Synchronization and variability imbalance underlie cognitive impairment in primary-progressive multiple sclerosis

Within-Individual BOLD Signal Variability and its Implications for Task-Based Cognition: A Systematic Review

Within-individual blood oxygen level-dependent (BOLD) signal variability, intrinsic moment-to-moment signal fluctuations within a single individual in specific voxels across a given time course, is a relatively new metric recognized in the neuroimaging literature. Within-individual BOLD signal variability has been postulated to provide information beyond that provided by mean-based analysis. Synthesis of the literature using within-individual BOLD signal variability methodology to examine various cognitive domains is needed to understand how intrinsic signal fluctuations contribute to optimal performance. This systematic review summarizes and integrates this literature to assess task-based cognitive performance in healthy groups and few clinical groups. Included papers were published through October 17, 2022. Searches were conducted on PubMed and APA PsycInfo. Studies eligible for inclusion used within-individual BOLD signal variability methodology to examine BOLD signal fluctuations during task-based functional magnetic resonance imaging (fMRI) and/or examined relationships between task-based BOLD signal variability and out-of-scanner behavioral measure performance, were in English, and were empirical research studies. Data from each of the included 19 studies were extracted and study quality was systematically assessed. Results suggest that variability patterns for different cognitive domains across the lifespan (ages 7-85) may depend on task demands, measures, variability quantification method used, and age. As neuroimaging methods explore individual-level contributions to cognition, within-individual BOLD signal variability may be a meaningful metric that can inform understanding of neurocognitive performance. Further research in understudied domains/populations, and with consistent quantification methods/cognitive measures, will help conceptualize how intrinsic BOLD variability impacts cognitive abilities in healthy and clinical groups.

Differences Between Resting-State fMRI BOLD Variability and Default Mode Network Connectivity in Healthy Older and Younger Adults

Background: Resting-state fMRI analyses have been used to examine functional connectivity in the aging brain. Recently, fluctuations in the fMRI BOLD signal have been used as a potential marker of integrity in neural systems. Despite its increasing popularity, the results of BOLD variability analyses and traditional seed-based functional connectivity analyses have rarely been compared. The current study examined fMRI BOLD signal variability and default mode network seed-based analyses in healthy older and younger adults to better understand the unique contributions of these methodological approaches. Methods: Thirty-four healthy participants were separated into a younger adult group (age 25-35, n = 17) and an older adult group (age 65+, n = 17). For each participant, a map of the standard deviation of the BOLD signal (SDBOLD) was derived. Group comparisons examined differences in resting-state SDBOLD in younger versus older adults. Seed-based analyses were used to examine differences between younger and older adults in the default mode network. Results: Between-group comparisons revealed significantly greater BOLD variability in widespread brain regions in older relative to younger adults. There were no significant differences between younger and older adults in the default mode network connectivity. Conclusion: The current findings align with an increasing number of studies reporting greater BOLD variability in older relative to younger adults. The current results also suggest that the traditional resting state examination methods may not detect nuanced age-related differences. Further large-scale studies in an adult lifespan sample are needed to better understand the functional relevance of the BOLD variability in normative aging.

Cognitive impairment in multiple sclerosis: from phenomenology to neurobiological mechanisms

Multiple sclerosis (MS) is an autoimmune-mediated disease of the central nervous system characterized by inflammation, demyelination and chronic progressive neurodegeneration. Among its broad and unpredictable range of clinical symptoms, cognitive impairment (CI) is a common and disabling feature greatly affecting the patients' quality of life. Its prevalence is 20% up to 88% with a wide variety depending on the phenotype of MS, with highest frequency and severity in primary progressive MS. Involving different cognitive domains, CI is often associated with depression and other neuropsychiatric symptoms, but usually not correlated with motor and other deficits, suggesting different pathophysiological mechanisms. While no specific neuropathological data for CI in MS are available, modern research has provided evidence that it arises from the disease-specific brain alterations. Multimodal neuroimaging, besides structural changes of cortical and deep subcortical gray and white matter, exhibited dysfunction of fronto-parietal, thalamo-hippocampal, default mode and cognition-related networks, disruption of inter-network connections and involvement of the γ-aminobutyric acid (GABA) system. This provided a conceptual framework to explain how aberrant pathophysiological processes, including oxidative stress, mitochondrial dysfunction, autoimmune reactions and disruption of essential signaling pathways predict/cause specific disorders of cognition. CI in MS is related to multi-regional patterns of cerebral disturbances, although its complex pathogenic mechanisms await further elucidation. This article, based on systematic analysis of PubMed, Google Scholar and Cochrane Library, reviews current epidemiological, clinical, neuroimaging and pathogenetic evidence that could aid early identification of CI in MS and inform about new therapeutic targets and strategies.

