Imaging resting state brain function in multiple sclerosis

Influence of natalizumab on resting-state connectivity in patients with multiple sclerosis

Background

Changes in brain connectivity occur in patients with multiple sclerosis (MS), even in patients under disease-modifying therapies. Using magnetic resonance imaging (MRI) to asses patients treated with disease-modifying therapies, such as natalizumab, can elucidate the mechanisms involved in clinical deterioration in MS.

Objectives

To evaluate differences in resting-state functional connectivity among MS patients treated with natalizumab, MS patients not treated with natalizumab, and controls.

Design

Single-center retrospective cross-sectional study.

Methods

Twenty-three MS patients being treated with natalizumab were retrospectively compared with 23 MS patients who were naïve for natalizumab, and were using first-line medications (interferon-β and/or glatiramer acetate), and 17 gender- and age-matched control subjects. The MS patient groups were also matched for time since diagnosis and hyperintense lesion volume on FLAIR. All participants underwent brain MRI using a 3 Tesla scanner. Independent component analysis and dual regression were used to identify resting-state functional connectivity using the FMRIB Software Library.

Results

In comparison to controls, the MS patients treated with natalizumab presented decreased connectivity in the left orbitofrontal cortex, in the anterior cingulate and orbitofrontal cortex network. The patients not treated with natalizumab presented increased connectivity in the secondary visual, sensorimotor, and ventral attention networks in comparison to controls.Compared to patients treated with natalizumab, the patients not using natalizumab presented increased connectivity in the left Heschl's gyrus and in the right superior frontal gyrus in the ventral attention network.

Conclusion

Differences in brain connectivity between MS patients not treated with natalizumab, healthy controls, and patients treated with natalizumab may be secondary to suboptimal neuronal compensation due to prior less efficient treatments, or due to a compensation in response to maladaptive plasticity.

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.

Resting-State Functional Connectivity in Relapsing-Remitting Multiple Sclerosis with Mild Disability: A Data-Driven, Whole-Brain Multivoxel Pattern Analysis Study

Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.

Increased flexibility of brain dynamics in patients with multiple sclerosis

Patients with multiple sclerosis consistently show widespread changes in functional connectivity. Yet, alterations are heterogeneous across studies, underscoring the complexity of functional reorganization in multiple sclerosis. Here, we aim to provide new insights by applying a time-resolved graph-analytical framework to identify a clinically relevant pattern of dynamic functional connectivity reconfigurations in multiple sclerosis. Resting-state data from 75 patients with multiple sclerosis (N = 75, female:male ratio of 3:2, median age: 42.0 ± 11.0 years, median disease duration: 6 ± 11.4 years) and 75 age- and sex-matched controls (N = 75, female:male ratio of 3:2, median age: 40.2 ± 11.8 years) were analysed using multilayer community detection. Local, resting-state functional system and global levels of dynamic functional connectivity reconfiguration were characterized using graph-theoretical measures including flexibility, promiscuity, cohesion, disjointedness and entropy. Moreover, we quantified hypo- and hyper-flexibility of brain regions and derived the flexibility reorganization index as a summary measure of whole-brain reorganization. Lastly, we explored the relationship between clinical disability and altered functional dynamics. Significant increases in global flexibility (t = 2.38, P_FDR = 0.024), promiscuity (t = 1.94, P_FDR = 0.038), entropy (t = 2.17, P_FDR = 0.027) and cohesion (t = 2.45, P_FDR = 0.024) were observed in patients and were driven by pericentral, limbic and subcortical regions. Importantly, these graph metrics were correlated with clinical disability such that greater reconfiguration dynamics tracked greater disability. Moreover, patients demonstrate a systematic shift in flexibility from sensorimotor areas to transmodal areas, with the most pronounced increases located in regions with generally low dynamics in controls. Together, these findings reveal a hyperflexible reorganization of brain activity in multiple sclerosis that clusters in pericentral, subcortical and limbic areas. This functional reorganization was linked to clinical disability, providing new evidence that alterations of multilayer temporal dynamics play a role in the manifestation of multiple sclerosis.

Good Visual Outcomes After Pituitary Tumor Surgery Are Associated With Increased Visual Cortex Functional Connectivity

BACKGROUND

Patients presenting with visual impairment secondary to pituitary macroadenomas often experience variable recovery after surgery. Several factors may impact visual outcomes including the extent of neuroaxonal damage in the afferent visual pathway and cortical plasticity. Optical coherence tomography (OCT) measures of retinal structure and resting-state functional MRI (rsfMRI) can be used to evaluate the impact of neuroaxonal injury and cortical adaptive processes, respectively. The purpose of this study was to determine whether rsfMRI patterns of functional connectivity (FC) distinguish patients with good vs poor visual outcomes after surgical decompression of pituitary adenomas.

METHODS

In this retrospective cohort study, we compared FC patterns between patients who manifested good (GO) vs poor (PO) visual outcomes after pituitary tumor surgery. Patients (n = 21) underwent postoperative rsfMRI a minimum of 1 year after tumor surgery. Seed-based connectivity of the visual cortex (primary [V1], prestriate [V2], and extrastriate [V5]) was compared between GO and PO patients and between patients and healthy controls (HCs) (n = 19). Demographics, visual function, and OCT data were compared preoperatively and postoperatively between patient groups. The threshold for GO was visual field mean deviation equal or less than -5.00 dB and/or visual acuity equal to or better than 20/40.

RESULTS

Increased postoperative FC of the visual system was noted for GO relative to PO patients. Specifically, good visual outcomes were associated with increased connectivity of right V5 to the bilateral frontal cortices. Compared with HCs, GO patients showed increased connectivity of V1 and left V2 to sensorimotor cortex, increased connectivity of right and left V2 to medial prefrontal cortex, and increased connectivity of right V5 the right temporal and frontal cortices.

