PLView

Versión 1.0.9.4 (3,33 MB) por UV
ECoG Data Processing and Visualization
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Actualizado 8 ene 2026

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PLView is a comprehensive MATLAB application designed for interactive visualization and analysis of brain connectivity from electrocorticography (ECoG) recordings. Developed as part of neuroscience research at Bar-Ilan University's Neural Processing and Brain Networks Lab, this tool enables researchers and clinicians to explore Phase Locking Value (PLV) connectivity patterns across brain networks in an intuitive, visual interface.
Key Features
Interactive 3D Brain Visualization
  • Real-time 3D brain model with electrode placement
  • Dynamic connectivity lines showing synchronization strength
  • Fully rotatable view with mouse controls
  • Color-coded electrodes by brain network (FPN, DMN, CON, MOTOR, etc.)
Comprehensive Connectivity Analysis
  • Phase Locking Value (PLV) computation between all electrode pairs
  • Cross-frequency coupling analysis (Phase-Amplitude coupling)
  • Support for multiple frequency bands (Delta, Theta, Alpha, Beta, Gamma, High Gamma)
  • Automated filtering and Hilbert transform processing
Dual Visualization Modes
  • 3D Brain Model: Spatial representation of electrodes on cortical surface with arched connectivity lines
  • 2D Circular Graph: Complete connectivity matrix visualization with dynamic color-coding
Flexible Analysis Parameters
  • Switch between experimental conditions (Rest, Easy Task, Hard Task)
  • Select frequency bands for phase and amplitude analysis
  • Toggle electrode role (phase vs amplitude)
  • Show/hide electrode labels
  • Interactive electrode selection for detailed connectivity exploration
Detailed Information Panel
  • Patient metadata and electrode count
  • Strongest connection identification (global and per-electrode)
  • MNI coordinates for selected electrodes
  • Network classification for each electrode
  • Dynamic updates based on user selection
Scientific Background
PLView implements Phase Locking Value analysis as described in neuroscience literature for measuring functional connectivity. The tool specifically focuses on:
  • Executive Function Networks: Analyzing the Frontoparietal Network (FPN) activity during cognitive tasks
  • Cross-Frequency Coupling: Computing phase-amplitude coupling between low-frequency phase (Beta: 12-30 Hz) and high-frequency amplitude (High Gamma: 70-250 Hz)
  • Task-Based Connectivity Changes: Comparing brain network synchronization across rest and cognitive load conditions
Use Cases
Clinical Applications
  • Intraoperative brain mapping during awake craniotomy
  • Identification of critical functional areas before tumor resection
  • Preservation of executive function networks during surgery
Research Applications
  • Network neuroscience studies of cognitive control
  • Brain connectivity analysis in clinical populations
  • Methodological development in ECoG signal processing
Technical Highlights
Architecture
  • Built with MATLAB App Designer for robust GUI development
  • Modular code structure with clear separation between processing and visualization
  • Efficient matrix operations for PLV computation across electrode pairs
  • Custom colormap implementation for intuitive connectivity representation
Performance
  • Processes complete ECoG datasets in seconds
  • Real-time visualization updates
  • Smooth 3D rendering with optimized graphics pipeline
  • Responsive UI with loading animations during data processing
Data Handling
  • Supports .mat file format (standard in neuroscience research)
  • Automatic electrode filtering based on network classification
  • Reference channel detection and exclusion
  • Trial concatenation and trimming according to experimental protocols
Installation
  1. Download from MATLAB File Exchange
  2. Add to MATLAB path or install via Add-On Explorer
  3. Launch from Apps tab
Requirements: MATLAB R2022b or later (created with R2024b)
Workflow
  1. Upload Data: Load .mat file containing ECoG recordings
  2. Select Condition: Choose experimental condition (Rest/Easy/Hard task)
  3. Configure Parameters: Set frequency bands for connectivity analysis
  4. Explore: Click electrodes to view individual connectivity patterns
  5. Analyze: Use visual and textual information to identify network organization
Data Format
The tool expects MATLAB .mat files containing:
  • ECoG time series data for multiple electrodes
  • Electrode metadata (names, MNI coordinates, network classifications)
  • Experimental condition labels
  • Sampling rate information (default: 2000 Hz)
Visualization Features
Color Coding
  • Networks: Each brain network has a distinct color (FPN, DMN, CON, MOTOR, etc.)
  • Connectivity: Custom gradient colormap (dark blue → purple → red → orange → white) represents PLV strength
  • Selection: Yellow highlighting for selected electrodes and their connections
Interactive Elements
  • Hover over axes for quick export options
  • Click electrodes for detailed connectivity view
  • Rotate 3D brain model freely
  • Dynamic colorbar showing PLV value range
Scientific Validation
Results from PLView align with published neuroscience literature showing:
  • Increased FPN connectivity during cognitively demanding tasks
  • Reduced DMN-FPN connectivity during focused attention
  • Beta-High Gamma phase-amplitude coupling in cognitive control
Future Development
Potential enhancements include:
  • Real-time processing for intraoperative use
  • Multi-patient comparison and group-level statistics
  • Additional connectivity metrics (coherence, causality measures)
  • Time-resolved connectivity visualization
  • Support for raw data with built-in preprocessing pipeline
____________________________________________________________
Credits
Developer: Yuval Zur
Academic Supervisor: Dr. Yaara Erez
Project Supervisor: Shir Hartman
Institution: Bar-Ilan University, Faculty of Engineering
Lab: Neural Processing and Brain Networks Lab ('Erez Lab')
Project Year: 2024-2025 (Oct-Oct)
References
Based on methodologies from:
  • Assem et al. (2023). "High gamma activity distinguishes frontal cognitive control regions from adjacent cortical networks." Cortex, 159, 286-298.
  • Lachaux et al. (1999). "Measuring Phase Synchrony in Brain Signals." Human Brain Mapping, 8, 194-208.
License
This tool was developed for academic and research purposes. Please contact the author for usage permissions and collaboration inquiries.
Keywords: ECoG, Brain Connectivity, PLV, Phase Locking Value, Neuroscience, Brain Networks, Visualization, MATLAB, Neurosurgery, Cognitive Neuroscience, Functional Connectivity, Frontoparietal Network

