CBI | ATR NIA Labs

Software

• VBMEG
  Estimate and visualize brain activities from MEG and/or EEG data. It can use various prior information on brain activities to improve their estimation accuracy. It can also visualize signal flows across brain regions.

• Sparase Estimation Toolbox
  Build a classification or regression model by automatically discarding non-relevant brain activities.

• SpatioTemporal Pattern estimation (STeP) toolbox
  Estimate repetitive spatiotemporal patterns from resting-state brain activity data

• Common Waveform Estimation (CWE) toolbox
  Estimate waveforms common across trials from trial data

• Sensor array Optimization based on Resolution Matrix (SORM) toolbox
  Design a sensor array of optically pumped magnetometers for accurately estimating the brain activity at target regions

Datasets

• MULTI-DIMENSIONAL SAMPLING OF INDIVIDUAL BRAINS (MULDS): Multi-modal and multi-task human brain imaging dataset
  – 5 subjects
  – Measurements: MEG+EEG, fMRI, NIRS(whole-head), T1-MRI, T2-MRI, diffusion MRI
  – Tasks: resting, face, language, audio-visual

• OPM-MEG, SQUID-MEG, and EEG (OSE) dataset
  The “OPM-MEG, SQUID-MEG, and EEG (OSE)” dataset aims to disseminate a new type of magnetoencephalography (MEG) device, an optically pumped magnetometer (OPM), which enables a wearable MEG measurement system. This dataset provides OPM-MEG, SQUID-MEG, and electroencephalography (EEG) data. Using this dataset, you can test the source imaging from the OPM-MEG data and compare the results with those from the conventional SQUID-MEG and EEG data.
  – 5 subjects
  – Measurements: OPM-MEG, SQUID-MEG, EEG, and T1-weighted image (T1)
  – Tasks: Motor, Auditory, Somatosensory, and Resting-state