CONCLUSIONS

Increased visual cortex connectivity is associated with good visual outcomes in patients with pituitary tumor, at late phase of recovery. Our findings suggest that rsfMRI does distinguish GO and PO patients after pituitary tumor surgery. This imaging modality may have a future role in characterizing the impact of cortical adaptation on visual recovery.

Mechanisms of Network Changes in Cognitive Impairment in Multiple Sclerosis

Background and Objectives

Cognitive impairment in multiple sclerosis (MS) is associated with functional connectivity abnormalities. While there have been calls to use functional connectivity measures as biomarkers, there remains to be a full understanding of why they are affected in MS. In this cross-sectional study, we tested the hypothesis that functional network regions may be susceptible to disease-related “wear and tear” and that this can be observable on co-occurring abnormalities on other magnetic resonance metrics. We tested whether functional connectivity abnormalities in cognitively impaired patients with MS co-occur with (1) overlapping, (2) local, or (3) distal changes in anatomic connectivity and cerebral blood flow abnormalities.

Methods

Multimodal 3T MRI and assessment with the Brief Repeatable Battery of Neuropsychological tests were performed in 102 patients with relapsing-remitting MS and 27 healthy controls. Patients with MS were classified as cognitively impaired if they scored ≥1.5 SDs below the control mean on ≥2 tests (n = 55) or as cognitively preserved (n = 47). Functional connectivity was assessed with Independent Component Analysis and dual regression of resting-state fMRI images. Cerebral blood flow maps were estimated, and anatomic connectivity was assessed with anatomic connectivity mapping and fractional anisotropy of diffusion-weighted MRI. Changes in cerebral blood flow and anatomic connectivity were assessed within resting-state networks that showed functional connectivity abnormalities in cognitively impaired patients with MS.

Results

Functional connectivity was significantly decreased in the anterior and posterior default mode networks and significantly increased in the right and left frontoparietal networks in cognitively impaired relative to cognitively preserved patients with MS (threshold-free cluster enhancement corrected at p ≤ 0.05, 2 sided). Networks showing functional abnormalities showed altered cerebral blood flow and anatomic connectivity locally and distally but not in overlapping locations.

Discussion

We provide the first evidence that functional connectivity abnormalities are accompanied by local cerebral blood flow and structural connectivity abnormalities but also demonstrate that these effects do not occur in exactly the same location. Our findings suggest a possibly shared pathologic mechanism for altered functional connectivity in brain networks in MS.

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.

Primary visual cortex of the brain is associated with optic nerve head changes in neuromyelitis optica spectrum disorders

OBJECTIVE

To explore the association between the primary visual cortex in the brain and optic nerve head changes, ONH, (structural thickness and microvascular changes) in neuromyelitis optica spectrum disorder (NMOSD).

METHODS

Nineteen patients who were aquaporin-4 (AQP-4) seropositive NMOSD patients and twenty-two healthy controls (HC) were enrolled for this cross-sectional study. Optical coherence tomographic angiography (OCT-A) was used to image and measure the capillaries density (RPC, radial peripapillary capillaries) and structural thickness (pRNFL, peripapillary retinal nerve fiber layer) around the optic nerve head. A resting-state functional magnetic resonance imaging was used to image and evaluate the gray matter volume (GMV) and functional connectivity (FC) the brain of each participant. We assessed the primary visual cortex (lingual gyrus, calcarine sulcus and thalamus) of the brain.

RESULTS

Changes in RPC density showed a significant association (P < 0.05) with FC of the right lingual gyrus, bilateral calcarine gyrus and left thalamus respectively. pRNFL thickness showed significant association with FC of the right lingual gyrus (Rho = 0.374, P = 0.016), right calcarine gyrus (Rho = 0.355, P = 0.023) and left thalamus (Rho = 0.376, P = 0.015) respectively.

CONCLUSIONS

Visual impairment, structural and microvascular changes around optic nerve head is associated with the functional visual networks in NMOSD. Our report suggests that structural and microvascular changes around the ONH reflect the changes in the primary visual cortex of the brain.

Altered structural and functional connectivity in CSF1R-related leukoencephalopathy

CSF1R-related leukoencephalopathy is a rare white-matter encephalopathy characterized by motor and neuropsychiatric symptoms due to colony-stimulating factor 1 receptor (CSF1R) gene mutation. Few studies have investigated the intrinsic brain alternations of patients with CSF1R-related leukoencephalopathy. We aim to evaluate the structural and functional changes in those patients. Seven patients with CSF1R-related leukoencephalopathy and 15 age-matched healthy controls (HCs) underwent multimodal magnetic resonance imaging (MRI), including high-resolution T1-weighted imaging, T2-weighted fluid attenuated inversion recovery imaging, diffusion-weighted imaging, diffusion kurtosis imaging (DKI) and resting-state functional MRI. First, to detect structural alterations, the gray matter volumes were compared using voxel-based morphometry analyses. Second, DKI parametric maps were used to evaluate the white matter (WM) connectivity changes. Finally, we constructed a seed-based resting-state functional connectivity matrix based on 90 regions of interest and examined the functional network changes of CSF1R-related leukoencephalopathy. Unlike the HCs, patients with CSF1R-related leukoencephalopathy predominantly had morphological atrophy in the bilateral thalamus and left hippocampus. In addition, the abnormal diffusivity was mainly distributed in the splenium of the corpus callosum, periventricular regions, centrum semiovale, subcortical U-fibers and midline cortex structures. Moreover, the patients had significantly reduced functional connectivity between the bilateral caudate nucleus and their contralateral hippocampus. Therefore, in addition to hyperintensity on the T2-weighted images, CSF1R-related leukoencephalopathy also showed abnormal structural and functional alterations, including subcortical atrophy and reduced functional connectivity, as well as altered diffuse parameters in the WM and subcortical regions. These findings expand our understanding of the potential pathophysiologic mechanism behind this hereditary disease.

