storEEG is system for storing and managing large amounts of EEG data. It allows for search and selection of EEG datasets, easy exporting and epoching of data, automated management of file structures, and easy-to-use interface to label data files. Base on the standard Brain Imagin Data Structure (BIDS).
This component extraction technique was developed to analyze stimulus responses in EEG in the absence of regressors or time markers. We use this to understand the responses to video and auditory narratives.
Eye movements during video are also similar across subjects. We have used ISC of eye-movements to cluster subjects into groups with distinct viewing patterns.
This methods can identify what the brain encodes about the stimulus while simultaneously decoding the corresponding brain activity. It is a component extraction technique that works in the absence of precise time markers. We use this to understand the EEG responses to unique experiences, such as video games.
This is an anatomically detailed segmentation of the MNI standard head extended to include structures relevant to current-flow models (CSF, skull, scalp, neck). As we show in a recent paper, the resulting lead field is identical to the TES forward model and can thus be used for TES targeting as well as EEG source localization.
Individualized current-flow modeling starts with the MRI of an individual subject. The first task is to accurately segment the anatomy. These are a few tools based on SPM8, which we have developed for fully automated whole-head segmentation (not just brain).
Collaborating with Dr. Anli Liu at NYU Medical Center, we measured electric fields in vivo intracranially during TES on 10 subjects (~1300 electrodes). These data are used to validate and calibrate the computational models of TES. You can download these data to benchmark your own models.
This is a small software compiled from Matlab that can be used to quickly simulate tDCS on a sphere. Users can adjust the thickness of brain, CSF, skull and scalp, as well as their conductivities to see how these parameters affect the current-flow patterns inside the brain.
Introducing ROAST, a fully automated Realistic vOlumetric-Approach-based Simulator for Transcranial electric stimulation. Except Matlab, it runs on open-source software packages such as iso2mesh and getDP. It can give you a simulation of a bipolar config of tDCS from a 1 mm resolution MRI in 10~15 minutes.