Mild inflammation causes a reduction in resting-state amplitude of low-frequency fluctuation in healthy adult males

Systemic inflammation has been associated with negative mood states and human sickness behaviour. Previous studies have shown an association between systemic inflammation and changes in task-related blood-oxygen-level-dependent activity and functional connectivity within large-scale networks. However, no study has examined the effect of inflammation on the magnitude of blood-oxygen-level-dependent low-frequency fluctuations at rest. We used a double-blind placebo-controlled crossover design to randomise 20 male subjects (aged 20–50 years) to receive either a Salmonella typhi vaccine or a placebo saline injection at two separate sessions. All participants underwent a resting-state functional magnetic resonance scan and a measure of inflammation (interleukin 6) and mood (Profile of Mood States) 3 h after injection. We compared the whole brain amplitude of low-frequency fluctuations between the vaccine and placebo conditions using a repeated measures design. Vaccine condition was associated with greater interleukin 6 levels (p < 0.001). Vaccine condition was also associated with lower amplitude of low-frequency fluctuations in the right and left frontal pole, superior frontal gyrus, paracingulate gyrus (Cluster 1) and the right mid and inferior frontal gyrus (Cluster 2) (p < 0.001, false discovery rate corrected). Lower amplitude of low-frequency fluctuations pertaining to first cluster correlated with greater total Profile of Mood States score (worse mood) (r = −0.38; p = 0.04). These results imply possible excitation/inhibition imbalance mechanisms during inflammation that may be a relevant target in psychiatric disease, especially mood disorders

In search of a marker of altered cerebrovascular function in hypertension: Analysis of the fractional amplitude of low-frequency fluctuations in UK Biobank resting state fMRI data

The selfish brain mechanism proposes that in some patients with impaired cerebral blood flow (CBF) or cerebrovascular function, hypertension may develop as a compensatory mechanism that aims to maintain CBF by increasing systemic blood pressure through an increase in cardiovascular sympathetic tone. The amplitude of low frequency fluctuations (ALFF) in the resting state blood oxygenation level dependent (BOLD) functional MRI signal has been previously posited as an index of cerebrovascular reactivity. We investigated whether regional fractional ALFF (fALFF) differs between 2054 hypertensives and 1724 normotensives using data from the UK Biobank dataset. Our primary hypothesis was that cerebrovascular function in the medulla and other regions involved in sympathetic regulation differs between hypertensives and normotensives, and that this is reflected by regional variations in fALFF. There is a significant regional variation in fALFF (F(14) =1126.17, p < 2 × 10−16, partial η2 = 0.22), but this regional variation does not differ between hypertensives and normotensives (F(14) = 0.23, p = 0.99, partial η2 = 8 × 10−5). Prospective longitudinal studies of cerebral haemodynamics in hypertensives and normotensives are required to further investigate the selfish brain mechanism

Task-Related modulations of BOLD low-frequency fluctuations within the default mode Network

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task

A reversal coarse-grained analysis with application to an altered functional circuit in depression

Introduction: When studying brain function using functional magnetic resonance imaging (fMRI) data containing tens of thousands of voxels, a coarse-grained approach – dividing the whole brain into regions of interest – is applied frequently to investigate the organization of the functional network on a relatively coarse scale. However, a coarse-grained scheme may average out the fine details over small spatial scales, thus rendering it difficult to identify the exact locations of functional abnormalities. Methods: A novel and general approach to reverse the coarse-grained approach by locating the exact sources of the functional abnormalities is proposed. Results: Thirty-nine patients with major depressive disorder (MDD) and 37 matched healthy controls are studied. A circuit comprising the left superior frontal gyrus (SFGdor), right insula (INS), and right putamen (PUT) exhibit the greatest changes between the patients with MDD and controls. A reversal coarse-grained analysis is applied to this circuit to determine the exact location of functional abnormalities. Conclusions: The voxel-wise time series extracted from the reversal coarse-grained analysis (source) had several advantages over the original coarse-grained approach: (1) presence of a larger and detectable amplitude of fluctuations, which indicates that neuronal activities in the source are more synchronized; (2) identification of more significant differences between patients and controls in terms of the functional connectivity associated with the sources; and (3) marked improvement in performing discrimination tasks. A software package for pattern classification between controls and patients is available in Supporting Information

Impact of Visual Repetition Rate on Intrinsic Properties of Low Frequency Fluctuations in the Visual Network

BACKGROUND: Visual processing network is one of the functional networks which have been reliably identified to consistently exist in human resting brains. In our work, we focused on this network and investigated the intrinsic properties of low frequency (0.01-0.08 Hz) fluctuations (LFFs) during changes of visual stimuli. There were two main questions to be discussed in this study: intrinsic properties of LFFs regarding (1) interactions between visual stimuli and resting-state; (2) impact of repetition rate of visual stimuli. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed scanning sessions that contained rest and visual stimuli in various repetition rates with a novel method. The method included three numerical approaches involving ICA (Independent Component Analyses), fALFF (fractional Amplitude of Low Frequency Fluctuation), and Coherence, to respectively investigate the modulations of visual network pattern, low frequency fluctuation power, and interregional functional connectivity during changes of visual stimuli. We discovered when resting-state was replaced by visual stimuli, more areas were involved in visual processing, and both stronger low frequency fluctuations and higher interregional functional connectivity occurred in visual network. With changes of visual repetition rate, the number of areas which were involved in visual processing, low frequency fluctuation power, and interregional functional connectivity in this network were also modulated. CONCLUSIONS/SIGNIFICANCE: To combine the results of prior literatures and our discoveries, intrinsic properties of LFFs in visual network are altered not only by modulations of endogenous factors (eye-open or eye-closed condition; alcohol administration) and disordered behaviors (early blind), but also exogenous sensory stimuli (visual stimuli with various repetition rates). It demonstrates that the intrinsic properties of LFFs are valuable to represent physiological states of human brains

Diurnal Variations in Neural Activity of Healthy Human Brain Decoded with Resting-State Blood Oxygen Level Dependent fMRI

It remains an ongoing investigation about how the neural activity alters with the diurnal rhythms in human brain. Resting-state functional magnetic resonance imaging (RS-fMRI) reflects spontaneous activities and/or the endogenous neurophysiological process of the human brain. In the present study, we applied the ReHo (regional homogeneity) and ALFF (amplitude of low frequency fluctuation) based on RS-fMRI to explore the regional differences in the spontaneous cerebral activities throughout the entire brain between the morning and evening sessions within a 24-h time cycle. Wide spread brain areas were found to exhibit diurnal variations, which may be attributed to the internal molecular systems regulated by clock genes, and the environmental factors including light-dark cycle, daily activities and homeostatic sleep drive. Notably, the diurnal variation of default mode network (DMN) suggests that there is an adaptation or compensation response within the subregions of DMN, implying a balance or a decoupling of regulation between these regions.National Natural Science Foundation of China [81371359]; National Basic Research Program of China [2015CB755500]; Basic Research Program of Shenzhen [JCYJ20160429191938883]SCI(E)[email protected]