Data from: Multiple insular-prefrontal pathways underlie perception to execution during response inhibition in humans
Data files
Oct 04, 2024 version files 4.60 MB
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diffusion_mri.zip
1.74 MB
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fmri_task.zip
1.64 MB
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parcellation.zip
1.22 MB
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README.md
4.55 KB
Dec 05, 2024 version files 4.61 MB
-
diffusion_mri.zip
1.74 MB
-
fmri_task.zip
1.64 MB
-
parcellation.zip
1.22 MB
-
README.md
4.82 KB
Abstract
Inhibiting prepotent responses in the face of external stop signals requires complex information processing, from perceptual to control processing. However, the cerebral circuits underlying these processes remain elusive. In this study, we used neuroimaging and brain stimulation to investigate the interplay between human brain regions during response inhibition at the whole-brain level. Magnetic resonance imaging suggested a sequential four-step processing pathway: initiating from the primary visual cortex (V1), progressing to the dorsal anterior insula (daINS), then involving two essential regions in the inferior frontal cortex (IFC), namely the ventral posterior IFC (vpIFC) and anterior IFC (aIFC), and reaching the basal ganglia (BG)/primary motor cortex (M1). A combination of ultrasound stimulation and time-resolved magnetic stimulation elucidated the causal influence of daINS on vpIFC and the unidirectional dependence of aIFC on vpIFC. These results unveil asymmetric pathways in the insular-prefrontal cortex and outline the macroscopic cerebral circuits for response inhibition: V1→daINS→vpIFC/aIFC→BG/M1.
https://doi.org/10.5061/dryad.c866t1ggj
Description of the data and file structure
This repository contains the data for the manuscript entitled:
| “Multiple insular-prefrontal pathways underlie perception to execution during response inhibition in humans” Nature Communications 15: 10380 (2024) | doi: 10.1038/s41467-024-54564-9 |
Authors: Osada T, Nakajima K, Shirokoshi T, Ogawa A, Oka S, Kamagata K, Aoki S, Oshima Y, Tanaka S, and Konishi S.
1. parcellation.zip
The file “parcellation.zip” contains data on cerebrocortical parcellation based on Osada et al. (2021). The files can be viewed using wb_view in Connectome Workbench (https://www.humanconnectome.org/software/connectome-workbench). Parcels (“parcel.dlabel.nii”) are displayed on the template surfaces (“Conte69.L.inflated.32k_fs_LR.surf.gii” and “Conte69.R.inflated.32k_fs_LR.surf.gii”).
- parcel.dlabel.nii: CIFTI file for the parcellation of the cerebral cortex. This file contains parcel designations and a color key for each grayordinate. Distinct colors indicate distinct parcels (i.e., functional units). The whole cerebral cortex was parcellated into 330 parcels.
- Conte69.L.inflated.32k_fs_LR.surf.gii and Conte69.R.inflated.32k_fs_LR.surf.gii: GIFTI files for surface geometry of the left and right hemispheres, respectively. These files specify 3D vertex coordinates and their topological relationships (triangular tessellation). These files are used for template surfaces.
2. fmri_task.zip
The file “fmri_task.zip” contains behavioral and activation data from the stop-signal task (a task for response inhibition) conducted during fMRI scanning. The activation data includes a vertexwise t-map (contrast: Stop success minus Go success) and a t-map based on ROIs in the cerebrocortical parcels. The t-maps can be viewed using wb_view and displayed on the template surfaces.
- performance_fmri.xlsx: Behavioral data for the stop-signal task for each subject during fMRI scanning. This includes reaction time for Go success trials, stop-signal delay (SSD), stop-signal reaction time (SSRT), correct response rates for Go and Stop trials, reaction time for Stop failure trials, and reaction times for Stop failure trials with SSDs shorter/longer than the median SSD.
- tmap_Stop_success_minus_Go_success.dtseries.nii: CIFTI file for the vertexwise task activation t-map (contrast: Stop success minus Go success).
- tmap_Stop_success_minus_Go_success.ptseries.nii: CIFTI file for task activation t-map on the basis of regions of interest (ROIs) of the cerebrocortical parcels.
- Conte69.L.inflated.32k_fs_LR.surf.gii and Conte69.R.inflated.32k_fs_LR.surf.gii: GIFTI files for surface geometry.
3. diffusion_mri.zip
The file “diffusion_mri.zip” contains diffusion MRI data for the seeds of the right vpIFC (“diffusion_seed_vpIFC.dtseries.nii”), the right daINS (“diffusion_seed_daINS.dtseries.nii”), the right STN (“diffusion_seed_STN.dtseries.nii”), the right anterior putamen (“diffusion_seed_AnteriorPutamen.dtseries.nii”), and the right caudate nucleus (“diffusion_seed_CaudateNucleus.dtseries.nii”). The structural connectivity data via diffusion MRI is shown based on ROIs in the cerebrocortical parcels. The maps can be viewed using wb_view and diplayed on the template surfaces.
- diffusion_seed_vpIFC.dtseries.nii: CIFTI file for structural connectivity data in the cerebral cortex for the seed of the right ventral posterior inferior frontal cortex (vpIFC).
- diffusion_seed_daINS.dtseries.nii: CIFTI file for structural connectivity data in the cerebral cortex for the seed of the right dorsal anterior insula (daINS).
- diffusion_seed_STN.dtseries.nii: CIFTI file for structural connectivity data in the cerebral cortex for the seed of the right subthalamic nucleus (STN).
- diffusion_seed_AnteriorPutamen.dtseries.nii: CIFTI file for structural connectivity data in the cerebral cortex for the seed of the right anterior putamen.
- diffusion_seed_CaudateNucleus.dtseries.nii: CIFTI file for structural connectivity data in the cerebral cortex for the seed of the right caudate nucleus.
- Conte69.L.inflated.32k_fs_LR.surf.gii and Conte69.R.inflated.32k_fs_LR.surf.gii: GIFTI files for surface geometry.
The data analyses were performed using freely available codes of HCP pipelines (https://github.com/Washington-University/HCPpipelines), FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki), and SPM (http://www.fil.ion.ucl.ac.uk/spm/).