Pathophysiology of multiple sclerosis damage and repair: Linking cerebral hypoperfusion to the development of irreversible tissue loss in multiple sclerosis using magnetic resonance imaging.

BACKGROUND AND PURPOSE: Reduced cerebral perfusion has been observed in multiple sclerosis (MS) and may contribute to tissue loss both acutely and chronically. Here, we test the hypothesis that hypoperfusion occurs in MS and relates to the presence of irreversible tissue damage. METHODS: In 91 patients with relapsing MS and 26 healthy controls (HC), gray matter (GM) cerebral blood flow (CBF) was assessed using pulsed arterial spin labeling. GM volume, T1 hypointense and T2 hyperintense lesion volumes (T1LV and T2LV, respectively), and the proportion of T2-hyperintense lesion volume that appears hypointense on T1-weighted magnetic resonance imaging (T1LV/T2LV) were quantified. GM CBF and GM volume were evaluated globally, as well as regionally, using an atlas-based approach. RESULTS: Global GM CBF was lower in patients (56.9 ± 12.3 mL/100 g/min) than in HC (67.7 ± 10.0 mL/100 g/min; p < 0.001), a difference that was widespread across brain regions. Although total GM volume was comparable between groups, significant reductions were observed in a subset of subcortical structures. GM CBF negatively correlated with T1LV (r = -0.43, p = 0.0002) and T1LV/T2LV (r = -0.37, p = 0.0004), but not with T2LV. CONCLUSIONS: GM hypoperfusion occurs in MS and is associated with irreversible white matter damage, thus suggesting that cerebral hypoperfusion may actively contribute and possibly precede neurodegeneration by hampering tissue repair abilities in MS.

Cerebral blood flow patterns in preterm and term neonates assessed with pseudo-continuous arterial spin labeling perfusion MRI.

In preterm (PT) infants, regional cerebral blood flow (CBF) disturbances may predispose to abnormal brain maturation even without overt brain injury. Therefore, it would be informative to determine the spatial distribution of grey matter (GM) CBF in PT and full-term (FT) newborns at term-equivalent age (TEA) and to assess the relationship between the features of the CBF pattern and both prematurity and prematurity-related brain lesions. In this prospective study, we obtained measures of CBF in 66 PT (51 without and 15 with prematurity-related brain lesions) and 38 FT newborns through pseudo-continuous arterial spin labeling (pCASL) MRI acquired at TEA. The pattern of GM CBF was characterized by combining an atlas-based automated segmentation of structural MRI with spatial normalization and hierarchical clustering. The effects of gestational age (GA) at birth and brain injury on the CBF pattern were investigated. We identified 4 physiologically-derived clusters of brain regions that were labeled Fronto-Temporal, Parieto-Occipital, Insular-Deep GM (DGM) and Sensorimotor, from the least to the most perfused. We demonstrated that GM perfusion was associated with GA at birth in the Fronto-Temporal and Sensorimotor clusters, positively and negatively, respectively. Moreover, the presence of periventricular leukomalacia was associated with significantly increased Fronto-Temporal GM perfusion and decreased Insular-DGM perfusion, while the presence of germinal matrix hemorrhage appeared to mildly decrease the Insular-DGM perfusion. Prematurity and prematurity-related brain injury heterogeneously affect brain perfusion. ASL MRI may, therefore, have strong potential as a noninvasive tool for the accurate stratification of individuals at risk of domain-specific impairment.

Cerebrovascular reactivity in multiple sclerosis is restored with reduced inflammation during immunomodulation.

Cerebrovascular reactivity (CVR) reflects the capacity of the brain's vasculature to increase blood flow following a vasodilatory stimulus. Reactivity is an essential property of the brain's blood vessels that maintains nutrient supplies in the face of changing demand. In Multiple Sclerosis (MS), CVR may be diminished with brain inflammation and this may contribute to neurodegeneration. We test the hypothesis that CVR is altered with MS neuroinflammation and that it is restored when inflammation is reduced. Using a breath-hold task during functional Magnetic Resonance Imaging (MRI), we mapped grey matter and white matter CVRs (CVRGM and CVRWM, respectively) in 23 young MS patients, eligible for disease modifying therapy, before and during Interferon beta treatment. Inflammatory activity was inferred from the presence of Gadolinium enhancing lesions at MRI. Eighteen age and gender-matched healthy controls (HC) were also assessed. Enhancing lesions were observed in 12 patients at the start of the study and in 3 patients during treatment. Patients had lower pre-treatment CVRGM (p = 0.04) and CVRWM (p = 0.02) compared to HC. In patients, a lower pre-treatment CVRGM was associated with a lower GM volume (r = 0.60, p = 0.003). On-treatment, there was an increase in CVRGM (p = 0.02) and CVRWM (p = 0.03) that negatively correlated with pre-treatment CVR (GM: r = - 0.58, p = 0.005; WM: r = - 0.60, p = 0.003). CVR increased when enhancing lesions reduced in number (GM: r = - 0.48, p = 0.02, WM: r = - 0.62, p = 0.003). Resolution of inflammation may restore altered cerebrovascular function limiting neurodegeneration in MS. Imaging of cerebrovascular function may thereby inform tissue physiology and improve treatment monitoring.