Blood Oxygenation Level-Dependent Response to Multiple Grip Forces in Multiple Sclerosis: Going Beyond the Main Effect of Movement in Brodmann Area 4a and 4p

This study highlights the importance of looking beyond the main effect of movement to study alterations in functional response in the presence of central nervous system pathologies such as multiple sclerosis (MS). Data show that MS selectively affects regional BOLD (blood oxygenation level dependent) responses to variable grip forces (GF). It is known that the anterior and posterior BA 4 areas (BA 4a and BA 4p) are anatomically and functionally distinct. It has also been shown in healthy volunteers that there are linear (first order, typical of BA 4a) and nonlinear (second to fourth order, typical of BA 4p) BOLD responses to different levels of GF applied during a dynamic motor paradigm. After modeling the BOLD response with a polynomial expansion of the applied GFs, the particular case of BA 4a and BA 4p were investigated in healthy volunteers (HV) and MS subjects. The main effect of movement (zeroth order) analysis showed that the BOLD signal is greater in MS compared with healthy volunteers within both BA 4 subregions. At higher order, BOLD-GF responses were similar in BA 4a but showed a marked alteration in BA 4p of MS subjects, with those with greatest disability showing the greatest deviations from the healthy response profile. Therefore, the different behaviors in HV and MS could only be uncovered through a polynomial analysis looking beyond the main effect of movement into the two BA 4 subregions. Future studies will investigate the source of this pathophysiology, combining the present fMRI paradigm with blood perfusion and nonlinear neuronal response analysis.

Acquisition Duration in Resting-State Arterial Spin Labeling. How Long Is Enough?

Resting-state Arterial Spin Labeling (rs-ASL) is a rather confidential method compared to resting-state BOLD. As ASL allows to quantify the cerebral blood flow, unlike BOLD, rs-ASL can lead to significant clinical subject-scaled applications. Despite directly impacting clinical practicability and functional networks estimation, there is no standard for rs-ASL regarding the acquisition duration. Our work here focuses on assessing the feasibility of ASL as an rs-fMRI method and on studying the effect of the acquisition duration on the estimation of functional networks. To this end, we acquired a long 24 min 30 s rs-ASL sequence and investigated how estimations of six typical functional brain networks evolved with respect to the acquisition duration. Our results show that, after a certain acquisition duration, the estimations of all functional networks reach their best and are stabilized. Since, for clinical application, the acquisition duration should be the shortest possible, we suggest an acquisition duration of 14 min, i.e., 240 volumes with our sequence parameters, as it covers the functional networks estimation stabilization.

Altered resting-state functional connectivity density in patients with neuromyelitis optica-spectrum disorders

BACKGROUND

Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune, demyelinating disorder, accompanied by abnormal spontaneous activity of the brain and impairment of the retina and optic nerve. Functional connectivity density (FCD) map, a graph theory method, was applied to explore the functional connectivity alterations of brian in NMOSD patients and investigate the alterations of FCD to the structural and microvascular changes around the optic nerve head (ONH).

METHODS

Nineteen NMOSD patients and 22 healthy controls (HCs) were included in our study. All participants underwent resting-state functional magnetic resonance imaging (fMRI) scans of the brain, and ophthalmological examinations included optical coherence tomographic angiography (OCT-A) imaging, visual acuity (VA), and intraocular pressure (IOP). The long- and short-range FCD was calculated by the fMRI graph theory method and two-sample t-tests were performed to compare the discrepancy of FCD between NMOSD and HCs. OCT-A imaging was used to obtain the structure (peripapillary retinal nerve fiber layer, pRNFL) and microvessels (radial peripapillary capillary, RPC) details around the ONH. The association between the long- and short-range FCD values with the structural and microvascular variation around the ONH were evaluated using Spearman's correlation.

RESULTS

Significantly decreased (corrected p < 0.05) long-range FCD was seen in the right superior parietal gyrus (SPG) in patients with NMOSD when compared to HCs. Increased long-range FCD was seen in the right fusiform gyrus (FFG), left orbital part of superior frontal orbital gyrus (ORBsup) and left anterior cingulum and paracingulate gyri (ACG) in NMOSD patients (corrected p < 0.05). The regions with reduced short-range FCD in NMOSD were the left angular gyrus (ANG) and right SPG (corrected p < 0.05). Increased short-range FCD was shown (corrected p < 0.05) in the right FFG of NMOSD. The pRNFL thickness and RPC density in all participants were negatively correlated with the long-range FCD values in the right FFG, left ORBsup, and left ACG as well as short-range FCD values in the right FFG, besides, both were positively correlated with the long-range FCD values in the right SPG and short-range FCD values in the left ANG and right SPG (p < 0.05).

CONCLUSION

Our study demonstrates that patients with NMOSD have widespread brain dysfunction after optic neuritis attacks which shows as impairment of widespread spatial distribution in long- and short-range FCD. Structural and microvascular changes around the ONH are associated with neural changes in the brain.

Alterations in the Brain Structure and Functional Connectivity in Aquaporin-4 Antibody-Positive Neuromyelitis Optica Spectrum Disorder

Purpose

To investigate the mechanisms underlying the gray matter volume (GMV) and functional connectivity (FC) changes in aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (NMOSD) patients.

Methods

This cross-sectional study consisted of 21 patients with aquaporin-4 antibody-positive NMOSD and 22 age- and sex-matched healthy controls. All participants underwent cerebral magnetic resonance imaging and testing each individual’s visual acuity was done.