Altered neural intrinsic oscillations in patients with multiple sclerosis: effects of cortical thickness

Objective

To investigate the effects of cortical thickness on the identification accuracy of fractional amplitude of low-frequency fluctuation (fALFF) in patients with multiple sclerosis (MS).

Methods

Resting-state functional magnetic resonance imaging data were collected from 31 remitting MS, 20 acute MS, and 42 healthy controls (HCs). After preprocessing, we first calculated two-dimensional fALFF (2d-fALFF) maps using the DPABISurf toolkit, and 2d-fALFF per unit thickness was obtained by dividing 2d-fALFF by cortical thickness. Then, between-group comparison, clinical correlation, and classification analyses were performed in 2d-fALFF and 2d-fALFF per unit thickness maps. Finally, we also examined whether the effect of cortical thickness on 2d-fALFF maps was affected by the subfrequency band.

Results

In contrast with 2d-fALFF, more changed regions in 2d-fALFF per unit thickness maps were detected in MS patients, such as increased region of the right inferior frontal cortex and faded regions of the right paracentral lobule, middle cingulate cortex, and right medial temporal cortex. There was a significant positive correlation between the disease duration and the 2d-fALFF values in the left early visual cortex in remitting MS patients (r = 0.517, Bonferroni-corrected, p = 0.008 × 4 < 0.05). In contrast with 2d-fALFF, we detected a positive correlation between the 2d-fALFF per unit thickness of the right ventral stream visual cortex and the modified Fatigue Impact Scale (MFIS) scores (r = 0.555, Bonferroni-corrected, p = 0.017 × 4 > 0.05). For detecting MS patients, 2d-fALFF and 2d- fALFF per unit thickness both performed remarkably well in support vector machine (SVM) analysis, especially in the remitting phase (AUC = 86, 83%). Compared with 2d-fALFF, the SVM model of 2d-fALFF per unit thickness had significantly higher classification performance in distinguishing between remitting and acute MS. More changed regions and more clinically relevant 2d-fALFF per unit thickness maps in the subfrequency band were also detected in MS patients.

Conclusion

By dividing the functional value by the cortical thickness, the identification accuracy of fALFF in MS patients was detected to be potentially influenced by cortical thickness. Additionally, 2d-fALFF per unit thickness is a potential diagnostic marker that can be utilized to distinguish between acute and remitting MS patients. Notably, we observed similar variations in the subfrequency band.

Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence

The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients' cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted，and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

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Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

A systematic review of resting state functional MRI connectivity changes and cognitive impairment in multiple sclerosis

INTRODUCTION

Cognitive impairment in multiple sclerosis (MS) is increasingly being investigated with resting state functional MRI (rs-fMRI) functional connectivity (FC) . However, results remain difficult to interpret, showing both high and low FC associated with cognitive impairment. We conducted a systematic review of rs-fMRI studies in MS to understand whether the direction of FC change relates to cognitive dysfunction, and how this may be influenced by the choice of methodology.

METHODS

Embase, Medline and PsycINFO were searched for studies assessing cognitive function and rs-fMRI FC in adults with MS.

RESULTS

Fifty-seven studies were included in a narrative synthesis. Of these, 50 found an association between cognitive impairment and FC abnormalities. Worse cognition was linked to high FC in 18 studies, and to low FC in 17 studies. Nine studies found patterns of both high and low FC related to poor cognitive performance, in different regions or for different MR metrics. There was no clear link to increased FC during early stages of MS and reduced FC in later stages, as predicted by common models of MS pathology. Throughout, we found substantial heterogeneity in study methodology, and carefully consider how this may impact on the observed findings.

