Unknown

Dataset Information

0

Mapping the orbitofrontal cortex using temporal fluctuations in cerebral blood flow.


ABSTRACT:

Introduction

The orbitofrontal cortex (OFC) is involved in diverse cognitive and behavioral processes including incentive valuation, decision-making, and reinforcement learning. Anatomic and cytoarchitectonic studies divide the OFC along both medial-lateral and rostral-caudal axes. OFC regions diverge in structure and function, assessed in vivo using white matter tractography and blood oxygenation level-dependent (BOLD) MRI, respectively. However, interpretation of T2 *-weighted BOLD is limited by susceptibility artifacts in the inferior frontal lobes, with the spatial pattern of these artifacts frequently assuming the geometry of OFC organization. Here, we utilize a novel perfusion-weighted arterial spin labeling (ASL) functional connectivity approach, which is minimally susceptibility-weighted, to test the hypothesis that OFC topology reflects correlated temporal hemodynamic activity.

Methods

In healthy participants (n = 20; age = 29.5 ± 7.3), 3D ASL scans were acquired (TR/TE = 3,900/13 ms; spatial resolution = 3.8 mm isotropic). To evaluate reproducibility, follow-up scanning on a separate day was performed on a participant subset (n = 8). ASL-based connectivity was modeled for gray matter OFC voxels, and k-means clustering (k = 2-8) applied to correlation statistics.

Results

These approaches revealed both medial-lateral and rostral-caudal OFC divisions, confirming our hypothesis. Longitudinal reproducibility testing revealed 84% voxel clustering agreement between sessions for the k = 2 solution.

Conclusion

To our knowledge, this constitutes the first in vivo cortical parcellation based on perfusion fluctuations. Our approach confirms functional OFC subdivisions predicted from anatomy using a less susceptibility-sensitive method than the conventional approach.

SUBMITTER: Petersen KJ 

PROVIDER: S-EPMC7994685 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC3023927 | biostudies-other
| S-EPMC9169582 | biostudies-literature
| S-EPMC8217767 | biostudies-literature
| S-EPMC3441053 | biostudies-literature
| S-EPMC17795 | biostudies-literature
| S-EPMC7465782 | biostudies-literature
| S-EPMC5051683 | biostudies-literature
| S-EPMC5464691 | biostudies-literature
| S-EPMC6039834 | biostudies-other
| S-EPMC3309501 | biostudies-other