Results

Neuromyelitis optica spectrum disorder patients showed significantly reduced GMV in the left calcarine, left thalamus and right lingual gyrus of the NMOSD patients when compared to HC (P < 0.05). NMOSD patients showed significantly decreased FC values (P < 0.05) in both the left and right calcarine, right lingual gyrus and left thalamus, respectively, when compared to HC. We also observed a positive correlation between the FC values of the left thalamus, bilateral calcarine gyrus and the visual acuity, respectively (P < 0.05). Furthermore, a negative association was seen between the duration of the disease, frequency of optic neuritis, and the FC values in the lingual gyrus, bilateral calcarine gyrus, and right lingual gyrus, respectively (P < 0.05).

Conclusion

Reduced visual acuity and frequency of optic neuritis are associated with alterations in the GMV and FC in NMOSD. Our current study, which provides imaging evidence on the impairment involved in NMOSD, sheds light on pathophysiological responses of optic neuritis attack on the brain especially on the visual network.

Fatigue in multiple sclerosis is associated with multimodal interoceptive abnormalities

BACKGROUND

Fatigue ranks among the most common and disabling symptoms in multiple sclerosis (MS). Recent theoretical works have surmised that this trait might be related to alterations across interoceptive mechanisms. However, this hypothesis has not been empirically evaluated.

OBJECTIVES

To determine whether fatigue in MS patients is associated with specific behavioral, structural, and functional disruptions of the interoceptive domain.

METHODS

Fatigue levels were established via the Modified Fatigue Impact Scale. Interoception was evaluated through a robust measure indexed by the heartbeat detection task. Structural and functional connectivity properties of key interoceptive hubs were tested by magnetic resonance imaging (MRI) and resting-state functional MRI. Machine learning analyses were employed to perform pairwise classifications.

RESULTS

Only patients with fatigue presented with decreased interoceptive accuracy alongside decreased gray matter volume and increased functional connectivity in core interoceptive regions, the insula, and the anterior cingulate cortex. Each of these alterations was positively associated with fatigue. Finally, machine-learning analysis with a combination of the above interoceptive indices (behavioral, structural, and functional) successfully discriminated (area under the curve > 90%) fatigued patients from both non-fatigued and healthy controls.

CONCLUSION

This study offers unprecedented evidence suggesting that disruptions of neurocognitive markers subserving interoception may constitute a signature of fatigue in MS.

Morphological MRI phenotypes of multiple sclerosis differ in resting-state brain function

We aimed to assess differences in resting-state functional connectivity (FC) between distinct morphological MRI-phenotypes in multiple sclerosis (MS). Out of 180 MS patients, we identified those with high T2-hyperintense lesion load (T2-LL) and high normalized brain volume (NBV; a predominately white matter damage group, WMD; N = 37) and patients with low T2-LL and low NBV (N = 37; a predominately grey matter damage group; GMD). Independent component analysis of resting-state fMRI was used to test for differences in the sensorimotor network (SMN) between MS MRI-phenotypes and compared to 37 age-matched healthy controls (HC). The two MS groups did not differ regarding EDSS scores, disease duration and distribution of clinical phenotypes. WMD compared to GMD patients showed increased FC in all sub-units of the SMN (sex- and age-corrected). WMD patients had increased FC compared to HC and GMD patients in the central SMN (leg area). Only in the WMD group, higher EDSS scores and T2-LL correlated with decreased connectivity in SMN sub-units. MS patients with distinct morphological MRI-phenotypes also differ in brain function. The amount of focal white matter pathology but not global brain atrophy affects connectivity in the central SMN (leg area) of the SMN, consistent with the notion of a disconnection syndrome.

A Neuropsychological Rehabilitation Program for Cognitive Impairment in Psychiatric and Neurological Conditions: A Review That Supports Its Efficacy

Neuropsychological rehabilitation has been the focus of much scientific research over the past decades due to its efficacy in different pathologies. Advances in the neuropsychology field have led to improvements and changes in neuropsychological interventions, which in turn have given rise to different approaches and rehabilitation programs. REHACOP is an integrative neuropsychological rehabilitation program designed by specialist neuropsychologists. With an integrated bottom-up and top-down approach, REHACOP includes neurocognition, social cognition, and daily living tasks hierarchically organized on an increasing level of difficulty. Task arrangement is addressed to maximize improvements and transfer effects into participant's daily living. To date, REHACOP has been implemented on different clinical samples such as patients with schizophrenia, multiple sclerosis (MS), and Parkinson's disease (PD). This manuscript presents the efficacy data of REHACOP across these three populations and discusses it in the context of the available literature. Overall, the magnitude of improvements obtained by means of REHACOP ranged from medium to high across samples. These changes were not restricted to specific neurocognitive domains since participants attending the REHACOP program also showed changes in social cognition and daily functioning variables by means of both direct and transfer effects. Results regarding REHACOP's efficacy in psychiatric and neurological conditions have contributed to expanding the existing evidence about the use of structured neuropsychological rehabilitation. In addition, the results obtained after its implementation highlighted the need and importance of designing and implementing integrative neuropsychological rehabilitation programs that are focused not only on cognition per se but also on participants' performance in daily living.

Association of Visual Impairment in Neuromyelitis Optica Spectrum Disorder With Visual Network Reorganization

Importance

Severe visual impairment is one of the major symptoms in neuromyelitis optica spectrum disorder (NMOSD), but functional network reorganization induced by the diminished sensory input has not been investigated thus far.

Objective

To examine adaptive visual network connectivity changes in NMOSD.

Design, Setting, and Participants

In this cross-sectional study, data were collected from May 1, 2013, through February 31, 2016, from 31 patients with aquaporin-4 antibody-positive NMOSD and 31 age- and sex-matched healthy control individuals at the Department of Neurology and NeuroCure Clinical Research Center at Charité-Universitätsmedizin Berlin, Berlin, Germany.

Main Outcomes and Measures

Visual function (high-contrast visual acuity and contrast sensitivity), optical coherence tomography (peripapillary retinal nerve fiber layer and ganglion cell layer thickness), and resting-state functional magnetic resonance imaging (functional connectivity of large-scale brain networks).

