Age-related change in task-evoked amygdala-prefrontal circuitry: a multiverse approach with an accelerated longitudinal cohort aged 4-22 years
Analysis scripts (R, python, and shell) and documentation for this project, and README files within each sub-directory give more detailed information on how each step was carried out (and where to find the code).
- See paper at Bloom et al., 2022 / Preprint Manuscript on BioRxiv
- Multiverse analysis tutorial + walkthrough
- Interactive multiverse explorer app
- Materials & preregistration on Open Science Framework
- Developmental Affective Neurocience Lab (Tottenham Lab)
| Sub-directory | Contents |
|---|---|
| 0_setup_and_behavioral_analyses | Compiling behavioral files collected in the scanner, making onset timing files, task behavior analyses |
| 1_head_motion | In-scanner head motion assessment |
| 2_prereg_level1 | Pre-registered FSL preprocessing pipeline |
| 3_pull_prereg_roi | Get amygdala reactivity estimates (native & MNI space) for preregistered pipeline |
| 4_gppi | Run generalized psychophysiological interaction models for task-based amygdala functional connectivity |
| 5_beta_series_correlation | Run beta series correlations for task-based amygdala functional connectivity |
| 6_multiverse_cpac_preproc | Run forked C-PAC preprocessing and FSL/AFNI GLM models to create proc multiverse |
| 7_group_level_analyses | Run all group-level analyses involving the fMRI data to make specification curves |
| 8_interactive_multiverse_app | Code for shiny application |
| 9_specification_curve_walkthrough | Markdown files for specification curve tutorial & simulated amygdala reactivity dataset |
Analysis code written by Paul A. Bloom
Email paul.bloom@columbia.edu
Computing was carried out using MacOs Mojave via a MacBook Pro 2019 laptop, a lab server (Ubuntu 18.04.4 LTS (GNU/Linux 4.15.0-154-generic x86_64)), and Columbia University's Habanero Research Computing Cluster.
- Python 3.4
- R 3.6.2
- FSL v6.00
- AFNI 20.1.16
- C-PAC 1.4.1