Hemispheric functional segregation facilitates target detection during sustained visuospatial attention.

Visuospatial attention is strongly lateralized, with the right hemisphere commonly exhibiting stronger activation and connectivity patterns than the left hemisphere during attentive processes. However, whether such asymmetry influences inter-hemispheric information transfer and behavioral performance is not known. Here we used a region of interest (ROI) and network-based approach to determine steady-state fMRI functional connectivity (FC) in the whole cerebral cortex during a leftward/rightward covert visuospatial attention task. We found that the global FC topology between either ROIs or networks was independent on the attended side. The side of attention significantly modulated FC strength between brain networks, with leftward attention primarily involving the connections of the right visual network with dorsal and ventral attention networks in both the left and right hemisphere. High hemispheric functional segregation significantly correlated with faster target detection response times (i.e., better performance). Our findings suggest that the dominance of the right hemisphere in visuospatial attention is associated with an hemispheric functional segregation that is beneficial for behavioral performance.

A flow-diffusion model of oxygen transport for quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) with single gas calibrated fMRI.

One promising approach for mapping CMRO2 is dual-calibrated functional MRI (dc-fMRI). This method exploits the Fick Principle to combine estimates of CBF from ASL, and OEF derived from BOLD-ASL measurements during arterial O2 and CO2 modulations. Multiple gas modulations are required to decouple OEF and deoxyhemoglobin-sensitive blood volume. We propose an alternative single gas calibrated fMRI framework, integrating a model of oxygen transport, that links blood volume and CBF to OEF and creates a mapping between the maximum BOLD signal, CBF and OEF (and CMRO2). Simulations demonstrated the method's viability within physiological ranges of mitochondrial oxygen pressure, PmO2, and mean capillary transit time. A dc-fMRI experiment, performed on 20 healthy subjects using O2 and CO2 challenges, was used to validate the approach. The validation conveyed expected estimates of model parameters (e.g., low PmO2), with spatially uniform OEF maps (grey matter, GM, OEF spatial standard deviation ≈ 0.13). GM OEF estimates obtained with hypercapnia calibrated fMRI correlated with dc-fMRI (r = 0.65, p = 2·10-3). For 12 subjects, OEF measured with dc-fMRI and the single gas calibration method were correlated with whole-brain OEF derived from phase measures in the superior sagittal sinus (r = 0.58, p = 0.048; r = 0.64, p = 0.025 respectively). Simplified calibrated fMRI using hypercapnia holds promise for clinical application.

Perception is associated with the brain's metabolic response to sensory stimulation.

Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here, we show in human primary visual cortex (V1) that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) have markedly different neurometabolic responses as measured by proton functional magnetic resonance spectroscopy (1H-fMRS). In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate-aspartate shuttle, occurred in V1 only when the flickering was perceived, without any relation with other behavioral or physiological variables. Whereas the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering, indicating increased output from V1. These results demonstrate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD-fMRI.

Evaluation of denoising strategies for task-based functional connectivity: Equalizing residual motion artifacts between rest and cognitively demanding tasks.

