Simulate Ca Video

This project provides a MATLAB function Simulate_Ca_video to simulate calcium imaging videos with various parameters and options. This documentation will guide you through the usage, parameters, and inner workings of the function.

Quick Start

To get started, you can call the function with default or customized parameters:

[out, Mot, outpath, file_name, A] = Simulate_Ca_video('Nneu', 100, 'ses', 2, 'CA1_A', true, 'PNR', 1);

For detailed information on each parameter and sub-function, please refer to the Function Documentation section.

Function Documentation

Syntax

[out, Mot, outpath, file_name, A] = Simulate_Ca_video(varargin)

Description

The Simulate_Ca_video function generates simulated calcium imaging videos with neural data, motion artifacts, and noise. It allows for customization of various parameters including the number of neurons, sessions, frame rate, and more.

Parameters

• 'outpath': Output path where simulation results will be saved.
• 'min_dist': Minimum distance between neurons in the simulated data.
• 'Nneu': Number of neurons to be simulated.
• 'PNR': Peak-to-Noise Ratio for the simulated data.
• 'd': Dimensions of the simulated video frames (width and height) in pixels.
• 'F': Frame rate (frames per second) for the simulated calcium video data.
• 'overlap': Proportion of neurons remapping across multiple sessions.
• 'motion': Inter-session misalignment amplitude.
• 'motion_sz': Size of the motion effect applied to the frames.
• 'translation': Add translation misalignment in addition to Non-rigid motion.
• 'ses': Number of sessions to be generated.
• 'seed': Random number generator seed.
• 'B': Baseline id for different baseline images.
• 'spike_prob': Probability distribution parameters for spike events.
• 'save_files': Flag to save simulation results.
• 'create_mask': Flag to create a mask during the simulation.
• 'comb_fact': Combination factor used in the simulation process.
• 'drift': Presence of drifting activities in the simulated data.
• 'LFP': Flag to simulate Local Field Potentials data.
• 'sf': Scaling factor used in the simulation process.
• 'plotme': Flag to generate plots during simulation.
• 'invtRise': Parameters related to the rising phase of calcium signals.
• 'invtDecay': Parameters related to the decaying phase of calcium signals.
• 'disappearBV': Erode baseline value.
• 'CA1_A': Change neurons shapes across sessions using CA1 data.
• 'A2': Use CA1 neurons shapes instead of DG.
• 'force_active': Ensure all neurons have at least one Calcium transient per session.

Usage Examples

% Example 1
[out, Mot, outpath, file_name, A] = Simulate_Ca_video('Nneu', 100, 'ses', 2, 'CA1_A', true, 'PNR', 1);

% Example 2
[out, Mot, outpath, file_name, A] = Simulate_Ca_video('Nneu', 50, 'ses', 1, 'F', 18000, 'LFP', 8, 'spike_prob', [-4.91, 0.83], 'sf', 60);

% Example 3
[out, Mot, outpath, file_name, A] = Simulate_Ca_video('Nneu', 300, 'ses', 20, 'F', 1500, 'motion', 0, 'min_dist', 2, 'spike_prob', [-2, 0.83], 'A2', true, 'overlap', 0.2);

Detailed Function Workflow

1. Initialize Variables: Using int_var to parse input parameters.
2. Create Baselines: Generate baseline images using create_baseline.
3. Create Neural Data: Generate neural data using create_neuron_data.
4. Apply Overlapping Mask: Apply remapping and drifting effects to the data.
5. Add Non-Rigid Motion: Introduce motion artifacts to the sessions using Add_NRmotion.
6. Create Noise Data: Generate and add noise to the simulated data.
7. Integrate Model: Combine all components to form the final simulated video.
8. Save Results: Save the output if the save_files flag is set.

Sub-Functions

int_var

Parses and initializes input parameters for the simulation.

get_out_path

Determines the output path for saving simulation results.

create_baseline

Generates baseline images for the simulation.

add_remapping_drifting

Applies remapping and drifting effects to the neural data.

Add_NRmotion

Adds non-rigid motion artifacts to the sessions.

saveash5

Saves data in HDF5 format.