The importance of hippocampal dynamic connectivity in explaining memory function in multiple sclerosis

Early MS Identification Using Non-linear Functional Connectivity and Graph-theoretic Measures of Cognitive Task-fMRI Data

Introduction

Functional neuroimaging has developed a fundamental ground for understanding the physical basis of the brain. Recent studies have extracted invaluable information from the underlying substrate of the brain. However, cognitive deficiency has insufficiently been assessed by researchers in multiple sclerosis (MS). Therefore, extracting the brain network differences among relapsing-remitting MS (RRMS) patients and healthy controls as biomarkers of cognitive task functional magnetic resonance imaging (fMRI) data and evaluating such biomarkers using machine learning were the aims of this study.

Methods

In order to activate cognitive functions of the brain, blood-oxygen-level-dependent (BOLD) data were collected throughout the application of a cognitive task. Accordingly, a nonlinear-based brain network was established using kernel mutual information based on the automated anatomical labeling atlas (AAL). Subsequently, a statistical test was carried out to determine the variation in brain network measures between the two groups on binary adjacency matrices. We also found the prominent graph features by merging the Wilcoxon rank-sum test with the Fisher score as a hybrid feature selection method.

Results

The results of the classification performance measures showed that the construction of a brain network using a new nonlinear connectivity measure in task-fMRI performs better than the linear connectivity measures in terms of classification. The Wilcoxon rank-sum test also demonstrated a superior result for clinical applications.

Conclusion

We believe that non-linear connectivity measures, like KMI, outperform linear connectivity measures, like correlation coefficient in finding the biomarkers of MS disease according to classification performance metrics.

Highlights

The performance of some brain regions (the hippocampus, parahippocampus, cuneus, pallidum, and two segments of the cerebellum) is different between healthy and MS people.Non-linear connectivity measures, such as Kernel mutual information, perform better than linear connectivity measures, such as correlation coefficient, in finding the biomarkers of MS disease.

Plain Language Summary

Multiple sclerosis (MS) can disrupt the function of the central nervous system. The function of brain network is impaired in these patients. In this study, we evaluated the change in brain network based on a non-linear connectivity measure using cognitive task-based fMRI data between MS patients and healthy controls. We used Kernel mutual information (KMI) and designed a graph network based on the results of connectivity analysis. The the paced auditory serial addition test was used to activate cognitive functions of the brain. The classification was employed for the results using different decision tree -based technique and support vector machine. KMI can be considered a valid measure of connectivity over linear measures, like the correlation coefficient. KMI does not have the drawbacks of mutual information technique. However, further studies should be implemented on brain data of MS patients to draw more definite conclusions.

Male and female are not the same: a multicenter study of static and dynamic functional connectivity in relapse-remitting multiple sclerosis in China

Background

Sex-related effects have been observed in relapsing-remitting multiple sclerosis (RRMS), but their impact on functional networks remains unclear.

Objective

To investigate the sex-related differences in connectivity strength and time variability within large-scale networks in RRMS.

Methods

This is a multi-center retrospective study. A total of 208 RRMS patients (135 females; 37.55 ± 11.47 years old) and 228 healthy controls (123 females; 36.94 ± 12.17 years old) were included. All participants underwent clinical and MRI assessments. Independent component analysis was used to extract resting-state networks (RSNs). We assessed the connectivity strength using spatial maps (SMs) and static functional network connectivity (sFNC), evaluated temporal properties and dynamic functional network connectivity (dFNC) patterns of RSNs using dFNC, and investigated their associations with structural damage or clinical variables.

Results

For static connectivity, only male RRMS patients displayed decreased SMs in the attention network and reduced sFNC between the sensorimotor network and visual or frontoparietal networks compared with healthy controls [P<0.05, false discovery rate (FDR) corrected]. For dynamic connectivity, three recurring states were identified for all participants: State 1 (sparse connected state; 42%), State 2 (middle-high connected state; 36%), and State 3 (high connected state; 16%). dFNC analyses suggested that altered temporal properties and dFNC patterns only occurred in females: female patients showed a higher fractional time (P<0.001) and more dwell time in State 1 (P<0.001) with higher transitions (P=0.004) compared with healthy females. Receiver operating characteristic curves revealed that the fraction time and mean dwell time of State 1 could significantly distinguish female patients from controls (area under the curve: 0.838-0.896). In addition, female patients with RRMS also mainly showed decreased dFNC in all states, particularly within cognitive networks such as the default mode, frontoparietal, and visual networks compared with healthy females (P < 0.05, FDR corrected).

Conclusion

Our results observed alterations in connectivity strength only in male patients and time variability in female patients, suggesting that sex-related effects may play an important role in the functional impairment and reorganization of RRMS.