In-scanner head motion represents a major confounding factor in functional connectivity studies and it raises particular concerns when motion correlates with the effect of interest. One such instance regards research focused on functional connectivity modulations induced by sustained cognitively demanding tasks. Indeed, cognitive engagement is generally associated with substantially lower in-scanner movement compared with unconstrained, or minimally constrained, conditions. Consequently, the reliability of condition-dependent changes in functional connectivity relies on effective denoising strategies. In this study, we evaluated the ability of common denoising pipelines to minimize and balance residual motion-related artifacts between resting-state and task conditions. Denoising pipelines-including realignment/tissue-based regression, PCA/ICA-based methods (aCompCor and ICA-AROMA, respectively), global signal regression, and censoring of motion-contaminated volumes-were evaluated according to a set of benchmarks designed to assess either residual artifacts or network identifiability. We found a marked heterogeneity in pipeline performance, with many approaches showing a differential efficacy between rest and task conditions. The most effective approaches included aCompCor, optimized to increase the noise prediction power of the extracted confounding signals, and global signal regression, although both strategies performed poorly in mitigating the spurious distance-dependent association between motion and connectivity. Censoring was the only approach that substantially reduced distance-dependent artifacts, yet this came at the great cost of reduced network identifiability. The implications of these findings for best practice in denoising task-based functional connectivity data, and more generally for resting-state data, are discussed.

Brain Network Modularity During a Sustained Working-Memory Task.

Spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal are spatially synchronized within specific brain networks and are thought to reflect synchronized brain activity. Networks are modulated by the performance of a task, even if the exact features and degree of such modulations are still elusive. The presence of networks showing anticorrelated fluctuations lend initially to suppose that a competitive relationship between the default mode network (DMN) and task positive networks (TPNs) supports the efficiency of brain processing. However, more recent results indicate that cooperative and competitive dynamics between networks coexist during task performance. In this study, we used graph analysis to assess the functional relevance of the topological reorganization of brain networks ensuing the execution of a steady state working-memory (WM) task. Our results indicate that the performance of an auditory WM task is associated with a switching between different topological configurations of several regions of specific networks, including frontoparietal, ventral attention, and dorsal attention areas, suggesting segregation of ventral attention regions in the presence of increased overall integration. However, the correct execution of the task requires integration between components belonging to all the involved networks.

Numerical simulation of the blood oxygenation level-dependent functional magnetic resonance signal using finite element method.

Since the introduction of functional magnetic resonance imaging (fMRI), several computational approaches have been developed to examine the effect of the morphology and arrangement of blood vessels on the blood oxygenation-level dependent (BOLD) signal in the brain. In the present work, we implemented the original Ogawa's model using a numerical simulation based on the finite element method (FEM) instead of the analytical models. In literature, there are different works using analytical methods to analyse the transverse relaxation rate ( R2∗ ), which BOLD signal is related to, modelling the vascular system with simple and canonical geometries such as an infinite cylinder model (ICM) or a set of cylinders. We applied the numerical simulation to the extravascular BOLD signal as a function of angular vessel distribution (perpendicular vs parallel to the static magnetic field) relevant for anatomical districts characterized by geometrical symmetries, such as spinal cord. Numerical simulations confirmed analytical results for the canonical ICM. Moreover, the perturbation to the magnetic field induced by blood deoxyhaemoglobin, as quantified assuming Brownian diffusion of water molecules around the vessel, revealed that vessels contribute the most to the variation of the R2∗ when they are preferentially perpendicular to the external magnetic field, regardless of their size. Our results indicate that the numerical simulation method is sensitive to the effects of different vascular geometry. This work highlights the opportunity to extend R2∗ simulations to realistic models of vasculature based on high-resolution anatomical images.

Influence of Repetitive Transcranial Magnetic Stimulation on Human Neurochemistry and Functional Connectivity: A Pilot MRI/MRS Study at 7 T.