DISCUSSION

These results indicate an urgent need for greater standardisation in the field - in terms of the choice of MRI analysis and the definition of cognitive impairment. This will allow us to use rs-fMRI FC as a biomarker in future clinical studies, and as a tool to understand mechanisms underpinning cognitive symptoms in MS.

Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis

Cognitive impairment (CI) occurs in 43 to 70% of multiple sclerosis (MS) patients at both early and later disease stages. Cognitive domains typically involved in MS include attention, information processing speed, memory, and executive control. The growing use of advanced magnetic resonance imaging (MRI) techniques is furthering our understanding on the altered structural connectivity (SC) and functional connectivity (FC) substrates of CI in MS. Regarding SC, different diffusion tensor imaging (DTI) measures (e.g., fractional anisotropy, diffusivities) along tractography-derived white matter (WM) tracts showed relevance toward CI. Novel diffusion MRI techniques, including diffusion kurtosis imaging, diffusion spectrum imaging, high angular resolution diffusion imaging, and neurite orientation dispersion and density imaging, showed more pathological specificity compared to the traditional DTI but require longer scan time and mathematical complexities for their interpretation. As for FC, task-based functional MRI (fMRI) has been traditionally used in MS to brain mapping the neural activity during various cognitive tasks. Analysis methods of resting fMRI (seed-based, independent component analysis, graph analysis) have been applied to uncover the functional substrates of CI in MS by revealing adaptive or maladaptive mechanisms of functional reorganization. The relevance for CI in MS of SC–FC relationships, reflecting common pathogenic mechanisms in WM and gray matter, has been recently explored by novel MRI analysis methods. This review summarizes recent advances on MRI techniques of SC and FC and their potential to provide a deeper understanding of the pathological substrates of CI in MS.

Altered anterior default mode network dynamics in progressive multiple sclerosis

BACKGROUND

Modifications in brain function remain relatively unexplored in progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of the disease at this stage.

OBJECTIVES

To characterize the dynamics of functional networks at rest in patients with PMS, and the relation with clinical disability.

METHODS

Thirty-two patients with PMS underwent clinical and cognitive assessment. The dynamic properties of functional networks, retrieved from transient brain activity, were obtained from patients and 25 healthy controls (HCs). Sixteen HCs and 19 patients underwent a 1-year follow-up (FU) clinical and imaging assessment. Differences in the dynamic metrics between groups, their longitudinal changes, and the correlation with clinical disability were explored.

RESULTS

PMS patients, compared to HCs, showed a reduced dynamic functional activation of the anterior default mode network (aDMN) and a decrease in its opposite-signed co-activation with the executive control network (ECN), at baseline and FU. Processing speed and visuo-spatial memory negatively correlated to aDMN dynamic activity. The anti-couplings between aDMN and auditory/sensory-motor network, temporal-pole/amygdala, or salience networks were differently associated with separate cognitive domains.

CONCLUSION

Patients with PMS presented an altered aDMN functional recruitment and anti-correlation with ECN. The aDMN dynamic functional activity and interaction with other networks explained cognitive disability.

The coupling of BOLD signal variability and degree centrality underlies cognitive functions and psychiatric diseases

