Examples

This section contains Jupyter notebooks that illustrate functionality of the toolbox.

• Constructing 10-10 coordinates on segmented MRI scans
  • Load segmentation masks
  • Load hand-picked landmarks
  • Construct scalp surface and transform to scanner RAS
  • Construct landmarks
  • Visualize
• Basic single trial fNIRS finger tapping classification
  • Loading raw CW-NIRS data from a SNIRF file
  • Frequency filtering and splitting into epochs
  • Plot frequency filtered data
  • Block Averages
  • Training a LDA classifier with Scikit-Learn
• Image Reconstruction
  • Load a finger-tapping dataset
  • Calculate block averages in optical density
  • Load segmented MRI scan
  • Coordinate systems
  • The TwoSurfaceHeadModel
  • Optode Registration
  • Simulate light propagation in tissue with MCX
  • Plot fluence
  • Plot concentration changes
• Photogrammetric Optode Coregistration
  • Choose between interactive and static 3D plots
• Channel Quality Assessment, Pruning, and Motion Artifact Detection
  • Loading raw CW-NIRS data from a SNIRF file and converting it to OD and CONC
  • Channel Quality Metrics: SNR
  • Channel Quality Metrics: Channel Distance
  • Channel Quality Metrics: Mean Amplitudes
  • Channel Pruning using Quality Metrics and the Pruning Function
  • Detecting Motion Artifacts and generating the MA mask
  • Refining the MA Mask
• Calculating the Scalp Coupling Index
  • Loading raw CW-NIRS data from a SNIRF file
  • 0. Utilities
  • 1. Bandpass filter to extract the cardiac signal
  • 2. Normalize filtered amplitudes
  • 3. Moving windows
  • 4. Calculate the correlation coefficient for each window
  • 5. Illustrate heat maps of SCIs for the whole recording and all channels
  • 6. Inspect time courses of good and bad channels
  • 7. Calculate a quality mask for each sample of the recording
• Storing estimated HRFs in snirf files
  • Load a finger-tapping dataset
  • Calculate concentrations
  • Frequency filtering and splitting into epochs
  • Blockaveraging to estimate the HRFs
  • Store HRFs
  • Inspect snirf file
  • Read HRFs from snirf file
  • Plot the HRFs
  • Tidy up
• Xarray Data Structures - an fNIRS example
  • Loading raw CW-NIRS data from a SNIRF file
  • Amplitude data
  • Montage information
  • Beer-Lambert transformation