Larger lesion volume in people with multiple sclerosis is associated with increased transition energies between brain states and decreased entropy of brain activity

Quantifying the relationship between the brain's functional activity patterns and its structural backbone is crucial when relating the severity of brain pathology to disability in multiple sclerosis (MS). Network control theory (NCT) characterizes the brain's energetic landscape using the structural connectome and patterns of brain activity over time. We applied NCT to investigate brain-state dynamics and energy landscapes in controls and people with MS (pwMS). We also computed entropy of brain activity and investigated its association with the dynamic landscape's transition energy and lesion volume. Brain states were identified by clustering regional brain activity vectors, and NCT was applied to compute the energy required to transition between these brain states. We found that entropy was negatively correlated with lesion volume and transition energy, and that larger transition energies were associated with pwMS with disability. This work supports the notion that shifts in the pattern of brain activity in pwMS without disability results in decreased transition energies compared to controls, but, as this shift evolves over the disease, transition energies increase beyond controls and disability occurs. Our results provide the first evidence in pwMS that larger lesion volumes result in greater transition energy between brain states and decreased entropy of brain activity.

Abnormal dynamic functional connectivity of hippocampal subregions associated with working memory impairment in melancholic depression

BACKGROUND

Previous studies have demonstrated structural and functional changes of the hippocampus in patients with major depressive disorder (MDD). However, no studies have analyzed the dynamic functional connectivity (dFC) of hippocampal subregions in melancholic MDD. We aimed to reveal the patterns for dFC variability in hippocampus subregions - including the bilateral rostral and caudal areas and its associations with cognitive impairment in melancholic MDD.

METHODS

Forty-two treatment-naive MDD patients with melancholic features and 55 demographically matched healthy controls were included. The sliding-window analysis was used to evaluate whole-brain dFC for each hippocampal subregions seed. We assessed between-group differences in the dFC variability values of each hippocampal subregion in the whole brain and cognitive performance on the MATRICS Consensus Cognitive Battery (MCCB). Finally, association analysis was conducted to investigate their relationships.

RESULTS

Patients with melancholic MDD showed decreased dFC variability between the left rostral hippocampus and left anterior lobe of cerebellum compared with healthy controls (voxel p < 0.005, cluster p < 0.0125, GRF corrected), and poorer cognitive scores in working memory, verbal learning, visual learning, and social cognition (all p < 0.05). Association analysis showed that working memory was positively correlated with the dFC variability values of the left rostral hippocampus-left anterior lobe of the cerebellum (r = 0.338, p = 0.029) in melancholic MDD.

CONCLUSIONS

These findings confirmed the distinct dynamic functional pathway of hippocampal subregions in patients with melancholic MDD, and suggested that the dysfunction of hippocampus-cerebellum connectivity may be underlying the neural substrate of working memory impairment in melancholic MDD.

Abnormal thalamic functional connectivity correlates with cardiorespiratory fitness and physical activity in progressive multiple sclerosis

BACKGROUND

Altered thalamic volumes and resting state (RS) functional connectivity (FC) might be associated with physical activity (PA) and cardiorespiratory fitness (CRF) in people with progressive multiple sclerosis (PMS).

OBJECTIVES

To assess thalamic structural and functional alterations and investigate their correlations with PA/CRF levels in people with PMS.

METHODS

Seven-day accelerometry and cardiopulmonary exercise testing were used to assess PA/CRF levels in 91 persons with PMS. They underwent 3.0 T structural and RS fMRI acquisition with 37 age/sex-matched healthy controls (HC). Between-group comparisons of MRI measures and their correlations with PA/CRF variables were assessed.

RESULTS

PMS people had lower volumes compared to HC (all p < 0.001). At corrected threshold, PMS showed decreased intra- and inter-thalamic RS FC, and increased RS FC between the thalamus and the hippocampus, bilaterally. At uncorrected threshold, decreased thalamic RS FC with caudate nucleus, cerebellum and anterior cingulate cortex (ACC), as well as increased thalamic RS FC with occipital regions, were also detected. Lower CRF, measured as peak oxygen consumption (VO_2peak), correlated with lower white matter volume (r = 0.31, p = 0.03). Moreover, lower levels of light PA correlated with increased thalamic RS FC with the right hippocampus (r = - 0.3, p = 0.05).

DISCUSSION

People with PMS showed widespread brain atrophy, as well as pronounced intra-thalamic and thalamo-hippocampal RS FC abnormalities. White matter atrophy correlated with CRF, while increased thalamo-hippocampal RS FC was associated to worse PA levels. Thalamic RS FC might be used to monitor physical impairment and efficacy of rehabilitative and disease-modifying treatments in future studies.

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a "network collapse". After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.