Brain signal variability has been consistently linked to functional integration; however, whether this coupling is associated with cognitive functions and/or psychiatric diseases has not been clarified. Using multiple multimodality datasets, including resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP: N = 927) and a Beijing sample (N = 416) and cerebral blood flow (CBF) and rsfMRI data from a Hangzhou sample (N = 29), we found that, compared with the existing variability measure (i.e., SD_BOLD), the mean-scaled (standardized) fractional standard deviation of the BOLD signal (mfSD_BOLD) maintained very high test-retest reliability, showed greater cross-site reliability and was less affected by head motion. We also found strong reproducible couplings between the mfSD_BOLD and functional integration measured by the degree centrality (DC), both cross-voxel and cross-subject, which were robust to scanning and preprocessing parameters. Moreover, both mfSD_BOLD and DC were correlated with CBF, suggesting a common physiological basis for both measures. Critically, the degree of coupling between mfSD_BOLD and long-range DC was positively correlated with individuals' cognitive total composite scores. Brain regions with greater mismatches between mfSD_BOLD and long-range DC were more vulnerable to brain diseases. Our results suggest that BOLD signal variability could serve as a meaningful index of local function that underlies functional integration in the human brain and that a strong coupling between BOLD signal variability and functional integration may serve as a hallmark of balanced brain networks that are associated with optimal brain functions.

Alterations in functional connectivity are associated with white matter lesions and information processing efficiency in multiple sclerosis

Functional connectivity (FC) is typically altered in individuals with Multiple Sclerosis (MS). However, in relapsing-remitting multiple sclerosis (RRMS) patients, the relationship between brain FC, tissue integrity and cognitive impairment is still unclear as contradictory findings have been documented. In this exploratory study we compared both the whole brain connectome and resting state networks (RSNs) FC of twenty-one RRMS and seventeen healthy controls (HCs), using combined network based statistics and independent component analyses. The total white matter (WM) lesion volume and information processing efficiency were also correlated with FC in the RRMS group. Both whole brain connectome and individual RSNs FC were diminished in patients with RRMS compared to HC. Additionally, the reduction in FC was found to be a function of the total WM lesion volume, with greatest impact in those harboring the largest lesion volume. Finally, a positive correlation between FC and information processing efficiency was observed in RRMS. This complimentary whole brain and RSNs FC approach can contribute to clarify literature inconsistencies regarding FC alterations and provide new insights on the white matter structural damage in explaining functional abnormalities in RRMS.

Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis

Cognitive impairment is a frequent and meaningful symptom in multiple sclerosis (MS), caused by the accrual of brain structural damage only partially counteracted by effective functional reorganization. As both these aspects can be successfully investigated through the application of advanced neuroimaging, here, we offer an up-to-date overview of the latest findings on structural, functional and metabolic correlates of cognitive impairment in adults with MS, focusing on the mechanisms sustaining damage accrual and on the identification of useful imaging markers of cognitive decline.

Subacute melamine exposure disrupts task-based hippocampal information flow via inhibiting the subunits 2 and 3 of AMPA glutamate receptors expression

Although melamine exposure induces cognitive deficits and dysfunctional neurotransmission in hippocampal Cornus Ammonis (CA) 1 region of rats, it is unclear whether the neural function, such as neural oscillations between hippocampal CA3-CA1 pathway and postsynaptic receptors involves in these effects. The levels of alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor (AMPAR) subunit glutamate receptor (GluR) 1 and GluR2/3 in CA1 region of melamine-treated rats, which were intragastric treated with 300 mg/kg/day for 4 weeks, were detected. Following systemic or intra-hippocampal CA1 injection with GluR2/3 agonist, spatial learning of melamine-treated rats was assessed in Morris water maze (MWM) task. Local field potentials were recorded in CA3-CA1 pathway before and during behavioral test. General Partial Directed Coherence approach was applied to determine directionality of neural information flow between CA3 and CA1 regions. Results showed that melamine exposure reduced GluR2/3 but not GluR1 level and systemic or intra-hippocampal CA1 injection with GluR2/3 agonist effectively mitigated the learning deficits. Phase synchronization between CA3 and CA1 regions were significantly diminished in delta, theta and alpha oscillations. Coupling directional index and strength of CA3 driving CA1 were marked reduced as well. Intra-hippocampal CA1 infusion with GluR2/3 agonist significantly enhanced the phase locked value and reversed the melamine-induced reduction in the neural information flow (NIF) from CA3 to CA1 region. These findings support that melamine exposure decrease the expression of GluR2/3 subunit involved in weakening directionality index of NIF, and thereby induced spatial learning deficits.

