Public Code

Code for all methods described in my published papers are available on my GitHub page, largely in MATLAB and python.
  • Voxel-Level Functional Connectivity: MATLAB code implementing functional connectivity methods from "Voxel-Level Functional Connectivity using Spatial Regularization" and "Discovering Voxel-Level Functional Connectivity Between Cortical Regions." Sample data and a demo function are included. [GitHub] [zip]
  • MVPA Decoding: MATLAB code for performing category decoding from ROIs or whole-brain searchlights.[GitHub] [zip]
  • Parcellation of Brain Connectivity: MATLAB and python code implementing spatially-coherent clustering methods from "Parcellating connectivity in spatial maps." A demo function on synthetic data is included. [GitHub] [zip]
  • Event Segmentation: Implementations of the event segmentation model described in "Discovering event structure in continuous narrative perception and memory." The python version is available as part of the Brain Imaging Analysis Kit, and the MATLAB version is hosted on my personal GitHub account.

Public Datasets

  • Cortical Atlases
    • The 172-parcel atlas from Baldassano et al. (2015), Parcellating connectivity in spatial maps. PeerJ 3:e784; DOI 10.7717/peerj.784, derived from the original S500 group eigenmap release from the Human Connectome Project.
      • Atlas172.dscalar.nii: CIFTI-2 format, the HCP grayordinate coordinate system.
      • Atlas172.nii: A volumetric version of the atlas, in MNI space. Voxels whose centers were within 3mm of a surface grayordinate were set to the parcellation label of the closest grayordinate.
      • Atlas172_PPA.nii: A version of Atlas172 masked to contain only voxels in the Parahippocampal Place Area, defined by MNI-transforming PPA localizers from 24 subjects and keeping voxels where at least 5 subjects overlapped. PPA covers three parcels in each hemisphere, the most posterior approximately corresponding to PHC1 (#8 left, #93 right) and PHC2 (#17 left, #101 right), and an "anterior PPA" (#16 left, #100 right).
    • The scene networks from Baldassano et al. Two distinct scene processing networks connecting vision and memory. bioRxiv DOI: 10.1101/057406, in MNI space: twoNetworks.nii.gz
  • Maps from published papers
    • Maps from Baldassano et al. (2016), Human–Object Interactions Are More than the Sum of Their Parts. Cerebral Cortex, DOI: 10.1093/cercor/bhw077 [zip]

Interactive Vizualizations

  • WebGL Atlas: Interactive 3D viewer showing the 172-parcel resting state parcellation from Baldassano et al. (2015), Parcellating connectivity in spatial maps.