Temporal Dynamics of Resting-state Functional Networks and Cognitive Functioning following Systemic Treatment for Breast Cancer

Many women with breast cancer suffer from a decline in memory and executive function, particularly after treatment with chemotherapy. Recent neuroimaging studies suggest that changes in network dynamics are fundamental in decline in these cognitive functions. This has, however, not yet been investigated in breast cancer patients. Using resting state functional magnetic resonance imaging, we prospectively investigated whether changes in dynamic functional connectivity were associated with changes in memory and executive function. We examined 34 breast cancer patients that received chemotherapy, 32 patients that did not receive chemotherapy, and 35 no-cancer controls. All participants were assessed prior to treatment and six months after completion of chemotherapy, or at similar intervals for the other groups. To assess memory and executive function, we used the Hopkins Verbal Learning Test – Immediate Recall and the Trail Making Test B, respectively. Using a sliding window approach, we then evaluated dynamic functional connectivity of resting state networks supporting memory and executive function, i.e. the default mode network and frontoparietal network, respectively. Next, we directly investigated the association between cognitive performance and dynamic functional connectivity. We found no group differences in cognitive performance or connectivity measures. The association between dynamic functional connectivity of the default mode network and memory differed significantly across groups. This was not the case for the frontoparietal network and executive function. This suggests that cancer and chemotherapy alter the role of dynamic functional connectivity in memory function. Further implications of these findings are discussed.

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 more unstable resting-state functional network in cognitively declining multiple sclerosis

Cognitive impairment is common in people with multiple sclerosis and strongly affects their daily functioning. Reports have linked disturbed cognitive functioning in multiple sclerosis to changes in the organization of the functional network. In a healthy brain, communication between brain regions and which network a region belongs to is continuously and dynamically adapted to enable adequate cognitive function. However, this dynamic network adaptation has not been investigated in multiple sclerosis, and longitudinal network data remain particularly rare. Therefore, the aim of this study was to longitudinally identify patterns of dynamic network reconfigurations that are related to the worsening of cognitive decline in multiple sclerosis. Resting-state functional MRI and cognitive scores (expanded Brief Repeatable Battery of Neuropsychological tests) were acquired in 230 patients with multiple sclerosis and 59 matched healthy controls, at baseline (mean disease duration: 15 years) and at 5-year follow-up. A sliding-window approach was used for functional MRI analyses, where brain regions were dynamically assigned to one of seven literature-based subnetworks. Dynamic reconfigurations of subnetworks were characterized using measures of promiscuity (number of subnetworks switched to), flexibility (number of switches), cohesion (mutual switches) and disjointedness (independent switches). Cross-sectional differences between cognitive groups and longitudinal changes were assessed, as well as relations with structural damage and performance on specific cognitive domains. At baseline, 23% of patients were cognitively impaired (≥2/7 domains Z < −2) and 18% were mildly impaired (≥2/7 domains Z < −1.5). Longitudinally, 28% of patients declined over time (0.25 yearly change on ≥2/7 domains based on reliable change index). Cognitively impaired patients displayed more dynamic network reconfigurations across the whole brain compared with cognitively preserved patients and controls, i.e. showing higher promiscuity (P = 0.047), flexibility (P = 0.008) and cohesion (P = 0.008). Over time, cognitively declining patients showed a further increase in cohesion (P = 0.004), which was not seen in stable patients (P = 0.544). More cohesion was related to more severe structural damage (average r = 0.166, P = 0.015) and worse verbal memory (r = −0.156, P = 0.022), information processing speed (r = −0.202, P = 0.003) and working memory (r = −0.163, P = 0.017). Cognitively impaired multiple sclerosis patients exhibited a more unstable network reconfiguration compared to preserved patients, i.e. brain regions switched between subnetworks more often, which was related to structural damage. This shift to more unstable network reconfigurations was also demonstrated longitudinally in patients that showed cognitive decline only. These results indicate the potential relevance of a progressive destabilization of network topology for understanding cognitive decline in multiple sclerosis.

Effect of 3-Month Aerobic Dance on Hippocampal Volume and Cognition in Elderly People With Amnestic Mild Cognitive Impairment: A Randomized Controlled Trial

As an intermediate state between normal aging and dementia, mild cognitive impairment (MCI), especially amnestic MCI (aMCI), is a key stage in the prevention and intervention of Alzheimer’s disease (AD). Whether dancing could increase the hippocampal volume of seniors with aMCI remains debatable. The aim of this study was to investigate the influence of aerobic dance on hippocampal volume and cognition after 3 months of aerobic dance in older adults with aMCI. In this randomized controlled trial, 68 elderly people with aMCI were randomized to either the aerobic dance group or the control group using a 1:1 allocation ratio. Ultimately, 62 of 68 participants completed this study, and the MRI data of 54 participants were included. A specially designed aerobic dance routine was performed by the dance group three times per week for 3 months, and all participants received monthly healthcare education after inclusion. MRI with a 3.0T MRI scanner and cognitive assessments were performed before and after intervention. High-resolution three-dimensional (3D) T1-weighted anatomical images were acquired for the analysis of hippocampal volume. A total of 35 participants (mean age: 71.51 ± 6.62 years) were randomized into the aerobic dance group and 33 participants (mean age: 69.82 ± 7.74 years) into the control group. A multiple linear regression model was used to detect the association between intervention and the difference of hippocampal volumes as well as the change of cognitive scores at baseline and after 3 months. The intervention group showed greater right hippocampal volume (β [95% CI]: 0.379 [0.117, 0.488], p = 0.002) and total hippocampal volume (β [95% CI]: 0.344 [0.082, 0.446], p = 0.005) compared to the control group. No significant association of age or gender was found with unilateral or global hippocampal volume. There was a correlation between episodic memory and intervention, as the intervention group showed a higher Wechsler Memory Scale-Revised Logical Memory (WMS-RLM) score (β [95% CI]: 0.326 [1.005, 6.773], p = 0.009). Furthermore, an increase in age may cause a decrease in the Mini-Mental State Examination (MMSE) score (β [95% CI]: −0.366 [−0.151, −0.034], p = 0.002). In conclusion, 3 months of aerobic dance could increase the right and total hippocampal volumes and improve episodic memory in elderly persons with aMCI.