Laminar analysis of the cortical T1/T2-weighted ratio at 7T

Objective

In this observational study, we explored cortical structure as function of cortical depth through a laminar analysis of the T1/T2-weighted (T1w/T2w) ratio, which has been related to dendrite density in ex vivo brain tissue specimens of patients with MS.

Methods

In 39 patients (22 relapsing-remitting, 13 female, age 41.1 ± 10.6 years; 17 progressive, 11 female, age 54.1 ± 9.9 years) and 21 healthy controls (8 female, , age 41.6 ± 10.6 years), we performed a voxel-wise analysis of T1w/T2w ratio maps from high-resolution 7T images from the subpial surface to the gray matter/white matter boundary. Six layers were sampled to ensure accuracy based on mean cortical thickness and image resolution.

Results

At the voxel-wise comparison (p < 0.05, family wise error rate corrected), the whole MS group showed lower T1w/T2w ratio values than controls, both when considering the entire cortex and each individual layer, with peaks occurring in the fusiform, temporo-occipital, and superior and middle frontal cortex. In relapsing-remitting patients, differences in the T1w/T2w ratio were only identified in the subpial layer, with the peak occurring in the fusiform cortex, whereas results obtained in progressive patients mirrored the widespread damage found in the whole group.

Conclusions

Laminar analysis of T1w/T2w ratio mapping confirms the presence of cortical damage in MS and shows a variable expression of intracortical damage according to the disease phenotype. Although in the relapsing-remitting stage, only the subpial layer appears susceptible to damage, in progressive patients, widespread cortical abnormalities can be observed, not only, as described before, with regard to myelin/iron concentration but, possibly, to other microstructural features.

Greater BOLD Variability is Associated With Poorer Cognitive Function in an Adult Lifespan Sample

Moment-to-moment fluctuations in brain signal assessed by functional magnetic resonance imaging blood oxygenation level dependent (BOLD) variability is increasingly thought to represent important “signal” rather than measurement-related “noise.” Efforts to characterize BOLD variability in healthy aging have yielded mixed outcomes, demonstrating both age-related increases and decreases in BOLD variability and both detrimental and beneficial associations. Utilizing BOLD mean-squared-successive-differences (MSSD) during a digit n-back working memory (WM) task in a sample of healthy adults (aged 20–94 years; n = 171), we examined effects of aging on whole-brain 1) BOLD variability during task (mean condition MSSD across 0–2–3-4 back conditions), 2) BOLD variability modulation to incrementally increasing WM difficulty (linear slope from 0–2–3-4 back), and 3) the association of age-related differences in variability with in- and out-of-scanner WM performance. Widespread cortical and subcortical regions evidenced increased mean variability with increasing age, with no regions evidencing age-related decrease in variability. Additionally, posterior cingulate/precuneus exhibited increased variability to WM difficulty. Notably, both age-related increases in BOLD variability were associated with significantly poorer WM performance in all but the oldest adults. These findings lend support to the growing corpus suggesting that brain-signal variability is altered in healthy aging; specifically, in this adult lifespan sample, BOLD-variability increased with age and was detrimental to cognitive performance.

Resting State BOLD Variability of the Posterior Medial Temporal Lobe Correlates with Cognitive Performance in Older Adults with and without Risk for Cognitive Decline

Local brain signal variability [SD of the BOLD signal (SDBOLD]] correlates with age and cognitive performance, and recently differentiated Alzheimer's disease (AD) patients from healthy controls. However, it is unknown whether changes to SDBOLD precede diagnosis of AD or mild cognitive impairment. We compared ostensibly healthy older adult humans who scored below the recommended threshold on the Montreal cognitive assessment (MoCA) and who showed reduced medial temporal lobe (MTL) volume in a previous study ("at-risk" group, n = 20), with healthy older adults who scored within the normal range on the MoCA ("control" group, n = 20). Using multivariate partial least-squares analysis we assessed the correlations between SDBOLD and age, MoCA score, global fractional anisotropy, global mean diffusivity, and four cognitive factors. Greater SDBOLD in the MTL and occipital cortex positively correlated with performance on cognitive control/speed tasks but negatively correlated with memory scores in the control group. These relations were weaker in the at-risk group. A post hoc analysis assessed associations between MTL volumes and SDBOLD in both groups. This revealed a negative correlation, most robust in the at-risk group, between MTL SDBOLD and MTL subregion volumetry, particularly the entorhinal and parahippocampal regions. Together, these results suggest that the association between SDBOLD and cognition differs between the at-risk and control groups, which may be because of lower MTL volumes in the at-risk group. Our data indicate relations between MTL SDBOLD and cognition may be helpful in understanding brain differences in individuals who may be at risk for further cognitive decline.

