The Relationship Between M in “Calibrated fMRI” and the Physiologic Modulators of fMRI

The “calibrated fMRI” technique requires a hypercapnia calibration experiment in order to estimate the factor “M”. It is desirable to be able to obtain the M value without the need of a gas challenge calibration. According to the analytical expression of M, it is a function of several baseline physiologic parameters, such as baseline venous oxygenation and CBF, both of which have recently been shown to be significant modulators of fMRI signal. Here we studied the relationship among hypercapnia-calibrated M, baseline venous oxygenation and CBF, and assessed the possibility of estimating M from the baseline physiologic parameters. It was found that baseline venous oxygenation and CBF are highly correlated (R2=0.77, P<0.0001) across subjects. However, the hypercapnia-calibrated M was not correlated with baseline venous oxygenation or CBF. The hypercapnia-calibrated M was not correlated with an estimation of M based on analytical expression either. The lack of correlation may be explained by the counteracting effect of venous oxygenation and CBF on the M factor, such that the actual M value of an individual may be mostly dependent on other parameters such as hematocrit. Potential biases in hypercapnia-based M estimation were also discussed in the context of possible reduction of CMRO2 during hypercapnia

Prediction of Task-Related BOLD fMRI with Amplitude Signatures of Resting-State fMRI

Blood oxygen contrast-functional magnetic resonance imaging (fMRI) signals are a convolution of neural and vascular components. Several studies indicate that task-related (T-fMRI) or resting-state (R-fMRI) responses linearly relate to hypercapnic task responses. Based on the linearity of R-fMRI and T-fMRI with hypercapnia demonstrated by different groups using different study designs, we hypothesized that R-fMRI and T-fMRI signals are governed by a common physiological mechanism and that resting-state fluctuation of amplitude (RSFA) should be linearly related to T-fMRI responses. We tested this prediction in a group of healthy younger humans where R-fMRI, T-fMRI, and hypercapnic (breath hold, BH) task measures were obtained form the same scan session during resting state and during performance of motor and BH tasks. Within individual subjects, significant linear correlations were observed between motor and BH task responses across voxels. When averaged over the whole brain, the subject-wise correlation between the motor and BH tasks showed a similar linear relationship within the group. Likewise, a significant linear correlation was observed between motor-task activity and RSFA across voxels and subjects. The linear rest–task (R–T) relationship between motor activity and RSFA suggested that R-fMRI and T-fMRI responses are governed by similar physiological mechanisms. A practical use of the R–T relationship is its potential to estimate T-fMRI responses in special populations unable to perform tasks during fMRI scanning. Using the R–T relationship determined from the first group of 12 healthy subjects, we predicted the T-fMRI responses in a second group of 7 healthy subjects. RSFA in both the lower and higher frequency ranges robustly predicted the magnitude of T-fMRI responses at the subject and voxel levels. We propose that T-fMRI responses are reliably predictable to the voxel level in situations where only R-fMRI measures are possible, and may be useful for assessing neural activity in task non-compliant clinical populations

BOLD ФМРТ КАРТИРОВАНИЕ ФУНКЦИОНАЛЬНО ЗНАЧИМЫХ ЗОН КОРЫ У ПАЦИЕНТОВ С ОПУХОЛЯМИ ГОЛОВНОГО МОЗГА С ПРИМЕНЕНИЕМ ДОПОЛНИТЕЛЬНЫХ ФИЗИОЛОГИЧЕСКИХ ПАРАМЕТРОВ

Introduction. Preoperative fMRI often shows a reduced BOLD response in the areas located perifocal to brain tumors caused by pathological vasoreactivity as a result of neurovascular uncoupling.The aim of this study was an accurate identification of the eloquent cortical areas near brain tumors by measuring vasoreactivity using the breath holding test.Material and methods. 23 patients with brain tumors located near eloquent cortical areas underwent fMRI mapping of the language and / or motor cortical areas depending on the location of the tumor. Breath hold test was  also included, the design of which coincided with motor and language block paradigms.Results. A statistical dependency between motor, speech tasks and breath-hold BOLD-response was included into the BOLD analysis using coherence. fMRI activation maps generated by this method showed activation in the eloquent areas adjacent to brain tumors which were not detected by the standard analysis. This study shows that neurovascular uncoupling affects the accuracy of BOLD fMRI in brain tumors.Conclusion. The results of fMRI mapping can be partially improved by the incorporating vasoreactivity measurements into a standard analysis.Введение. Предоперационные BOLD фМРТ часто показывают понижение BOLD-ответа, вызванное патологической вазореактивностью вследствие нейроваскулярного разобщения в перифокальных опухолям зонах головного мозга.Цель исследования: разработать алгоритм получения карт BOLD-активации, учитывающий измененную гемодинамику у пациентов с внутримозговыми и внемозговыми опухолями, при сопоставлении карт BOLD-ответа на моторные и речевые задания с/без включения задачи задержки дыхания.Материалы и методы. В исследование включено 23 пациента с опухолями головного мозга, расположенными вблизи функционально значимых зон коры. Всем пациентам осуществлялось фМРТ-картирование речевых и/или двигательных зон коры головного мозга в зависимости от локализации опухоли, а также проводился тест с задержкой дыхания, дизайн которого совпадал с моторными и речевыми блоковыми парадигмами.Результаты. Полученная зависимость между моторными или речевыми заданиями и ответом на задержку дыхания была включена в постобработку данных фМРТ с использованием когерентного анализа. Карты, построенные этим методом, показали клинически значимые области активации, прилегающие к опухолям головного мозга, не выявлявшиеся с помощью стандартного метода анализа.Заключение. Результаты фМРТ-картирования можно частично улучшить включением данных измерения вазореактивности в стандартный анализ