Results

Thirty-one patients with NMOSD (mean [SD] age, 48.2 [13.9] years; 28 women and 3 men) and 31 healthy controls (mean [SD] age, 47.2 [15.3] years; 28 women and 3 men) participated in the study. Patients had a selective and pronounced increase of functional connectivity in the primary and secondary visual networks. Increased primary visual network connectivity correlated with reduced high-contrast visual acuity (r = -0.39, P = .006), reduced low-contrast sensitivity (r = -0.33, P = .03), and more severe retinal damage measured by optical coherence tomography (r = -0.4, P = .01). Furthermore, visual functional connectivity was significantly higher in patients with a history of optic neuritis compared with patients without optic neuritis (mean [SD] regression coefficients, 50.0 [4.3] vs 34.6 [5.6]; P = .04).

Conclusions and Relevance

Impaired visual function and retinal damage are associated with selective reorganization of the visual network in NMOSD. These findings advance the understanding of visual system dysfunction in NMOSD and, more generally, provide insight into pathophysiologic responses of the visual system to impaired visual input.

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.

Imaging functional motor connectivity in hemiparetic children with perinatal stroke

Perinatal stroke causes lifelong disability, particularly hemiparetic cerebral palsy. Arterial ischemic strokes (AIS) are large, cortical, and subcortical injuries acquired near birth due to acute occlusion of the middle cerebral artery. Periventricular venous infarctions (PVI) are smaller, subcortical strokes acquired prior to 34 weeks gestation involving injury to the periventricular white matter. Both stroke types can damage motor pathways, thus, we investigated resulting alterations in functional motor networks and probed function. We measured blood oxygen level dependent (BOLD) fluctuations at rest in 38 participants [10 arterial patients (age = 14.7 ± 4.1 years), 10 venous patients (age = 13.5 ± 3.7 years), and 18 typically developing controls (TDCs) (age = 15.3 ± 5.1 years)] and explored strength and laterality of functional connectivity in the motor network. Inclusion criteria included MRI-confirmed, unilateral perinatal stroke, symptomatic hemiparetic cerebral palsy, and 6-19 years old at time of imaging. Seed-based functional connectivity analyses measured temporal correlations in BOLD response over the whole brain using primary motor cortices as seeds. Laterality indices based on mean z-scores in lesioned and nonlesioned hemispheres explored laterality. In AIS patients, significant differences in both strength and laterality of motor network connections were observed compared with TDCs. In PVI patients, motor networks largely resembled those of healthy controls, albeit slightly weaker and asymmetric, despite subcortical damage and hemiparesis. Functional connectivity strengths were not related to motor outcome scores for either stroke group. This study serves as a foundation to better understand how resting-state fMRI can assess motor functional connectivity and potentially be applied to explore mechanisms of interventional therapies after perinatal stroke.

Characterization of relapsing-remitting multiple sclerosis patients using support vector machine classifications of functional and diffusion MRI data

Multiple Sclerosis patients' clinical symptoms do not correlate strongly with structural assessment done with traditional magnetic resonance images. However, its diagnosis and evaluation of the disease's progression are based on a combination of this imaging analysis complemented with clinical examination. Therefore, other biomarkers are necessary to better understand the disease. In this paper, we capitalize on machine learning techniques to classify relapsing-remitting multiple sclerosis patients and healthy volunteers based on machine learning techniques, and to identify relevant brain areas and connectivity measures for characterizing patients. To this end, we acquired magnetic resonance imaging data from relapsing-remitting multiple sclerosis patients and healthy subjects. Fractional anisotropy maps, structural and functional connectivity were extracted from the scans. Each of them were used as separate input features to construct support vector machine classifiers. A fourth input feature was created by combining structural and functional connectivity. Patients were divided in two groups according to their degree of disability and, together with the control group, three group pairs were formed for comparison. Twelve separate classifiers were built from the combination of these four input features and three group pairs. The classifiers were able to distinguish between patients and healthy subjects, reaching accuracy levels as high as 89% ± 2%. In contrast, the performance was noticeably lower when comparing the two groups of patients with different levels of disability, reaching levels below 63% ± 5%. The brain regions that contributed the most to the classification were the right occipital, left frontal orbital, medial frontal cortices and lingual gyrus. The developed classifiers based on MRI data were able to distinguish multiple sclerosis patients and healthy subjects reliably. Moreover, the resulting classification models identified brain regions, and functional and structural connections relevant for better understanding of the disease.

Altered neural signatures of interoception in multiple sclerosis

Multiple sclerosis (MS) patients present several alterations related to sensing of bodily signals. However, no specific neurocognitive impairment has yet been proposed as a core deficit underlying such symptoms. We aimed to determine whether MS patients present changes in interoception-that is, the monitoring of autonomic bodily information-a process that might be related to various bodily dysfunctions. We performed two studies in 34 relapsing-remitting, early-stage MS patients and 46 controls matched for gender, age, and education. In Study 1, we evaluated the heartbeat-evoked potential (HEP), a cortical signature of interoception, via a 128-channel EEG system during a heartbeat detection task including an exteroceptive and an interoceptive condition. Then, we obtained whole-brain MRI recordings. In Study 2, participants underwent fMRI recordings during two resting-state conditions: mind wandering and interoception. In Study 1, controls exhibited greater HEP modulation during the interoceptive condition than the exteroceptive one, but no systematic differences between conditions emerged in MS patients. Patients presented atrophy in the left insula, the posterior part of the right insula, and the right anterior cingulate cortex, with abnormal associations between neurophysiological and neuroanatomical patterns. In Study 2, controls showed higher functional connectivity and degree for the interoceptive state compared with mind wandering; however, this pattern was absent in patients, who nonetheless presented greater connectivity and degree than controls during mind wandering. MS patients were characterized by atypical multimodal brain signatures of interoception. This finding opens a new agenda to examine the role of inner-signal monitoring in the body symptomatology of MS.