Clinical Trial Registration: This study was registered on the Chinese Clinical Trial Registry [www.chictr.org.cn], identifier [ChiCTR-INR-15007420].

Functional network dynamics and decreased conscientiousness in multiple sclerosis

BACKGROUND

Conscientiousness is a personality trait that declines in people with multiple sclerosis (PwMS) and its decline predicts worse clinical outcomes. This study aims to investigate the neural underpinnings of lower Conscientiousness in PwMS by examining MRI anomalies in functional network dynamics.

METHODS

70 PwMS and 50 healthy controls underwent personality assessment and resting-state MRI. Associations with dynamic functional network properties (i.e., eigenvector centrality) were evaluated, using a dynamic sliding-window approach.

RESULTS

In PwMS, lower Conscientiousness was associated with increased variability of centrality in the left insula (t_max = 4.21) and right inferior parietal lobule (t_max = 3.79); a relationship also observed in regressions accounting for handedness, disease duration, disability, and tract disruption in relevant structural networks (ΔR² = 0.071, p = 0.003; ΔR² = 0.094, p = 0.004). Centrality dynamics of the observed regions were not associated with Neuroticism (R² < 0.001, p = 0.956; R² < 0.001, p = 0.945). As well, higher Conscientiousness was associated with greater variability in connectivity for the left insula with the default-mode network (F = 3.92, p = 0.023) and limbic network (F = 5.66, p = 0.005).

CONCLUSION

Lower Conscientiousness in PwMS was associated with increased variability in network centrality, most prominently for the left insula and right inferior parietal cortex. This effect, specific to Conscientiousness and significant after accounting for disability and structural network damage, could indicate that overall stable network centrality is lost in patients with low Conscientiousness, especially for the insula and right parietal cortex. The positive relationship between Conscientiousness and variability of connectivity between left insula and default-mode network potentially affirms that dynamics between the salience and default-mode networks is related to the regulation of behavior.

Correlations between hippocampal functional connectivity, structural changes, and clinical data in patients with relapsing-remitting multiple sclerosis: a case-control study using multimodal magnetic resonance imaging

Multiple sclerosis is associated with structural and functional brain alterations leading to cognitive impairments across multiple domains including attention, memory, and the speed of information processing. The hippocampus, which is a brain important structure involved in memory, undergoes microstructural changes in the early stage of multiple sclerosis. In this study, we analyzed hippocampal function and structure in patients with relapsing-remitting multiple sclerosis and explored correlations between the functional connectivity of the hippocampus to the whole brain, changes in local brain function and microstructure, and cognitive function at rest. We retrospectively analyzed data from 20 relapsing-remitting multiple sclerosis patients admitted to the Department of Neurology at the China-Japan Union Hospital of Jilin University, China, from April 2015 to November 2019. Sixteen healthy volunteers were recruited as the healthy control group. All participants were evaluated using a scale of extended disability status and the Montreal cognitive assessment within 1 week before and after head diffusion tensor imaging and functional magnetic resonance imaging. Compared with the healthy control group, the patients with relapsing-remitting multiple sclerosis had lower Montreal cognitive assessment scores and regions of simultaneously enhanced and attenuated whole-brain functional connectivity and local functional connectivity in the bilateral hippocampus. Hippocampal diffusion tensor imaging data showed that, compared with the healthy control group, patients with relapsing-remitting multiple sclerosis had lower hippocampal fractional anisotropy values and higher mean diffusivity values, suggesting abnormal hippocampal structure. The left hippocampus whole-brain functional connectivity was negatively correlated with the Montreal cognitive assessment score (r = −0.698, P = 0.025), and whole-brain functional connectivity of the right hippocampus was negatively correlated with extended disability status scale score (r = −0.649, P = 0.042). The mean diffusivity value of the left hippocampus was negatively correlated with the Montreal cognitive assessment score (r = −0.729, P = 0.017) and positively correlated with the extended disability status scale score (r = 0.653, P = 0.041). The right hippocampal mean diffusivity value was positively correlated with the extended disability status scale score (r = 0.684, P = 0.029). These data suggest that the functional connectivity and presence of structural abnormalities in the hippocampus in patients with relapse-remission multiple sclerosis are correlated with the degree of cognitive function and extent of disability. This study was approved by the Ethics Committee of China-Japan Union Hospital of Jilin University, China (approval No. 201702202) on February 22, 2017.