Citar como

Zur, Y. (2025). PLView: Visualization Tool for Brain Mapping with Electrical Stimulation and Brain Activity Recordings. (https://www.mathworks.com/matlabcentral/fileexchange/182041) Bar-Ilan University Capstone Project.

Compatibilidad con la versión de MATLAB
Se creó con R2024b
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
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Versión Publicado Notas de la versión
1.0.9.4

- Updated repository's 'Overview' tab.
1.0.9.3

- Fixed ElectrodesData source.
1.0.9.2

- Fixed ElectrodeRoleChanged function.
1.0.9.1

- Change the main window state to maximized on startup.
1.0.9

- Edited the left menu to be less confusing. (removed Switch Frequency button and add Selected Electrode Role radio menu)
1.0.8

- Deleted unnecessary functions

1.0.7

Updated the data processing to be more robust (can handle multiple stripes in the same test condition) and to ignore the reference electrode.
1.0.6

- Fixed missing variable assignment. (where app.CurrentConditionData remained empty)
1.0.5

- Changed variable name from 'trials' to 'trialsData'.
1.0.4

- Updated the trials stacking loop to be more robust. supporting numeric array and cell array.
1.0.3

- Updated trials path (from PatientData.patient_data.data_all... to PatientData.data_all...)
1.0.2

- Updated PatientName to store the last 7 characters of the uploaded .mat file (i.e "2017_02") instead of the first 7.
1.0.1

- Updated icons to supported .PNG format
- Updated the function locating the 3D brain mesh file
1.0