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation method commonly used in the disciplines of neuroscience, neurology, and neuropsychiatry to examine or modulate brain function. Low frequency rTMS (e.g., 1 Hz) is associated with a net suppression of cortical excitability, whereas higher frequencies (e.g., 5 Hz) purportedly increase excitability. Magnetic resonance spectroscopy (MRS) and resting-state functional MRI (rsfMRI) allow investigation of neurochemistry and functional connectivity, respectively, and can assess the influence of rTMS in these domains. This pilot study investigated the effects of rTMS on the primary motor cortex using pre and post MRS and rsfMRI assessments at 7 T. Seven right-handed males (age 27 ± 7 y.o.) underwent single-voxel MRS and rsfMRI before and about 30-min after rTMS was administered outside the scanner for 20-min over the primary motor cortex of the left (dominant) hemisphere. All participants received 1-Hz rTMS; one participant additionally received 5-Hz rTMS in a separate session. Concentrations of 17 neurochemicals were quantified in left and right motor cortices. Connectivity metrics included fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) of both motor cortices, strength of related brain networks, and inter-hemispheric connectivity. The group-analysis revealed few trends (i.e., uncorrected for multiple comparisons), including a mean increase in the concentration of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) after the inhibitory rTMS protocol as compared to baseline in the stimulated (left) motor cortex (+8%, p = 0.043), along with a slight increase of total creatine (+2%, p = 0.018), and decrease of aspartate (-18%, p = 0.016). Additionally, GABA tended to decrease in the contralateral hemisphere (-6%, p = 0.033). No other changes of metabolite concentrations were found. Whereas functional connectivity outcomes did not exhibit trends of significant changes induced by rTMS, the percent changes of few connectivity metrics in both hemispheres were negatively correlated with GABA changes in the contralateral hemisphere. While studies in larger cohorts are needed to confirm these preliminary findings, our results indicate the safety and feasibility of detecting changes in key metabolites associated with neurotransmission after a single 1-Hz rTMS session, establishing the construct for future exploration of the neurochemical, and connectivity mechanisms of cortical responses to neuromodulation.

Brain Networks Underlying Eye's Pupil Dynamics.

Phasic changes in eye's pupil diameter have been repeatedly observed during cognitive, emotional and behavioral activity in mammals. Although pupil diameter is known to be associated with noradrenergic firing in the pontine Locus Coeruleus (LC), thus far the causal chain coupling spontaneous pupil dynamics to specific cortical brain networks remains unknown. In the present study, we acquired steady-state blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data combined with eye-tracking pupillometry from fifteen healthy subjects that were trained to maintain a constant attentional load. Regression analysis revealed widespread visual and sensorimotor BOLD-fMRI deactivations correlated with pupil diameter. Furthermore, we found BOLD-fMRI activations correlated with pupil diameter change rate within a set of brain regions known to be implicated in selective attention, salience, error-detection and decision-making. These regions included LC, thalamus, posterior cingulate cortex (PCC), dorsal anterior cingulate and paracingulate cortex (dACC/PaCC), orbitofrontal cortex (OFC), and right anterior insular cortex (rAIC). Granger-causality analysis performed on these regions yielded a complex pattern of interdependence, wherein LC and pupil dynamics were far apart in the network and separated by several cortical stages. Functional connectivity (FC) analysis revealed the ubiquitous presence of the superior frontal gyrus (SFG) in the networks identified by the brain regions correlated to the pupil diameter change rate. No significant correlations were observed between pupil dynamics, regional activation and behavioral performance. Based on the involved brain regions, we speculate that pupil dynamics reflects brain processing implicated in changes between self- and environment-directed awareness.

Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects.

The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are two large-scale brain imaging studies that will extend the recently completed HCP Young-Adult (HCP-YA) project to nearly the full lifespan, collecting structural, resting-state fMRI, task-fMRI, diffusion, and perfusion MRI in participants from 5 to 100+ years of age. HCP-D is enrolling 1300+ healthy children, adolescents, and young adults (ages 5-21), and HCP-A is enrolling 1200+ healthy adults (ages 36-100+), with each study collecting longitudinal data in a subset of individuals at particular age ranges. The imaging protocols of the HCP-D and HCP-A studies are very similar, differing primarily in the selection of different task-fMRI paradigms. We strove to harmonize the imaging protocol to the greatest extent feasible with the completed HCP-YA (1200+ participants, aged 22-35), but some imaging-related changes were motivated or necessitated by hardware changes, the need to reduce the total amount of scanning per participant, and/or the additional challenges of working with young and elderly populations. Here, we provide an overview of the common HCP-D/A imaging protocol including data and rationales for protocol decisions and changes relative to HCP-YA. The result will be a large, rich, multi-modal, and freely available set of consistently acquired data for use by the scientific community to investigate and define normative developmental and aging related changes in the healthy human brain.

Corrigendum: Multi-modal Brain MRI in Subjects with PD and iRBD.

[This corrects the article on p. 709 in vol. 11, PMID: 29311789.].

Scale-invariant rearrangement of resting state networks in the human brain under sustained stimulation.

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may not be the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation.

Disruption of Semantic Network in Mild Alzheimer's Disease Revealed by Resting-State fMRI.

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing.

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.

Temporal Information Entropy of the Blood-Oxygenation Level-Dependent Signals Increases in the Activated Human Primary Visual Cortex.