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.

Delayed access to conscious processing in multiple sclerosis: Reduced cortical activation and impaired structural connectivity

Although multiple sclerosis (MS) is frequently accompanied by visuo‐cognitive impairment, especially functional brain mechanisms underlying this impairment are still not well understood. Consequently, we used a functional MRI (fMRI) backward masking task to study visual information processing stratifying unconscious and conscious in MS. Specifically, 30 persons with MS (pwMS) and 34 healthy controls (HC) were shown target stimuli followed by a mask presented 8–150 ms later and had to compare the target to a reference stimulus. Retinal integrity (via optical coherence tomography), optic tract integrity (visual evoked potential; VEP) and whole brain structural connectivity (probabilistic tractography) were assessed as complementary structural brain integrity markers. On a psychophysical level, pwMS reached conscious access later than HC (50 vs. 16 ms, p < .001). The delay increased with disease duration (p < .001, β = .37) and disability (p < .001, β = .24), but did not correlate with conscious information processing speed (Symbol digit modality test, β = .07, p = .817). No association was found for VEP and retinal integrity markers. Moreover, pwMS were characterized by decreased brain activation during unconscious processing compared with HC. No group differences were found during conscious processing. Finally, a complementary structural brain integrity analysis showed that a reduced fractional anisotropy in corpus callosum and an impaired connection between right insula and primary visual areas was related to delayed conscious access in pwMS. Our study revealed slowed conscious access to visual stimulus material in MS and a complex pattern of functional and structural alterations coupled to unconscious processing of/delayed conscious access to visual stimulus material in MS.

Identifying the Distinct Cognitive Phenotypes in Multiple Sclerosis

Importance

Cognitive impairment is a common and disabling feature of multiple sclerosis (MS), but a precise characterization of cognitive phenotypes in patients with MS is lacking.

Objectives

To identify cognitive phenotypes in a clinical cohort of patients with MS and to characterize their clinical and magnetic resonance imaging (MRI) features.

Design, Setting, and Participants

This multicenter cross-sectional study consecutively screened clinically stable patients with MS and healthy control individuals at 8 MS centers in Italy from January 1, 2010, to October 31, 2019. Patients with MS and healthy control individuals who were not using psychoactive drugs and had no history of other neurological or medical disorders, learning disability, severe head trauma, and alcohol or drug abuse were enrolled.

Main Outcomes and Measures

Participants underwent a neurological examination and a cognitive evaluation with the Rao Brief Repeatable Battery and Stroop Color and Word Test. A subgroup of participants also underwent a brain MRI examination. Latent profile analysis was used on cognitive test z scores to identify cognitive phenotypes. Linear regression and mixed-effects models were used to define clinical and MRI features of each phenotype.

Results

A total of 1212 patients with MS (mean [SD] age, 41.1 [11.1] years; 784 women [64.7%]) and 196 healthy control individuals (mean [SD] age, 40.4 [8.6] years; 130 women [66.3%]) were analyzed in this study. Five cognitive phenotypes were identified: preserved cognition (n = 235 patients [19.4%]), mild-verbal memory/semantic fluency (n = 362 patients [29.9%]), mild-multidomain (n = 236 patients [19.5%]), severe-executive/attention (n = 167 patients [13.8%]), and severe-multidomain (n = 212 patients [17.5%]) involvement. Patients with preserved cognition and mild-verbal memory/semantic fluency were younger (mean [SD] age, 36.5 [9.8] years and 38.2 [11.1] years) and had shorter disease duration (mean [SD] 8.0 [7.3] years and 8.3 [7.6] years) compared with patients with mild-multidomain (mean [SD] age, 42.6 [11.2] years; mean [SD] disease duration, 12.8 [9.6] years; P < .001), severe-executive/attention (mean [SD] age, 42.9 [11.7] years; mean [SD] disease duration, 12.2 [9.5] years; P < .001), and severe-multidomain (mean [SD] age, 44.0 [11.0] years; mean [SD] disease duration, 13.3 [10.2] years; P < .001) phenotypes. Severe cognitive phenotypes prevailed in patients with progressive MS. At MRI evaluation, compared with those with preserved cognition, patients with mild-verbal memory/semantic fluency exhibited decreased mean (SE) hippocampal volume (5.42 [0.68] mL vs 5.13 [0.68] mL; P = .04), patients with the mild-multidomain phenotype had decreased mean (SE) cortical gray matter volume (687.69 [35.40] mL vs 662.59 [35.48] mL; P = .02), patients with severe-executive/attention had higher mean (SE) T2-hyperintense lesion volume (51.33 [31.15] mL vs 99.69 [34.07] mL; P = .04), and patients with the severe-multidomain phenotype had extensive brain damage, with decreased volume in all the brain structures explored, except for nucleus pallidus, amygdala and caudate nucleus.

