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NeuroFdpToolbox

MATLAB toolbox to automatically detect and analyse fractional Lévy motions of propagating neural activity patterns, developed by Dr. Pulin Gong's group at University of Sydney. This toolbox includes the generation of a spiking neural network model, and the detailed processes for analysing our simulated and experimental data. If you use our code in your research, please cite us as follows:

Liu Y., Long X., Martin PR, Solomon SG and Gong P., Lévy walk dynamics explain gamma burst patterns in primate cerebral cortex. Communications Biology, volume 4, Article number: 739 (2021). https://www.nature.com/articles/s42003-021-02256-1

Network generation

A spiking neural circuit simulation model edited by Yifan Gu, Yuxi Liu, James Henderson, Guozhang Chen. The instruction is detailed in the readme file in the sub-folder.

SpikeNet is a software that has three stand-alone components.

  1. User interface for configuring spiking neuronal networks
  2. A c++ simulator
  3. User interface for parsing and post-analyzing the simulation results.

The design of SpikeNet provides the following four main features.

  • Configurability SpikeNet supports any user-defined structure of synaptic connectivity topologies, coupling strengths and conduction delays. It can be easily extended by developers to support any variations of integrate-and-fire neuron and synapse models.

  • Performance Simulation of spiking neuronal network quickly becomes computationally intensive if the number of neurons in the network exceeds a few thousand. To achieve superior performance, various measures have been taken at both algorithmic and implementation level.

  • User-friendly interface In SpikeNet, although c++ is used for heavy-duty computation, its user-interface is written in high-level programming language (Matlab) for user-friendliness and fast prototyping. This means SpikeNet does not require non-developer users to be familiar with c++.

  • Scalability The design of the SpikeNet c++ simulator readily supports parallel computing using Message Passing Interface (MPI). Additionally, the HDF5-based I/O file format provides big data handling capability. Also Portable Batch System (PBS) scripts for array jobs are provided if the you have access to a cluster.

Simulation data analysis

The matlab function for generating the neuron microcircuit is main_Gamma.m The detection, analysis and visualization of the fractional propagating patterns in the simulation data can be found in the folder model_data_analysis, such as GetBurst2.m; LFPAmpPattern5.m; MSDAnalysis.m; SpikeMatchLFPPhase.m; SpikesVSLFPPattern.m; Visualization3DLFPBurst.m; get_MSD_PBC.m, etc. The code to generate the figure 4-6 in the paper "Lévy walk dynamics explain gamma burst patterns in primate cerebral cortex" can be found in the sub-folder experimental_data_analysis/New/GammaPaperFig1-4.

Experimental data analysis

The detection, analysis and visualization of the fractional propagating patterns in the experimental data can be found in the main function Project1.m in the sub-folder experimental_data_analysis/Toolbox_CSC. An example movie of the experimental data can be found:

Example superdiffusive gamma burst pattern movie

The full data can be shared upon requested. The code to generate the figure 2 and figure 3 in the paper "Lévy walk dynamics explain gamma burst patterns in primate cerebral cortex" can be found in the sub-folder experimental_data_analysis/Toolbox_CSC/p1.

Authors