Electrophysiology data and code related to grid cell encoding of head direction

This dataset contains electrophysiology data, data on animal position in open field, spike sorting results and information on synchronizing the ephys and position data, as well code to run for example motion tracking and spike sorting, as well as statistical analyses.Background of studyThe study addresses the mechanisms of spatial cognition and memory; investigating whether neurons that use grid codes (neurons active at vertices of grid of tessellating triangles) also provide info about head direction.Grid cells have grid fields that lack selectivity for head direction or other navigation variables. Conjunctive cells have grid fields that manifest only when animal moves in particular direction. The study specifically investigates global and local modulation of grid cell firing by head direction - including selectivity of grid cell firing for head direction (distinct to direction tuning of conjunctive cells). Mouse dataTetrode electrophysiological data were recorded from p038 mice, data analysed in Python and R, with spike sporting performed via an automated analysis and clustering pipeline based around MountainSort. Head direction was recorded via a custom Bonsai script to track red and green polystyrene balls attached to either side of the mouse’s head. Mice were handled three times a week for 5 - 10 minutes for four weeks following surgery.Neurons were then classified using grid and head direction scores. Statistical analyses were performed to compare the observed data with 1000 shuffled data sets and evaluate significance of firing rate and head direction results.Rat data was downloaded from the Kavli Institute’s online database (https://www.ntnu.edu/kavli/research/grid-cell-data). MATLAB files held trajectory of the animal and firing times of sorted cells. These were converted into a spatial data frame similar to the mouse data so the same analysis scripts could be used to perform all analyses.Stellate cell model: The model stellate cell used a previous morphological reconstruction of a mouse MEC layer 2 stellate cell. All simulations were performed in the NEURON simulation environment. Simulation code will be available at https://github.com/MattNolanLab. Sample size:324 recorded neurons in the medial entorhinal cortex (MEC)15 mice179 recording sessions 2-16 sessions per animal, mean = 11.2, standard deviation = 4.1 sessionsData files:Spike sorted data are available at Edinburgh Datashare: https://doi.org/10.7488/ds/2855 Analysis code is available on Github: https://github.com/MattNolanLab/grid_cell_analysis Raw electrophysiology data are available as part of this data record in openephys format, with one file per channel and accompanying parameters, settings, and visually identified broken channels. Data files are organised by sample into 30 .7z archive files, named according to the identity of the animal, recording date and time.