Conclusions and Relevance

This study found that by defining homogeneous and clinically meaningful phenotypes, the limitations of the traditional dichotomous classification in MS can be overcome. These phenotypes can represent a more meaningful measure of the cognitive status of patients with MS and can help define clinical disability, support clinicians in treatment choices, and tailor cognitive rehabilitation strategies.

Mind the gap: from neurons to networks to outcomes in multiple sclerosis

MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.

Dynamic functional connectivity as a neural correlate of fatigue in multiple sclerosis

BACKGROUND

More than 80% of multiple sclerosis (MS) patients experience symptoms of fatigue. MS-related fatigue is only partly explained by structural (lesions and atrophy) and functional (brain activation and conventional static functional connectivity) brain properties.

OBJECTIVES

To investigate the relationship of dynamic functional connectivity (dFC) with fatigue in MS patients and to compare dFC with commonly used clinical and MRI parameters.

METHODS

In 35 relapsing-remitting MS patients (age: 42.83 years, female/male: 20/15, disease duration: 11 years) and 19 healthy controls (HCs) (age: 41.38 years, female/male: 11/8), fatigue was measured using the CIS-20r questionnaire at baseline and at 6-month follow-up. All subjects underwent structural and resting-state functional MRI at baseline. Global static functional connectivity (sFC) and dynamic functional connectivity (dFC) were calculated. dFC was assessed using a sliding-window approach by calculating the summed difference (diff) and coefficient of variation (cv) across windows. Moreover, regional connectivity between regions previously associated with fatigue in MS was estimated (i.e. basal ganglia and regions of the Default Mode Network (DMN): medial prefrontal, posterior cingulate and precuneal cortices). Hierarchical regression analyses were performed with forward selection to identify the most important correlates of fatigue at baseline. Results were not corrected for multiple testing due to the exploratory nature of the study.

RESULTS

Patients were more fatigued than HCs at baseline (p = 0.001) and follow-up (p = 0.002) and fatigue in patients was stable over time (p = 0.213). Patients had significantly higher baseline global dFC than HCs, but no difference in basal ganglia-DMN dFC. In the regression model for baseline fatigue in patients, basal ganglia-DMN dFC-cv (standardized β = -0.353) explained 12.5% additional variance on top of EDSS (p = 0.032). Post-hoc analysis revealed higher basal ganglia-DMN dFC-cv in non-fatigued patients compared to healthy controls (p = 0.013), whereas fatigued patients and healthy controls showed similar basal ganglia-DMN dFC.

CONCLUSIONS

Less dynamic connectivity between the basal ganglia and the cortex is associated with greater fatigue in MS patients, independent of disability status. Within patients, lower dynamics of these connections could relate to lower efficiency and increased fatigue. Increased dynamics in non-fatigued patients compared to healthy controls might represent a network organization that protects against fatigue or signal early network dysfunction.

Altered Dynamic Functional Connectivity in Patients With Mitochondrial Encephalomyopathy With Lactic Acidosis and Stroke-Like Episodes (MELAS) at Acute and Chronic Stages: Shared and Specific Brain Connectivity Abnormalities

BACKGROUND

Mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) is a rare maternally inherited genetic disease; however, little is known about its underlying brain basis. Furthermore, the dynamic functional connectivity (dFC) of brain networks in MELAS has not been explored.

PURPOSE

To investigate the abnormalities of dFC in patients with MELAS at the acute and chronic stages, and to determine the possible relations between dynamic connectivity alterations and volumes of stroke-like lesions (SLLs).

STUDY TYPE

Prospective.

SUBJECTS

Twenty-two MELAS patients at the acute stage, 23 MELAS patients at the chronic stage, and 22 healthy controls.

FIELD STRENGTH/SEQUENCE

Single-shot gradient-recalled echo planar imaging (EPI) sequence at 3T.

ASSESSMENT

Dynamic FC states were estimated using the sliding window approach and k-means clustering analyses. Combined with graph theory, the topological properties of the dFC network were also accessed.

STATISTICAL TESTS

Permutation test, Pearson correlation coefficient, and false discovery rate correction.

RESULTS

We identified four dFC states and found that MELAS patients (especially at the acute stage) spent more time in a state with weaker connectivity (state 1) and less time in states with stronger connectivity. In addition, volumes of acute SLLs were positively correlated with mean dwell time in state 1 (r = 0.539, P < 0.05) and negatively correlated with the number of transitions (r = -0.520, P < 0.05). Furthermore, MELAS patients at the acute stage exhibited significantly increased global efficiency (P < 0.01) and decreased local efficiency (P < 0.001) compared to the controls and the patients at the chronic stage. Patients at the chronic stage only showed significantly (P < 0.001) decreased local efficiency compared to the controls.

DATA CONCLUSION

Our findings suggest similar and distinct dFC alterations in MELAS patents at the acute and chronic stages, providing novel insights for understanding the neuropathological mechanisms of MELAS. Level of Evidence 2 Technical Efficacy Stage Stage 2 J. MAGN. RESON. IMAGING 2021;53:427-436.

