ROI, were exported in a tab-delimited spreadsheet format and imported into MATLAB.
NeuroscienceAnimal BehaviourExtinctionStriatumInstrumental learningDopamine receptorsspiny projection neuronsNuclear activityHistone H3neuromodulationQuantitative microscopyFluorescence microscopyAnimal BehaviourAnimal NeurobiologyAnimal Physiology - SystemsBehavioral NeuroscienceComputational BiologyNeuroscience