Resting State BOLD Variability Is Linked to White Matter Vascular Burden in Healthy Aging but Not in Older Adults With Subjective Cognitive Decline

Background: Alzheimer's disease (AD) is the leading cause of dementia. A lack of curative treatments and a rapidly aging global population have amplified the need for early biomarkers of the disease process. Recent advances suggest that subjective cognitive decline (SCD) may be one of the earliest symptomatic markers of the AD cascade. Previous studies have identified changes in variability in the blood-oxygen-level-dependent (BOLD) signal in patients with AD, with a possible association between BOLD variability and cerebrovascular factors in the aging brain. The objective of the current study was to determine whether changes in BOLD variability can be identified in individuals with SCD, and whether this signal may be associated with markers of cerebrovascular integrity in SCD and older adults without memory complaints. Method: Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database from 19 participants with SCD and 19 similarly-aged controls. For each participant, a map of BOLD signal variability (SDBOLD) was computed as the standard deviation of the BOLD time-series at each voxel. Group comparisons were performed to examine differences in resting-state SDBOLD in SCD vs. healthy controls. Relationships were then examined between participant SDBOLD maps and neuroimaging markers of white matter vascular infarcts in each group separately. Results: Between-group comparisons showed no significant differences in whole-brain SDBOLD in individuals with SCD and controls. In the healthy aging group, higher white matter hyperintensity (WMH) burden was associated with greater SDBOLD in right temporal regions (p < 0.05), and lower scores on a measure of global executive functioning. These associations were not identified in individuals with SCD. Conclusion: The current study underscores previous evidence for a relationship between SDBOLD and white matter vascular infarcts in the healthy aging brain. The findings also provide evidence for a dissociable relationship between healthy aging and SCD, such that in healthy controls, increased WMH is associated with declines in executive function that is not observed in older adults who present with memory complaints. Further multimodal work is needed to better understand the contributions of vascular pathology to the BOLD signal, and its potential relationship with pathological aging.

Cerebral blood flow and heart rate variability predict fatigue severity in patients with chronic fatigue syndrome

Prolonged, disabling fatigue is the hallmark of chronic fatigue syndrome (CFS). Previous neuroimaging studies have provided evidence for nervous system involvement in CFS etiology, including perturbations in brain structure/function. In this arterial spin labeling (ASL) MRI study, we examined variability in cerebral blood flow (CBFV) and heart rate (HRV) in 28 women: 14 with CFS and 14 healthy controls. We hypothesized that CBFV would be reduced in individuals with CFS compared to healthy controls, and that increased CBFV and HRV would be associated with lower levels of fatigue in affected individuals. Our results provided support for these hypotheses. Although no group differences in CBFV or HRV were detected, greater CBFV and more HRV power were both associated with lower fatigue symptom severity in individuals with CFS. Exploratory statistical analyses suggested that protective effects of high CBFV were greatest in individuals with low HRV. We also found novel evidence of bidirectional association between the very high frequency (VHF) band of HRV and CBFV. Taken together, the results of this study suggest that CBFV and HRV are potentially important measures of adaptive capacity in chronic illnesses like CFS. Future studies should address these measures as potential therapeutic targets to improve outcomes and reduce symptom severity in individuals with CFS.

Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes

The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or "BOLDSD," is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan.