Cognitive Impairment and Brain Reorganization in MS: Underlying Mechanisms and the Role of Neurorehabilitation

Multiple sclerosis (MS) is a chronic, immune-mediated, inflammatory, and degenerative disease of the central nervous system (CNS) that affects both white and gray matter. Various mechanisms throughout its course, mainly regarding gray matter lesions and brain atrophy, result in cognitive network dysfunction and can cause clinically significant cognitive impairment in roughly half the persons living with MS. Altered cognition is responsible for many negative aspects of patients' lives, independently of physical disability, such as higher unemployment and divorce rates, reduced social activities, and an overall decrease in quality of life. Despite its devastating impact it is not included in clinical ratings and decision making in the way it should be. It is interesting that only half the persons with MS exhibit cognitive dysfunction, as this implies that the other half remain cognitively intact. It appears that a dynamic balance between brain destruction and brain reorganization is taking place. This balance acts in favor of keeping brain systems functioning effectively, but this is not so in all cases, and the effect does not last forever. When these systems collapse, functional brain reorganization is not effective anymore, and clinically apparent impairments are evident. It is therefore important to reveal which factors could make provision for the subpopulation of patients in whom cognitive impairment occurs. Even if we manage to detect this subpopulation earlier, effective pharmaceutical treatments will still be lacking. Nevertheless, recent evidence shows that cognitive rehabilitation and neuromodulation, using non-invasive techniques such as transcranial magnetic or direct current stimulation, could be effective in cognitively impaired patients with MS. In this Mini Review, we discuss the mechanisms underlying cognitive impairment in MS. We also focus on mechanisms of reorganization of cognitive networks, which occur throughout the disease course. Finally, we review theoretical and practical issues of neurorehabilitation and neuromodulation for cognition in MS as well as factors that influence them and prevent them from being widely applied in clinical settings.

Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis

Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.

Two-year dynamic functional network connectivity in clinically isolated syndrome

Background:

The features of functional network connectivity reorganization at the earliest stages of MS have not been investigated yet.

Objective:

To combine static and dynamic analysis of resting state (RS) functional connectivity (FC) to identify mechanisms of clinical dysfunction and recovery occurring in clinically isolated syndrome (CIS) patients.

Methods:

RS functional magnetic resonance imaging (fMRI) and clinical data were prospectively acquired from 50 CIS patients and 13 healthy controls (HC) at baseline, month 12 and month 24. Between-group differences and longitudinal evolution of network FC were analysed across 41 functionally relevant networks.

Results:

At follow-up, 47 patients developed MS. Disability remained stable (and relatively low). CIS and HC exhibited two recurring RS FC states (states 1 and 2, showing low and high internetwork connectivity, respectively). At baseline, patients showed reduced state 2 connectivity strength in the default-mode and cerebellar networks, and no differences in global dynamism versus HC. A selective FC reduction in networks affected by the clinical attack was also detected. At follow-up, increased state 2 connectivity strength and global connectivity dynamism was observed in patients versus HC.

Conclusion:

Longitudinal FC modifications occurring relatively early in the course of multiple sclerosis may represent a protective mechanism contributing to preserve clinical function over time.

Reduced dynamics of functional connectivity and cognitive impairment in multiple sclerosis

BACKGROUND

In multiple sclerosis (MS), abnormalities of brain network dynamics and their relevance for cognitive impairment have never been investigated.

OBJECTIVES

The aim of this study was to assess the dynamic resting state (RS) functional connectivity (FC) on 62 relapsing-remitting MS patients and 65 sex-matched healthy controls enrolled at 7 European sites.

METHODS

MS patients underwent clinical and cognitive evaluation. Between-group network FC differences were evaluated using a dynamic approach (based on sliding-window correlation analysis) and grouping correlation matrices into recurrent FC states.

RESULTS

Dynamic FC analysis revealed, in healthy controls and MS patients, three recurrent FC states: two characterized by strong intra- and inter-network connectivity and one characterized by weak inter-network connectivity (State 3). A total of 23 MS patients were cognitively impaired (CI). Compared to cognitively preserved (CP), CI-MS patients had reduced RS-FC between subcortical and default-mode networks in the low-connectivity State 3 and lower dwell time (i.e. time spent in a given state) in the high-connectivity State 2. CI-MS patients also exhibited a lower number and a less frequent switching between meta-states, as well as a smaller distance traveled through connectivity states.

CONCLUSION

Time-varying RS-FC was markedly less dynamic in CI- versus CP-MS patients, suggesting that slow inter-network connectivity contributes to cognitive dysfunction in MS.

Rationale and design of a single-blind, randomised controlled trial of exercise training for managing learning and memory impairment in persons with multiple sclerosis

INTRODUCTION

This randomised controlled trial (RCT) examines treadmill walking exercise training effects on learning and memory performance, hippocampal volume, and hippocampal resting-state functional connectivity in persons with multiple sclerosis (MS) who have objective impairments in learning new information.

