Code Orange

lab software is stored and updated on our GitHub

This page merely serves to introduce some highlights. On the actual website, we try to keep functions documented where possible, but if any issues arise, we’ll do the best we can to respond to submissions. However, this software is provided as is and we cannot commit to ongoing support. If you use these tools, please cite the relevant GitHub repository, and any related publications.

iEye

example_run.png

MATLAB toolbox for interactive display and automatic analysis of eye-tracking data from memory-guided saccade experiments.

Interactive version (used in Mackey et al, 2016a; 2016b; Mackey & Curtis 2017): GitHub

Automated scoring (active development, currently in use): GitHub

Documentation available in most functions, as well as README on GitHub.

IEM

Tutorials (MATLAB) for implementing inverted encoding model (IEM) analyses: GitHub.

See a commentary by Tommy, Masih, and others in eNeuro: [ web | pdf ]

IEM.jpg

PopEye

Python based population receptive field modeling.

Coming soon…

AFNI scripts for preprocessing multiband fMRI data. Procedures will be described in detail in forthcoming preprints and publications.

Data processing involves: (1) surface reconstruction from T1 & T2 high-resolution anatomical images using Freesurfer, (2) standard spatial preprocessing steps (unwarping, motion correction, registration to anatomical images, surface smoothing, projection into volume space) using AFNI, (3) standard temporal normalization steps (linear detrending, conversion to percent signal change per voxel) using AFNI, and (4) additional custom processing, including computation of receptive field model parameters and multivariate analyses, using custom MATLAB and Python scripts, detailed below

Preprocessing scripts: available on GitHub (requires Freesurfer 6.0, AFNI, vistasoft)

Utility functions for extracting timeseries from nii files, etc (MATLAB): available on GitHub

Tools for GPU accelerating large-scale linear regression problems (e.g., ‘grid fits’): available on GitHub (requires CUDA-compatible NVidia GPU and Windows or Linux computer)

Custom version of vistalab’s vistasoft package for GPU-accelerated RF model fitting: available on GitHub (requires gridfitgpu)

fMRI preprocessing & analysis

Stimulus presentation

Scripts for stimulus presentation used across studies (typically, using Psychtoolbox)

Attended bar task used for voxel receptive field modeling and retinotopic mapping: GitHub

vRF.PNG