Maze_analysis

Simulation of place cell population activities (encoding either Euclidean- or graph-based position) and computational analysis of the generated data..

Synthetic data

The folder data_generation/ contains the code to generate sythetic data. Run generate_data.py to generate sythetic data

The following paramaters can be changed at the top of the file:

• USE_CUSTOM_SETTINGS: if set to 1, custom settings are used. If set to 0, default settings are used-
• PLOT: Whether to display the synthetized data
• SAVE: Whether to save the synthetized data.

Saving

The data is saved in the folder generated_data/.

For each experiment, three class objects (corresponding to trajectory, maze and place cells) are saved as .pkl files and a summary text file is generated. The summary file contains information about the time of the experiment and the main settings.

Settings

Custom settings can be defined in settings/custom_settings.py:

maze settings

• size: width of the maze
• octogonalMaze: whether to use a octogonal or square cells
• cellList: list of cells involved in each maze configuration
• edgeList: lists of connected cells (one list per maze configuration)
• nodeList: list of node cells (one list per maze configuration)
• nb_of_trials: number of maze configuration. Shall be consistent with cellList, edgeList and nodeList.
• homes: list of home positions for each maze configuration
• goals: list of goal positions for each maze configuration
• resolution: pixel width of each cell. The resolution is involved in computations to find out whether a point is contained in a cell.

trajectory settings

• type: "point_to_point" or "random_walk"
• n_traj: list containinf the number of trajectories generated per maze configuration
• n_steps: number of steps per trajectory (only for random walk)
• step_size
• p_drift: strength of the drift towards goal positiom (between 0 and 1. 0 gives random walk, 1 gives direct trajectory to the goal node)
• angular_res: angule resolution of the trajectory, i.e. number of directions the rat can move toward.
• speed_variabilty: variability of the step size (in percentage of step_size)

firing settings

• hyp: hypothesis. "euclidean" or "graph"
• n_neurons: number of neurons (place cells)
• std: std of the gaussian function (for firing rate computation)
• nu_max: max firing rate of the neurons
• noise_on_rate: noise level on the firing rates (in percentage of the max firing rate)
• noise_on_field: noise on place field centers' positions. For each place field center coordinate, the noise is randomly (uniform dist) chosen between -noise_on_field and +noise_on_field.