METHODS AND ANALYSIS

Forty fully ambulatory persons with MS who demonstrate objective learning and memory impairments will be randomly assigned into either the intervention or active control study conditions. The intervention condition involves supervised, progressive treadmill walking exercise training three times per week for a 3-month period. The active control condition involves supervised, progressive low-intensity resistive exercise that will be delivered at the same frequency as the intervention condition. The primary outcome will involve composite performance on neuropsychological learning and memory tests, and the secondary outcomes involve MRI measures of hippocampal volume and resting-state functional connectivity administered before and after the 3-month study period. Outcomes will be administered by treatment-blinded assessors using alternate test forms to minimise practice effects, and MRI data processing will be performed by blinded data analysts.

ETHICS AND DISSEMINATION

This study has been approved by a university institutional review board. The primary results will be disseminated via peer-reviewed publications and the final data will be made available to third parties in applicable data repositories. If successful, the results from this study will eventually inform subsequent RCTs for developing physical rehabilitation interventions (ie, treadmill walking exercise training) for improving learning and memory and its relationship with hippocampal outcomes in larger samples of cognitively impaired persons with MS. The results from this early-phase RCT will further lay preliminary groundwork for ultimately providing clinicians and patients with guidelines for better using chronic treadmill walking exercise for improving cognition and brain health. This approach is paramount as learning and memory impairment is common, burdensome and poorly managed in MS.

TRIAL REGISTRATION NUMBER

NCT03319771; Pre-results.

Dynamic Functional Connectivity and Symptoms of Parkinson's Disease: A Resting-State fMRI Study

Research has shown that dynamic functional connectivity (dFC) in Parkinson’s disease (PD) is associated with better attention performance and with motor symptom severity. In the current study, we aimed to investigate dFC of both the default mode network (DMN) and the frontoparietal network (FPN) as neural correlates of cognitive functioning in patients with PD. Additionally, we investigated pain and motor problems as symptoms of PD in relation to dFC. Twenty-four PD patients and 27 healthy controls participated in this study. Memory and executive functioning were assessed with neuropsychological tests. Pain was assessed with the Numeric Rating Scale (NRS); motor symptom severity was assessed with the Unified Parkinson’s Disease Rating Scale (UPDRS). All subjects underwent resting-state functional magnetic resonance imaging (fMRI), from which dFC was defined by calculating the variability of functional connectivity over a number of sliding windows within each scan. dFC of both the DMN and FPN with the rest of the brain was calculated. Patients performed worse on tests of visuospatial memory, verbal memory and working memory. No difference existed between groups regarding dFC of the DMN nor the FPN with the rest of the brain. A positive correlation existed between dFC of the DMN and visuospatial memory. Our results suggest that dynamics during the resting state are a neural correlate of visuospatial memory in PD patients. Furthermore, we suggest that brain dynamics of the DMN, as measured with dFC, could be a phenomenon specifically linked to cognitive functioning in PD, but not to other symptoms.

Information processing speed in multiple sclerosis: Relevance of default mode network dynamics

Objective

To explore the added value of dynamic functional connectivity (dFC) of the default mode network (DMN) during resting-state (RS), during an information processing speed (IPS) task, and the within-subject difference between these conditions, on top of conventional brain measures in explaining IPS in people with multiple sclerosis (pwMS).

Methods

In 29 pwMS and 18 healthy controls, IPS was assessed with the Letter Digit Substitution Test and Stroop Card I and combined into an IPS-composite score. White matter (WM), grey matter (GM) and lesion volume were measured using 3 T MRI. WM integrity was assessed with diffusion tensor imaging. During RS and task-state fMRI (i.e. symbol digit modalities task, IPS), stationary functional connectivity (sFC; average connectivity over the entire time series) and dFC (variation in connectivity using a sliding window approach) of the DMN was calculated, as well as the difference between both conditions (i.e. task-state minus RS; ΔsFC-DMN and ΔdFC-DMN). Regression analysis was performed to determine the most important predictors for IPS.

Results

Compared to controls, pwMS performed worse on IPS-composite (p = 0.022), had lower GM volume (p < 0.05) and WM integrity (p < 0.001), but no alterations in sFC and dFC at the group level. In pwMS, 52% of variance in IPS-composite could be predicted by cortical volume (β = 0.49, p = 0.01) and ΔdFC-DMN (β = 0.52, p < 0.01). After adding dFC of the DMN to the model, the explained variance in IPS increased with 26% (p < 0.01).

Conclusion

On top of conventional brain measures, dFC from RS to task-state explains additional variance in IPS. This highlights the potential importance of the DMN to adapt upon cognitive demands to maintain intact IPS in pwMS.

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Problems with information processing speed occur often in multiple sclerosis (MS)

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Dynamics in brain communication can reflect information transfer within the brain

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With fMRI, dynamic communication can be measured, which increases upon task demands

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This increase in dynamics explains information processing speed in MS