Latency structure of BOLD signals within white matter in resting-state fMRI

Bi, Guo; Zhou, Fugen; Li, Muwei; Gore, John C.

doi:10.1101/2021.03.06.434206

Cited by 3 publications

(8 citation statements)

References 87 publications

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“…Similar to previous study on WM using completely independent dataset (Guo et al 2021a), results from this dataset also exhibited network-level lead/lag relationships, suggesting existence of dominant direction of signal propagations. We further applied linear mixed-effect analysis on the mean latencies of the off-diagonal blocks to investigate the main effect of stages on the variations of each mean latency.…”

Section: -B)supporting

confidence: 85%

“…K-means, a clustering technique, was applied on voxel-wise FC matrix within WM to obtain RSNs. A path of signal propagation, dominated by the direction from the inferior to the superior, was identified by performing latency analysis on WM RSNs, similar to previous study on a different dataset with large cohort of youngsters (Guo et al 2021a) at the resolution of 8 RSNs. Hence, in this study, the whole WM were parcellated into 8 clusters, as shown in Figure 8-A, by applying K-means on group-level FC matrix consisting of paired voxels of N2 group where the most subjects were included.…”

Section: Latency Among Rsns In Relation To Different Sleep Stagesmentioning

confidence: 86%

“…On the contrary, BOLD signals from white matter (WM) have long been regarded as artefacts, leading to the ignorance of the functional role of WM BOLD signals. However, a recent complemented study (Guo et al 2021a) on a large cohort of youngsters revealed the existence of highly reproducible latency structure of BOLD fMRI signals in WM. Variations of the latency structure were found to be associated with different sensory states (eye closed vs eye open).…”

Section: Introductionmentioning

confidence: 99%

“…With the observations above, we hypothesized that the propagations of BOLD fMRI signals in WM also behaved as a slow process involving in sustaining different levels of consciousness and cognitive processes by dynamically modulating directions of signal propagations among regions across wakefulness and nonrapid eye movement (NREM) sleep stages. To test this hypothesis, lagged cross-covariance (Mitra et al 2014;Raut et al 2020;Guo et al 2021a) and FC analysis were both performed on BOLD fMRI signals from a simultaneous EEG-fMRI dataset. Latency analyses were performed in three different aspects.…”

Section: Introductionmentioning

confidence: 99%

“…Latency analyses were performed in three different aspects. First, latency projections (Mitra et al 2014;Guo et al 2021a) showed significant reorganizations of latency topographies, which suggested reorganized apparent propagations of BOLD signals in WM regions across wakefulness and NREM sleep stages in an average sense. Second, using the regions found in the first step as seeds, we further calculated seed-based latency maps, reflecting latency value of each voxel with respect to the reference seed, and found that the reorganizations of latency topographies were driven by inconsistent shifts of latencies shared by different regions in WM across wakefulness and NREM sleep stages.…”

Section: Introductionmentioning

confidence: 99%

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Reorganizations of latency structure within white matter from wakefulness to sleep

Zhou

Zou

et al. 2021

Preprint

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Previous studies based on resting-state fMRI (rsfMRI) data have revealed the existence of highly repro-ducible latency structure, reflecting the propagation of BOLD fMRI signals, in white matter (WM). Here, based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data collected from 35 healthy subjects who were instructed to sleep, we explored the alterations of propagations in WM across wakefulness and nonrapid eye movement (NREM) sleep stages. Lagged cross-covariance was computed among voxel-wise time series, followed by parabolic interpolation to determine the actual latency value in-between. In WM, regions including cerebellar peduncle, internal capsule, posterior thalamic radiation, genu of corpus callosum, and corona radiata, were found to change their temporal roles drastically, as revealed by applying linear mixed-effect model on voxel-wise latency projections across wakefulness and NREM sleep stages. Using these regions as seeds, further seed-based latency analysis revealed that variations of latency projections across different stages were underlain by inconsistent temporal shifts between each seed and the remaining part of WM. Finally, latency analysis on resting-state networks (RSNs), obtained by applying k-means clustering technique on group-level functional connectivity matrix, identified a path of signal propagations similar to previous findings in EEG during wakefulness, which propagated mainly from the brainstem upward to internal capsule and further to corona radiata. This path showed inter-RSN temporal reorganizations depending on the paired stages between which the brain transitioned, e.g., it changed, between internal capsule and corona radiata, from mainly unidirectional to clearly reciprocal when the brain transitioned from wakefulness to N3 stage. These findings suggested the functional role of BOLD signals in white matter as a slow process, dynamically modulated across wakefulness and NREM sleep stages, and involving in maintaining differ-ent levels of consciousness and cognitive processes.

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Section: -B)supporting

confidence: 85%

Section: Latency Among Rsns In Relation To Different Sleep Stagesmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reorganizations of latency structure within white matter from wakefulness to sleep

Zhou

Zou

et al. 2021

Preprint

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Along-tract quantification of resting-state BOLD hemodynamic response functions in white matter

Schilling

Rheault

et al. 2022

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Detailed knowledge of the BOLD hemodynamic response function (HRF) is crucial for accurate analysis and interpretation of functional MRI data. Considerable efforts have been made to characterize the HRF in gray matter (GM) but much less is known about BOLD effects in white matter (WM). However, recent reports have demonstrated reliable detection and analyses of WM BOLD signals after stimulation and in a resting state. WM and GM differ in energy requirements and blood flow, so neurovascular couplings may well be different. We aimed to derive a comprehensive characterization of the HRF in WM across a population, including accurate measurements of its shape and its variation along and between WM pathways, using resting-state fMRI acquisitions. Our results show that the HRF is significantly different between WM and GM. Features of the HRF, such as a prominent initial dip, show strong relationships with features of the tissue microstructure derived from diffusion imaging, and these relationships differ between WM and GM, consistent with BOLD signal fluctuations reflecting different energy demands and differences in neurovascular coupling between tissues of different composition. We also show that the HRF varies significantly along WM pathways, and is different between different WM pathways. Thus, much like in GM, changes in flow and/or oxygenation are different for different parts of the WM. These features of the HRF in WM are especially relevant for interpretation of the biophysical basis of BOLD effects in WM.

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Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution

Kim

Taylor²,

Himmelbach³

et al. 2022

Front. Neurosci.

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Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.

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Latency structure of BOLD signals within white matter in resting-state fMRI

Cited by 3 publications

References 87 publications

Reorganizations of latency structure within white matter from wakefulness to sleep

Reorganizations of latency structure within white matter from wakefulness to sleep

Along-tract quantification of resting-state BOLD hemodynamic response functions in white matter

Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution

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