The effects of age on resting‐state BOLD signal variability is explained by cardiovascular and cerebrovascular factors

Funder: Amsterdam NeuroscienceAbstract: Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well‐being. Many studies of neurocognitive aging have investigated brain function with the blood‐oxygen level‐dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath‐holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age‐related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age‐related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population‐based, lifespan Cam‐CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel‐level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging

The effects of age on resting‐state BOLD signal variability is explained by cardiovascular and cerebrovascular factors

Funder: Amsterdam NeuroscienceAbstract: Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well‐being. Many studies of neurocognitive aging have investigated brain function with the blood‐oxygen level‐dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath‐holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age‐related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age‐related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population‐based, lifespan Cam‐CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel‐level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging

Grading of Frequency Spectral Centroid Across Resting-State Networks

Ongoing, slowly fluctuating brain activity is organized in resting-state networks (RSNs) of spatially coherent fluctuations. Beyond spatial coherence, RSN activity is governed in a frequency-specific manner. The more detailed architecture of frequency spectra across RSNs is, however, poorly understood. Here we propose a novel measure–the Spectral Centroid (SC)–which represents the center of gravity of the full power spectrum of RSN signal fluctuations. We examine whether spectral underpinnings of network fluctuations are distinct across RSNs. We hypothesize that spectral content differs across networks in a consistent way, thus, the aggregate representation–SC–systematically differs across RSNs. We therefore test for a significant grading (i.e., ordering) of SC across RSNs in healthy subjects. Moreover, we hypothesize that such grading is biologically significant by demonstrating its RSN-specific change through brain disease, namely major depressive disorder. Our results yield a highly organized grading of SC across RSNs in 820 healthy subjects. This ordering was largely replicated in an independent dataset of 25 healthy subjects, pointing toward the validity and consistency of found SC grading across RSNs. Furthermore, we demonstrated the biological relevance of SC grading, as the SC of the salience network–a RSN well known to be implicated in depression–was specifically increased in patients compared to healthy controls. In summary, results provide evidence for a distinct grading of spectra across RSNs, which is sensitive to major depression

Separating vascular and neuronal effects of age on fMRI BOLD signals.

Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.This work is supported by the British Academy (PF160048), the Guarantors of Brain (G101149), the Wellcome Trust (103838), the Medical Research Council (SUAG/051 G101400; and SUAG/046 G101400), European Union’s Horizon 2020 (732592) and the Cambridge NIHR Biomedical Research Centre

Functional networks and network perturbations in rodents

Synchronous low-frequency oscillation in the resting human brain has been found to form networks of functionally associated areas and hence has been widely used to map the functional connectivity of the brain using techniques such as resting-state functional MRI (rsfMRI). Interestingly, similar resting-state networks can also be detected in the anesthetized rodent brain, including the default mode-like network. This opens up opportunities for understanding the neurophysiological basis of the rsfMRI signal, the behavioral relevance of the network characteristics, connectomic deficits in diseases and treatment effects on brain connectivity using rodents, particularly transgenic mouse models. In this review, we will provide an overview on the resting-state networks in the rat and mouse brains, the effects of pharmacological agents, brain stimulation, structural connectivity, genetics on these networks, neuroplasticity after behavioral training and applications in models of neurological disease and psychiatric disorders. The influence of anesthesia, strain difference, and physiological variation on the rsfMRI-based connectivity measure will be discussed

Functional connectivity of the ageing brain

This thesis investigated the impact of advancing age on modifying the functional connectivity (FC) of both typical cortical resting-state networks and subcortical structures in the human brain. Furthermore, it explored how any differences in FC may be associated with changes in sleep quality, also thought to be affected by age, and how such interactions may contribute to typical cognitive disruption associated with older age. The results suggest that older age is associated with the heterogeneous, spatially specific re-organisation of resting-state networks (RSNs), as well as indicating gender-specific spatial re-organisation. Investigation of thalamic FC revealed that older adults exhibited greater thalamo-sensory and thalamo-hippocampal FC, which was related to cognitive performance on RT and memory tasks, respectively. Investigation into participant’s sleep patterns provided evidence that sleep quality was more variable amongst the older participants. Furthermore, older adults that slept the longest each night were found to exhibit patterns of thalamic FC which were associated with better cognitive performance, than seen in older shorter sleepers. These results provide preliminary evidence that sleep may be associated with more ‘preferable’ patterns of FC in older adults which may be beneficial for cognitive function