Modulation of functional activity and connectivity by acupuncture in patients with Alzheimer disease as measured by resting-state fMRI

Acupuncture has been used in the therapy of Alzheimer disease (AD); however, its neural mechanisms are still unclear. The aim of this study is to examine the effect of acupuncture on the functional connectivity in AD by using resting-state functional magnetic resonance imaging (rs-fMRI). Twenty-eight subjects (14 AD and 14 normal controls) participated in this study. The rs-fMRI data were acquired before and after acupuncture stimulation at the acupoints of Tai chong (Liv3) and Hegu (LI4). During the baseline resting state, by using the amplitude of low-frequency fluctuations (ALFF), we found a significantly decreased or increased ALFF in the AD patients relative to the controls. These regions were located in the right superior frontal gyrus (SFG), left postcentral gyrus, subgenual cingulate cortex (SCC), right middle cingulate cortex (MCC), right inferior frontal gyrus (IFG), right hippocampus and the right inferior temporal gyrus (ITG). Then, we selected these brain regions as seeds to investigate whether regional activity and functional connectivity could be modulated by acupuncture in the AD patients. When compared to the pre-acupuncture stage, several of the above regions showed an increased or decreased ALFF after acupuncture in the AD patients. In addition, the functional connectivity between the hippocampus and the precentral gyrus showed enhancement after acupuncture in the AD patients. Finally, there were close correlations between the functional activity, connectivity and clinical performance in the AD patients. The current study confirmed that acupuncture at Tai chong (Liv3) and He gu (LI4) can modulate functional activity and connectivity of specific cognition-related regions in AD patients.

Brain tumors disrupt the resting-state connectome

Brain tumor patients often experience functional deficits that extend beyond the tumor site. While resting-state functional MRI (rsfMRI) has been used to map such functional connectivity changes in brain tumor patients, the interplay between abnormal tumor vasculature and the rsfMRI signal is still not well understood. Therefore, there is an exigent need for new tools to elucidate how the blood‑oxygenation-level-dependent (BOLD) rsfMRI signal is modulated in brain cancer. In this initial study, we explore the utility of a preclinical model for quantifying brain tumor-induced changes on the rsfMRI signal and resting-state brain connectivity. We demonstrate that brain tumors induce brain-wide alterations of resting-state networks that extend to the contralateral hemisphere, accompanied by global attenuation of the rsfMRI signal. Preliminary histology suggests that some of these alterations in brain connectivity may be attributable to tumor-related remodeling of the neurovasculature. Moreover, this work recapitulates clinical rsfMRI findings from brain tumor patients in terms of the effects of tumor size on the neurovascular microenvironment. Collectively, these results lay the foundation of a preclinical platform for exploring the usefulness of rsfMRI as a potential new biomarker in patients with brain cancer.

How changes in brain activity and connectivity are associated with motor performance in people with MS

People with multiple sclerosis (MS) exhibit pronounced changes in brain structure, activity, and connectivity. While considerable work has begun to elucidate how these neural changes contribute to behavior, the heterogeneity of symptoms and diagnoses makes interpretation of findings and application to clinical practice challenging. In particular, whether MS related changes in brain activity or brain connectivity protect against or contribute to worsening motor symptoms is unclear. With the recent emergence of neuromodulatory techniques that can alter neural activity in specific brain regions, it is critical to establish whether localized brain activation patterns are contributing to (i.e. maladaptive) or protecting against (i.e. adaptive) progression of motor symptoms. In this manuscript, we consolidate recent findings regarding changes in supraspinal structure and activity in people with MS and how these changes may contribute to motor performance. Furthermore, we discuss a hypothesis suggesting that increased neural activity during movement may be either adaptive or maladaptive depending on where in the brain this increase is observed. Specifically, we outline preliminary evidence suggesting sensorimotor cortex activity in the ipsilateral cortices may be maladaptive in people with MS. We also discuss future work that could supply data to support or refute this hypothesis, thus improving our understanding of this important topic.

Cortical geometry as a determinant of brain activity eigenmodes: Neural field analysis

Perturbation analysis of neural field theory is used to derive eigenmodes of neural activity on a cortical hemisphere, which have previously been calculated numerically and found to be close analogs of spherical harmonics, despite heavy cortical folding. The present perturbation method treats cortical folding as a first-order perturbation from a spherical geometry. The first nine spatial eigenmodes on a population-averaged cortical hemisphere are derived and compared with previous numerical solutions. These eigenmodes contribute most to brain activity patterns such as those seen in electroencephalography and functional magnetic resonance imaging. The eigenvalues of these eigenmodes are found to agree with the previous numerical solutions to within their uncertainties. Also in agreement with the previous numerics, all eigenmodes are found to closely resemble spherical harmonics. The first seven eigenmodes exhibit a one-to-one correspondence with their numerical counterparts, with overlaps that are close to unity. The next two eigenmodes overlap the corresponding pair of numerical eigenmodes, having been rotated within the subspace spanned by that pair, likely due to second-order effects. The spatial orientations of the eigenmodes are found to be fixed by gross cortical shape rather than finer-scale cortical properties, which is consistent with the observed intersubject consistency of functional connectivity patterns. However, the eigenvalues depend more sensitively on finer-scale cortical structure, implying that the eigenfrequencies and consequent dynamical properties of functional connectivity depend more strongly on details of individual cortical folding. Overall, these results imply that well-established tools from perturbation theory and spherical harmonic analysis can be used to calculate the main properties and dynamics of low-order brain eigenmodes.

Fatigue in multiple sclerosis: The contribution of resting-state functional connectivity reorganization

OBJECTIVES

To investigate resting-state functional connectivity (RS-FC) of the default-mode network (DMN) and of sensorimotor network (SMN) network in relapsing remitting (RR) multiple sclerosis (MS) patients with fatigue (F) and without fatigue(NF).

