graph LR
Data_Ingestion_Loading_Module["Data Ingestion/Loading Module"]
Signal_Processing_Module["Signal Processing Module"]
Network_Construction_Module["Network Construction Module"]
Network_Analysis_Module["Network Analysis Module"]
Statistical_Analysis_Module["Statistical Analysis Module"]
Visualization_Reporting_Module["Visualization/Reporting Module"]
User_Interface_GUI_["User Interface (GUI)"]
Configuration_Management["Configuration Management"]
Data_Ingestion_Loading_Module -- "sends raw data to" --> Signal_Processing_Module
Configuration_Management -- "provides parameters to" --> Data_Ingestion_Loading_Module
Signal_Processing_Module -- "sends processed spike data to" --> Network_Construction_Module
Network_Construction_Module -- "sends constructed network structures to" --> Network_Analysis_Module
Configuration_Management -- "provides parameters to" --> Network_Construction_Module
Network_Analysis_Module -- "sends analysis results to" --> Statistical_Analysis_Module
Statistical_Analysis_Module -- "sends statistical findings to" --> Visualization_Reporting_Module
Visualization_Reporting_Module -- "sends data for display to" --> User_Interface_GUI_
User_Interface_GUI_ -- "sends user inputs to" --> Configuration_Management
Configuration_Management -- "provides parameters to" --> Signal_Processing_Module
Configuration_Management -- "provides parameters to" --> Network_Analysis_Module
Configuration_Management -- "provides parameters to" --> Statistical_Analysis_Module
click Signal_Processing_Module href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MEA-NAP/Signal_Processing_Module.md" "Details"
click Network_Construction_Module href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MEA-NAP/Network_Construction_Module.md" "Details"
click Network_Analysis_Module href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MEA-NAP/Network_Analysis_Module.md" "Details"
click Statistical_Analysis_Module href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MEA-NAP/Statistical_Analysis_Module.md" "Details"
click Visualization_Reporting_Module href "https://github.com/CodeBoarding/GeneratedOnBoardings/blob/main/MEA-NAP/Visualization_Reporting_Module.md" "Details"
One paragraph explaining the functionality which is represented by this graph. What the main flow is and what is its purpose.
Responsible for loading raw neural data from various proprietary formats (e.g., Axion Biosystems, MCS data loaders) into a standardized, in-memory representation suitable for subsequent processing. This module handles file parsing and initial data validation.
Related Classes/Methods: None
Signal Processing Module [Expand]
Performs pre-processing on the raw neural data, including filtering, noise reduction, spike detection, and spike sorting. Its primary output is clean, processed spike train data ready for network inference.
Related Classes/Methods: None
Network Construction Module [Expand]
Builds network representations, typically connectivity matrices, from the processed neural data. This module infers functional or structural connections between neural elements, often utilizing the Spike Time Tiling Coefficient (STTC) to establish relationships based on spike timing. It translates temporal spike patterns into a graph-theoretic structure.
Related Classes/Methods: None
Network Analysis Module [Expand]
Analyzes the constructed network representations using various graph theory metrics and algorithms (e.g., from the Brain Connectivity Toolbox - BCT). This includes calculating measures like node degree, clustering coefficient, path length, and modularity to characterize network topology.
Related Classes/Methods: None
Statistical Analysis Module [Expand]
Performs statistical tests and comparisons on the network analysis results. This module can compare network metrics across different experimental conditions, identify significant differences, and assess the robustness of findings.
Related Classes/Methods: None
Visualization/Reporting Module [Expand]
Generates visual representations (e.g., network plots, heatmaps, statistical charts) and comprehensive reports of the processed data, constructed networks, analysis results, and statistical findings. It aims to present complex data in an intuitive and interpretable manner.
Related Classes/Methods: None
Provides a graphical interface for users to interact with the entire pipeline. This includes configuring analysis parameters, initiating data processing, monitoring progress, and viewing results. It acts as the primary point of user interaction for the desktop application.
Related Classes/Methods: None
Centralizes and manages all configurable parameters and settings for the entire pipeline, such as file paths, processing thresholds, STTC parameters, and analysis options. It ensures consistency, reproducibility, and ease of modification across different analysis runs.
Related Classes/Methods: None