Many methods for the forward modeling of the blood-oxygenation level-dependent (BOLD) effect have been created and analyzed to elucidate the mechanisms of BOLD functional MRI (fMRI) techniques and to expand on the potential of the transverse relaxation time (T 2 *) in quantitative MRI. Simulations of this nature can be difficult to implement without prior experience, and differences made by methodological choices can be unclear, which provides a significant barrier of entry into the field. In this paper, we present BOLDsωimsuite, a toolbox for forward modeling of the BOLD effect, which collects many of the principal methods used in the literature into a single coherent package. Implemented as a Python package, simulations are made using scripts by combining various simulation components, thereby providing flexibility in methodological choices. The goal of this toolbox is to provide an open-source, reproducible simulation software suite that is adaptable for different MRI applications, and to which additional features can be added by the user with relative ease. This paper first provides an overview of the methods available in the package and how these methods can be constructed from the toolbox’s modular code components. Then, a brief theoretical explanation of each simulation component is given, supported by the relevant contributors. Next, sample simulations and analyzes that can be created using the package are presented to display its features. Finally, recommendations regarding computational requirements are included to help users choose the best simulation methods to fit their needs. This package has many use cases and significantly reduces methodological barriers to forward modeling. It can also be a good learning tool for MR physics as well as a powerful tool to promote reproducible science.

Macrovascular biases have been a long-standing challenge for functional magnetic resonance imaging (fMRI), limiting its ability to detect spatially specific neural activity. Recent experimental studies, including our own, found substantial resting-state macrovascular blood-oxygenation level-dependent (BOLD) fMRI contributions from large veins and arteries, extending into the perivascular tissue at 3 T and 7 T. The objective of this study is to demonstrate the feasibility of predicting, using a biophysical model, the experimental resting-state BOLD fluctuation amplitude (RSFA) and associated functional connectivity (FC) values at 3 Tesla. We investigated the feasibility of both 2D and 3D infinite-cylinder Models as well as macrovascular anatomical networks (macro-VANs) derived from angiograms. Our results demonstrate that (1) with the availability of macro-VANs, it is feasible to model macrovascular BOLD FC using both the macro-VAN-based model and 3D infinite-cylinder Models, though the former performed better; (2) biophysical modelling can accurately predict the BOLD pair-wise correlation near to large veins (with R 2 ranging from 0.53 to 0.93 across different subjects), but not near to large arteries; (3) compared with FC, biophysical modelling provided less accurate predictions for RSFA; (4) modelling of perivascular BOLD connectivity was feasible at close distances from veins (with R 2 ranging from 0.08 to 0.57), but not arteries, with performance deteriorating with increasing distance. While our current study demonstrates the feasibility of simulating macrovascular BOLD in the resting state, our methodology may also apply to understanding task-based BOLD. Furthermore, these results suggest the possibility of correcting for macrovascular bias in resting-state fMRI and other types of fMRI using biophysical modelling based on vascular anatomy.

While tract-wise differences in volume and microstructure are common targets of investigation in age-related changes in the white matter (WM), there has been relatively little exploration into other attributes of tract morphometry or its relation to microstructure in vivo, and limited understanding on how they jointly inform the understanding of the WM aging trajectory. This study examines 10 WM tracts for tract-wise differences in morphometry (i.e., volume, length, and volume-to-length ratio) and microstructural integrity (i.e., fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity) using diffusion MRI data from the Human Connectome Project in Aging (HCP-A) with the goal of laying the foundation for a more comprehensive model of age-related WM microstructure-morphometry trajectories with a special focus on age-shifted correlations and sex differences. Results indicated that degeneration in microstructure was detectable at younger ages than changes in morphometry, with widely heterogeneous patterns of interrelation and morphometry-microstructural associations in aging both across tracts and between sexes. Multi-parametric signatures of decline suggest differing stages or mechanisms of degeneration across tracts, with female subjects exhibiting a higher proportion of tracts in later stages of decline than males. This work highlights the value of integrating microstructural and morphometric measures of WM health, and encourages the integration of yet more modalities in improving our mechanistic understanding of WM aging.

In resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity (FC) mapping, temporal correlation is widely assumed to reflect synchronized neural-related activity. Although a large number of studies have demonstrated the potential vascular effects on FC, little research has been conducted on FC resulting from macrovascular signal fluctuations. Previously, our study found ( Tong, Yao, et al., 2019 ) a robust anti-correlation between the fMRI signals in the internal carotid artery and the internal jugular vein (and the sagittal sinus). The present study extends the previous study to include all detectable major veins and arteries in the brain in a systematic analysis of the macrovascular contribution to the functional connectivity of the whole-gray matter (GM). This study demonstrates that: (1) The macrovasculature consistently exhibited strong correlational connectivity among itself, with the sign of the correlations varying between arterial and venous connectivity; (2) GM connectivity was found to have a strong macrovascular contribution, stronger from veins than arteries; (3) FC originating from the macrovasculature displayed disproportionately high spatial variability compared to that associated with all GM voxels; and (4) macrovascular contributions to connectivity were still evident well beyond the confines of the macrovascular space. These findings highlight the extensive contribution to rs-fMRI blood-oxygenation level-dependent (BOLD) and FC predominantly by large veins, but also by large arteries. These findings pave the way for future studies aimed at more comprehensively modeling and thereby removing these macrovascular contributions.

Synchronized 40-Hz gamma oscillations in specific sensory and higher-order thalamocortical networks provide a neural mechanism for feature binding. Aging-related changes in gamma oscillations may cause deficits in auditory feature binding, contributing to impaired speech-in-noise perception. Gamma synchrony is controlled through inhibitory mechanisms mediated by the neurotransmitter γ-aminobutyric acid (GABA), which has been shown to decline in aging. This study investigated aging-related changes in gamma oscillations and how they relate to auditory function and cortical GABA levels. Magnetoencephalograms of 40-Hz auditory steady-state responses (ASSRs) were recorded in young and older adults by presenting amplitude-modulated tones in quiet and mixed with concurrent multi-talker babble noise. Responses in the quiet condition had longer latencies and more prominent amplitudes, indicating the 40-Hz ASSRs in noise were dominated by a sensory component and in quiet by a component involved in higher-order processing. The ASSR amplitudes increased in older adults under both stimulus conditions. However, larger ASSR amplitudes were associated with more severe hearing and speech-in-noise loss only in the noise condition. This suggests the aging-related increase in synchrony of sensory gamma oscillations has a detrimental effect on auditory processing. It may cause increased interference between competing sounds in the central auditory system, making it difficult for the aging auditory system to separate speech features from noise and bind them into a distinct perceptual object. Also in older adults, larger amplitudes of the 40-Hz ASSRs in the quiet condition were associated with higher left auditory cortex GABA concentrations measured with magnetic resonance spectroscopy, supporting GABA’s role in internally generated gamma synchrony in aging.