METHODS

In all, 59 RRMS patients and 29 healthy controls (HC) underwent magnetic resonance imaging (MRI) protocol including resting-state fMRI (RS-fMRI). Functional connectivity of the DMN and SMN was evaluated by independent component analysis (ICA). A linear regression analysis was performed to explore whether fatigue was mainly driven by changes observed in the DMN or in the SMN. Regional gray matter atrophy was assessed by voxel-based morphometry (VBM).

RESULTS

Compared to HC, F-MS patients showed a stronger RS-FC in the posterior cingulate cortex (PCC) and a reduced RS-FC in the anterior cingulated cortex (ACC) of the DMN. F-MS patients, compared to NF-MS patients, revealed (1) an increased RS-FC in the PCC and a reduced RS-FC in the ACC of the DMN and (2) an increased RS-FC in the primary motor cortex and in the supplementary motor cortex of the SMN. The regression analysis suggested that fatigue is mainly driven by RS-FC changes of the DMN.

CONCLUSIONS

Fatigue in RRMS is mainly associated to a functional rearrangement of non-motor RS networks.

Altered Functional Connectivity of Striatal Subregions in Patients with Multiple Sclerosis

Abnormal corticostriatal resting-state functional connectivity (rsFC) has been implicated in the neuropathology of multiple sclerosis. The striatum, a component of the basal ganglia, is involved in diverse functions including movement, cognition, emotion, and limbic information processing. However, the brain circuits of the striatal subregions contributing to the changes in rsFC in relapsing–remitting multiple sclerosis (RRMS) patients remain unknown. We used six subdivisions of the striatum in each hemisphere as seeds to investigate the rsFC of striatal subregions between RRMS patients and matched healthy controls (HCs). In addition, we also scanned a subcohort of RRMS patients after an average of 7 months to test the reliability of our findings. Compared to HCs, we found significantly increased dorsal caudal putamen (DCP) connectivity with the premotor area, dorsal lateral prefrontal cortex (DLPFC), insula, precuneus, and superior parietal lobule, and significantly increased connectivity between the superior ventral striatum and posterior cingulate cortex (PCC) in RRMS patients following both scans. Furthermore, we found significant associations between the Expanded Disability Status Scale and the rsFC of the left DCP with the DLPFC and parietal areas in RRMS patients. Our results suggest that the DCP may be a critical striatal subregion in the pathophysiology of RRMS.

The Italian Neuroimaging Network Initiative (INNI): enabling the use of advanced MRI techniques in patients with MS

Magnetic resonance imaging (MRI) is an important paraclinical tool to diagnose and monitor multiple sclerosis (MS). Conventional MRI measures lack of pathological specificity and are weakly correlated with MS clinical manifestations. Advanced MRI techniques are improving the understanding of the mechanisms underlying tissue injury, repair, and functional adaptation in MS; however, they require careful standardization. The definition of standardized methods for the collection and analysis of advanced MRI techniques is central not only to improve the understanding of disease pathophysiology and evolution, but also to generate research hypotheses, monitor treatment, increase cost-effectiveness and power of clinical trials. We promoted the Italian Neuroimaging Network Initiative (INNI), involving centers and investigators with an International recognized expertise, with the major goal to determine and validate novel MRI biomarkers to be utilized as predictors and/or outcomes in future MS studies. The INNI initiative supported the creation of a centralized repository, where advanced structural and functional MRI scans available at the participating sites, with the related clinical and neuropsychological data, are collected. These data will be used to perform research studies to identify clinical, neuropsychological and imaging biomarkers characteristics of the entire spectrum of MS. INNI will be instrumental to help to define standardized MRI and clinical protocols towards an increasing uptake of personalized interventions for people with MS at a national and international level. Upon approval of the INNI Steering Committee, the data collected in the online database will be shared with any research center detailing specific research proposals on disease pathophysiology or treatment effects.

Abnormal functional connectivity and cortical integrity influence dominant hand motor disability in multiple sclerosis: a multimodal analysis

Functional reorganization and structural damage occur in the brains of people with multiple sclerosis (MS) throughout the disease course. However, the relationship between resting-state functional connectivity (FC) reorganization in the sensorimotor network and motor disability in MS is not well understood. This study used resting-state fMRI, T1-weighted and T2-weighted, and magnetization transfer (MT) imaging to investigate the relationship between abnormal FC in the sensorimotor network and upper limb motor disability in people with MS, as well as the impact of disease-related structural abnormalities within this network. Specifically, the differences in FC of the left hemisphere hand motor region between MS participants with preserved (n = 17) and impaired (n = 26) right hand function, compared with healthy controls (n = 20) was investigated. Differences in brain atrophy and MT ratio measured at the global and regional levels were also investigated between the three groups. Motor preserved MS participants had stronger FC in structurally intact visual information processing regions relative to motor impaired MS participants. Motor impaired MS participants showed weaker FC in the sensorimotor and somatosensory association cortices and more severe structural damage throughout the brain compared with the other groups. Logistic regression analysis showed that regional MTR predicted motor disability beyond the impact of global atrophy whereas regional grey matter volume did not. More importantly, as the first multimodal analysis combining resting-state fMRI, T1-weighted, T2-weighted and MTR images in MS, we demonstrate how a combination of structural and functional changes may contribute to motor impairment or preservation in MS. Hum Brain Mapp 37:4262-4275, 2016. © 2016 Wiley Periodicals, Inc.

