henhaobio
Sign in

bioRxivNeurosciencePreprint

The many layers of BOLD. On the contribution of different vascular compartments to laminar fMRI.

Wouter SchellekensiD, Alex A. BhogaliD, Emiel C. A. RoefsiD, Mario Gilberto Báez‐YáñeziD, Jeroen C.W. SieroiD, Natalia PetridouiD

PDFDOI

Abstract

Ultra-high field functional Magnetic Resonance Imaging (fMRI) offers the spatial resolution to measure neural activity at the scale of cortical layers. Most fMRI studies make use of the Blood-Oxygen-Level Dependent (BOLD) signal, arising from a complex interaction of changes in cerebral blood flow (CBF) and volume (CBV), and venous oxygenation. However, along with cyto- and myeloarchitectural changes across cortical depth, laminar fMRI is confronted with additional confounds related to vascularization differences that exist across cortical depth. In the current study, we quantify how the non-uniform distribution of macro- and micro-vascular compartments, as measured with Gradient-Echo (GE) and Spin-Echo (SE) scan sequences, respectively, affect laminar BOLD fMRI responses following evoked hypercapnic and hyperoxic breathing conditions. We find that both macro- and micro-vascular compartments are capable of comparable theoretical maximum signal intensities, as represented by the M-scaling parameter. However, the capacity for vessel dilation, as reflected by the cerebrovascular reactivity (CVR), is approximately three times larger for the macro-compared to the micro-vasculature at superficial layers. Finally, there is roughly a 35% difference in CBV estimates between the macro- and micro-vascular compartments, although this relative difference is approximately uniform across cortical depth.

Citations
1

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISAkbari '22Dresbach '24Huber '21Beckett '20Báez‐Yáñez '24Shao '21
77% semantic matchNeuroscience
Atena Akbari, Saskia Bollmann, Tonima Ali+1 more·Human Brain Mapping·Oct 3, 2022· 22 citations