Inter-Subject Correlation of EEG

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.

Inter-Subject Correlation of Eye movements

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.

Stimulus-Response Correlation of EEG

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.

The New-York Head

This is a detailed current-flow model of a standard head for targeting of Transcranial Electric Stimulation (TES) and EEG source localization. As we show in a recent paper, the TES forward model and EEG lead field are identical.

Automated MRI head segmentation

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).

Automated whole-head segmentation | Code and data

Whole-head Tissue Probability Map and fast processing routines to improve SPM results.

Morphologically accurate head segmentation | Code and data

Adds neighborhood priors to the ananatomical priors.


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.