Functional Connectivity in Multiple Sclerosis: Recent Findings and Future Directions

Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of the high variability of the lesion patterns between patients, it is difficult to relate existing biomarkers to symptoms and their progression. The scattered nature of lesions in multiple sclerosis offers itself to be studied through the lens of network analyses. Recent research into multiple sclerosis has taken such a network approach by making use of functional connectivity. In this review, we briefly introduce measures of functional connectivity and how to compute them. We then identify several common observations resulting from this approach: (a) high likelihood of altered connectivity in deep-gray matter regions, (b) decrease of brain modularity, (c) hemispheric asymmetries in connectivity alterations, and (d) correspondence of behavioral symptoms with task-related and task-unrelated networks. We propose incorporating such connectivity analyses into longitudinal studies in order to improve our understanding of the underlying mechanisms affected by multiple sclerosis, which can consequently offer a promising route to individualizing imaging-related biomarkers for multiple sclerosis.

Cerebellum and cognition in progressive MS patients: functional changes beyond atrophy?

BACKGROUND

The cerebellum is a predilection site of pathology in progressive multiple sclerosis (PMS) patients, contributing to cognitive deficits. Aim of this study was to investigate lobular cerebellar functional connectivity (FC) in PMS patients in relation to cognition.

METHODS

In this cross-sectional study, resting state fMRI analysis was carried out on 29 PMS patients (11 males, mean age 51.2 ± 11.9 years) and 22 age- and sex-matched healthy controls (HC) (11 males, mean age 49.6 ± 8.8 years). Data were analyzed with a seed-based approach, with four different seeds placed at the level of cerebellar Lobule VI, Crus I, Crus II and Lobule VIIb, accounting for cerebellar structural damage. Cognitive status was assessed with the BICAMS battery. Correlations between fMRI data and clinical variables were probed with the Spearman correlation coefficient.

RESULTS

When testing FC differences between PMS and HC without taking into account cerebellar structural damage, PMS patients showed a reduction of FC between Crus II/Lobule VIIb and the right frontal pole (p = 0.001 and p = 0.002, respectively), with an increased FC between Lobule VIIb and the right precentral gyrus (p < 0.001). After controlling for structural damage, PMS patients still showed a reduced FC between Crus II and right frontal pole (p = 0.005), as well as an increased FC between Lobule VIIb and right precentral gyrus (p = 0.003), with the latter showing an inverse correlation with BVMT scores (r = - 0.393; p = 0.03).

CONCLUSION

PMS patients show cerebellar FC rearrangements that are partially independent from cerebellar structural damage, and are likely expression of a maladaptive functional rewiring.

Resting State BOLD Variability in Alzheimer's Disease: A Marker of Cognitive Decline or Cerebrovascular Status?

Background: Alzheimer's disease (AD) is a neurodegenerative disorder that may benefit from early diagnosis and intervention. Therefore, there is a need to identify early biomarkers of AD using non-invasive techniques such as functional magnetic resonance imaging (fMRI). Recently, novel approaches to the analysis of resting-state fMRI data have been developed that focus on the moment-to-moment variability in the blood oxygen level dependent (BOLD) signal. The objective of the current study was to investigate BOLD variability as a novel early biomarker of AD and its associated psychophysiological correlates. Method: Data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 2 database from 19 participants with AD and 19 similarly aged controls. For each participant, a map of BOLD signal variability (SDBOLD) was computed as the standard deviation of the BOLD timeseries at each voxel. Group comparisons were performed to examine global differences in resting state SDBOLD in AD versus healthy controls. Correlations were then examined between participant SDBOLD maps and (1) ADNI-derived composite scores of memory and executive function and (2) neuroimaging markers of cerebrovascular status. Results: Between-group comparisons revealed significant (p < 0.05) increases in SDBOLD in patients with AD relative to healthy controls in right-lateralized frontal regions. Lower memory scores and higher WMH burden were associated with greater SDBOLD in the healthy control group (p < 0.1), but not individuals with AD. Conclusion: The current study provides proof of concept of a novel resting state fMRI analysis technique that is non-invasive, easily accessible, and clinically compatible. To further explore the potential of SDBOLD as a biomarker of AD, additional studies in larger, longitudinal samples are needed to better understand the changes in SDBOLD that characterize earlier stages of disease progression and their underlying psychophysiological correlates.