data/software
Data
EPIC (Extended Precision measurement of Inhibitory Control)
The EPIC (Extended Precision measurement of Inhibitory Control) dataset includes over 5,000 trials per participant across four tasks—Flanker, Prime-Probe, Stroop, and Go/No-Go—collected from nine participants. Designed to provide high-precision individual-level estimates of inhibitory control, this dataset aims to enhance the accuracy of inhibitory control assessments, explore intra- and inter-individual variations, and support the development of alternative modeling approaches.
Dataset is described in:
Lee, H.J., Smith, D.M., Hauenstein, C.E., Dworetsky, A., Kraus, B.T., Dorn, M., Nee, D.E, Gratton, C. Precise individual measures of inhibitory control. Nat Hum Behav (2025). https://doi.org/10.1038/s41562-025-02198-2
Midnight Scan Club
OpenfMRI dataset from the Dosenbach lab and Midnight Scan Club group at WUSTL.
Dataset is described in:
Gordon, E. M., Laumann, T. O., Gilmore, A. W., Newbold, D. J., Greene, D. J., Berg, J. J., ... (2017). Precision functional mapping of individual human brains. Neuron, 95(4), 791-807.
Midnight Scan Club: ROI-based information
Timeseries, correlation matrices, and distance matrices for data from the Midnight Scan Club.
Data is provided from rest and four tasks (motor, semantic, coherence, and memory) and for both group parcellations (Gordon 333 regions) and individual parcellations (described in Gordon et al., 2017).
PAN: Precision targeting of Association Networks
This dataset contains the Precision targeting of Association Networks (PAN) data. Data were collected in 10 individuals over 6-9 separate two-hour scanning sessions. In all sessions, resting-state and task data was collected, totaling approximately 2 hours of resting-state and 6 hours of task-state data per individual. In the first two sessions, T1 data was also collected. Dataset is described in: - Ladwig, Z., Kermani, K. Z., Dworetsky, A., Labora, N., Hernandez, J. J., Dorn, M., Smith, D. M., Nee, D. E., Petersen, S. E., Braga, R. M., Gratton, C. Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex. (in press) https://www.biorxiv.org/content/10.1101/2025.07.24.666468v2. Processing and analysis code is available here - https://www.github.com/GrattonLab/Ladwig-LPFC.
Probabilistic mapping ROI set and point-and-click tools
Files associated with Dworetsky et al., 2021 "Probabilistic mapping of human functional brain networks identifies regions of high group consensus" in Neuroimaging.
Software
Codebase: Dworetsky et al., 2024, Nature Neuroscience
MATLAB scripts used to conduct border/ectopic variant analyses; allows users to classify network variants as either border shifts or ectopic intrusions, and compare their spatial/network distributions, prediction of behavioral phenotypes, activation during tasks, subgroup properties, and genetic similarity.
Codebase: Gratton et al., 2018, Neuron
Code to conduct analyses on Midnight Scan Club data from:
Gratton C, Laumann TO, Nielsen AN, Greene DJ, Gordon EM, Gilmore AW, Nelson SM, Coalson RS, Snyder AZ, Schlaggar BL, Dosenbach NUF, Petersen SE. Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation. Neuron. April 18, 2018.
Codebase: Gratton et al., 2020, Neuroimage
The included MATLAB scripts were used in the study: Gratton et al. (2020) Removal of high frequency contamination from motion estimates in single-band fMRI saves data without biasing functional connectivty. Neuroimage. These scripts will allow users to make measurements of the frequency content of motion metrics, relate them to demographic characteristics, and use different motion metrics to detect motion-functional connectivity links following Ciric et al., 2017.
Codebase: Kraus et al., 2021, Neuroimage
The included files and scripts were used in: Kraus et al., 2021. Network variants are similar between task and rest states. Neuroimage. This code will allow users to match sampling of rest data between tasks (if desired), create network variants, find the spatial overlap of variants, assign them to network templates, and other subsidiary analyses included in the paper.
Codebase: Lee et al., 2025, Nature Human Behaviour
All analyses from Lee, H. J., Smith, D. M., Hauenstein, C., Dworetsky, A., Kraus, B. T., Dorn, M., Nee, D. E., & Gratton, C. (2025). Precise individual measures of inhibitory control. Nature Human Behaviour can be replicated with the provided scripts. This codebase includes MATLAB scripts, with Psychtoolbox required for experimental tasks and WinBUGS, R2OpenBUGS, and lme4 required for the Bayesian hierarchical approach.
Codebase: Seitzman et al., 2019, PNAS
MATLAB scripts used in the study by Seitzman et al., (2019), "Trait-like variants in human functional brain networks". PNAS. These scripts will allow users to create network variants, assign them to network templates, and find subgroups/sub-types of individuals on the basis of network variants.
Midnight Scan Club: Tutorial - Matlab
Tutorial for viewing and processing functional connectivity data, based on the Midnight scan club dataset.
Originally presented at Dartmouth MIND summer school, 2017.
Midnight Scan Club: Tutorial - Python
Tutorial for viewing and processing functional connectivity data, based on the Midnight scan club dataset.
Originally presented at Neurohackademy summer school, 2019.