Time-domain analysis of blood-oxygenation level-dependent (BOLD) signals allows the identification of clusters of voxels responding to photic stimulation in primary visual cortex (V1). However, the characterization of information encoding into temporal properties of the BOLD signals of an activated cluster is poorly investigated. Here, we used Shannon entropy to determine spatial and temporal information encoding in the BOLD signal within the most strongly activated area of the human visual cortex during a hemifield photic stimulation. We determined the distribution profile of BOLD signals during epochs at rest and under stimulation within small (19-121 voxels) clusters designed to include only voxels driven by the stimulus as highly and uniformly as possible. We found consistent and significant increases (2-4% on average) in temporal information entropy during activation in contralateral but not ipsilateral V1, which was mirrored by an expected loss of spatial information entropy. These opposite changes coexisted with increases in both spatial and temporal mutual information (i.e., dependence) in contralateral V1. Thus, we showed that the first cortical stage of visual processing is characterized by a specific spatiotemporal rearrangement of intracluster BOLD responses. Our results indicate that while in the space domain BOLD maps may be incapable of capturing the functional specialization of small neuronal populations due to relatively low spatial resolution, some information encoding may still be revealed in the temporal domain by an increase of temporal information entropy.

Multi-modal Brain MRI in Subjects with PD and iRBD.

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a condition that often evolves into Parkinson's disease (PD). Therefore, by monitoring iRBD it is possible to track the neurodegeneration of individuals who may progress to PD. Here we aimed at piloting the characterization of brain tissue properties in mid-brain subcortical regions of 10 healthy subjects, 8 iRBD, and 9 early-diagnosed PD. We used a battery of magnetic resonance imaging (MRI) contrasts at 3 T, including adiabatic and non-adiabatic rotating frame techniques developed by our group, along with diffusion tensor imaging (DTI) and resting-state fMRI. Adiabatic T1ρ and T2ρ, and non-adiabatic RAFF4 (Relaxation Along a Fictitious Field in the rotating frame of rank 4) were found to have lower coefficient of variations and higher sensitivity to detect group differences as compared to DTI parameters such as fractional anisotropy and mean diffusivity. Significantly longer T1ρ were observed in the amygdala of PD subjects vs. controls, along with a trend of lower functional connectivity as measured by regional homogeneity, thereby supporting the notion that amygdalar dysfunction occurs in PD. Significant abnormalities in reward networks occurred in iRBD subjects, who manifested lower network strength of the accumbens. In agreement with previous studies, significantly longer T1ρ occurred in the substantia nigra compacta of PD vs. controls, indicative of neuronal degeneration, while regional homogeneity was lower in the substantia nigra reticulata. Finally, other trend-level findings were observed, i.e., lower RAFF4 and T2ρ in the midbrain of iRBD subjects vs. controls, possibly indicating changes in non-motor features as opposed to motor function in the iRBD group. We conclude that rotating frame relaxation methods along with functional connectivity measures are valuable to characterize iRBD and PD subjects, and with proper validation in larger cohorts may provide pathological signatures of iRBD and PD.

Intrinsic patterns of coupling between correlation and amplitude of low-frequency fMRI fluctuations are disrupted in degenerative dementia mainly due to functional disconnection.

Low frequency fluctuations (LFFs) of the BOLD signal are a major discovery in the study of the resting brain with functional magnetic resonance imaging (fMRI). Two fMRI-based measures, functional connectivity (FC), a measure of signal synchronicity, and the amplitude of LFFs (ALFF), a measure of signal periodicity, have been proved to be sensitive to changes induced by several neurological diseases, including degenerative dementia. In spite of the increasing use of these measures, whether and how they are related to each other remains to be elucidated. In this work we used voxel-wise FC and ALFF computed in different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; and full-band: 0.01-0.073 Hz), in order to assess their relationship in healthy elderly as well as the relevant changes induced by Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). We found that in healthy elderly subjects FC and ALFF are positively correlated in anterior and posterior cingulate cortex (full-band, slow-4 and slow-5), temporal cortex (full-band and slow-5), and in a set of subcortical regions (full-band and slow-4). These correlation patterns between FC and ALFF were absent in either AD or MCI patients. Notably, the loss of correlation between FC and ALFF in the AD group was primarily due to changes in FC rather than in ALFF. Our results indicate that degenerative dementia is characterized by a loss of global connection rather than by a decrease of fluctuation amplitude.