Reproducibility of Resting State Connectivity in Patients with Stable Multiple Sclerosis

Given increasing efforts to use resting-state fMRI (rfMRI) as a biomarker of disease progression in multiple sclerosis (MS) we here explored the reproducibility of longitudinal rfMRI over three months in patients with clinically and radiologically stable MS. To pursue this aim, two approaches were applied in nine rfMRI networks: First, the intraclass correlation coefficient (ICC 3,1) was assessed for the mean functional connectivity maps across the entire network and a region of interest (ROI). Second, the ratio of overlap between Z-thresholded connectivity maps for each network was assessed. We quantified between-session functional reproducibility of rfMRI for 20 patients with stable MS and 14 healthy controls (HC). Nine rfMRI networks (RSNs) were examined at baseline and after 3 months of follow-up: three visual RSNs, the default-mode network, sensorimotor-, auditory-, executive control, and the left and right fronto-parietal RSN. ROI analyses were constrained to thresholded overlap masks for each individual (Z>0) at baseline and follow-up.In both stable MS and HC mean functional connectivity across the entire network did not reach acceptable ICCs for several networks (ICC<0.40) but we found a high reproducibility of ROI ICCs and of the ratio of overlap. ROI ICCs of all nine networks were between 0.98 and 0.99 for HC and ranged from 0.88 to 0.99 in patients with MS, respectively. The ratio of overlap for all networks was similar for both groups, ranging from 0.60 to 0.75.Our findings attest to a high reproducibility of rfMRI networks not only in HC but also in patients with stable MS when applying ROI analysis. This supports the utility of rfMRI to monitor functional changes related to disease progression or therapeutic interventions in MS.

Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis

Brain entropy (BEN) mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI), reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS), a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS) patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS) and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS.

Multiple sclerosis

Due to its sensitivity to the different multiple sclerosis (MS)-related abnormalities, magnetic resonance imaging (MRI) has become an established tool to diagnose MS and to monitor its evolution. MRI has been included in the diagnostic workup of patients with clinically isolated syndromes suggestive of MS, and ad hoc criteria have been proposed and are regularly updated. In patients with definite MS, the ability of conventional MRI techniques to explain patients' clinical status and progression of disability is still suboptimal. Several advanced MRI-based technologies have been applied to estimate overall MS burden in the different phases of the disease. Their use has allowed the heterogeneity of MS pathology in focal lesions, normal-appearing white matter and gray matter to be graded in vivo. Recently, additional features of MS pathology, including macrophage infiltration and abnormal iron deposition, have become quantifiable. All of this, combined with functional imaging techniques, is improving our understanding of the mechanisms associated with MS evolution. In the near future, the use of ultrahigh-field systems is likely to provide additional insight into disease pathophysiology. However, the utility of advanced MRI techniques in clinical trial monitoring and in assessing individual patients' response to treatment still needs to be assessed.

Head Motion and Correction Methods in Resting-state Functional MRI

Resting-state functional magnetic resonance imaging (RS-fMRI) is used to investigate brain functional connectivity at rest. However, noise from human physiological motion is an unresolved problem associated with this technique. Following the unexpected previous result that group differences in head motion between control and patient groups caused group differences in the resting-state network with RS-fMRI, we reviewed the effects of human physiological noise caused by subject motion, especially motion of the head, on functional connectivity at rest detected with RS-fMRI. The aim of the present study was to review head motion artifact with RS-fMRI, individual and patient population differences in head motion, and correction methods for head motion artifact with RS-fMRI. Numerous reports have described new methods [e.g., scrubbing, regional displacement interaction (RDI)] for motion correction on RS-fMRI, many of which have been successful in reducing this negative influence. However, the influence of head motion could not be entirely excluded by any of these published techniques. Therefore, in performing RS-fMRI studies, head motion of the participants should be quantified with measurement technique (e.g., framewise displacement). Development of a more effective correction method would improve the accuracy of RS-fMRI analysis.

Aberrant Cross-Brain Network Interaction in Children With Attention-Deficit/Hyperactivity Disorder and Its Relation to Attention Deficits: A Multisite and Cross-Site Replication Study

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is increasingly viewed as a disorder stemming from disturbances in large-scale brain networks, yet the exact nature of these impairments in affected children is poorly understood. We investigated a saliency-based triple-network model and tested the hypothesis that cross-network interactions between the salience network (SN), central executive network, and default mode network are dysregulated in children with ADHD. We also determined whether network dysregulation measures can differentiate children with ADHD from control subjects across multisite datasets and predict clinical symptoms.

METHODS

Functional magnetic resonance imaging data from 180 children with ADHD and control subjects from three sites in the ADHD-200 database were selected using case-control design. We investigated between-group differences in resource allocation index (RAI) (a measure of SN-centered triple network interactions), relation between RAI and ADHD symptoms, and performance of multivariate classifiers built to differentiate children with ADHD from control subjects.

RESULTS

RAI was significantly lower in children with ADHD than in control subjects. Severity of inattention symptoms was correlated with RAI. Remarkably, these findings were replicated in three independent datasets. Multivariate classifiers based on cross-network coupling measures differentiated children with ADHD from control subjects with high classification rates (72% to 83%) for each dataset. A novel cross-site classifier based on training data from one site accurately (62% to 82%) differentiated children with ADHD on test data from the two other sites.

CONCLUSIONS

Aberrant cross-network interactions between SN, central executive network, and default mode network are a reproducible feature of childhood ADHD. The triple-network model provides a novel, replicable, and parsimonious systems neuroscience framework for characterizing childhood ADHD and predicting clinical symptoms in affected children.

Reproducibility and Temporal Structure in Weekly Resting-State fMRI over a Period of 3.5 Years

Resting-state functional MRI (rs-fMRI) permits study of the brain’s functional networks without requiring participants to perform tasks. Robust changes in such resting state networks (RSNs) have been observed in neurologic disorders, and rs-fMRI outcome measures are candidate biomarkers for monitoring clinical trials, including trials of extended therapeutic interventions for rehabilitation of patients with chronic conditions. In this study, we aim to present a unique longitudinal dataset reporting on a healthy adult subject scanned weekly over 3.5 years and identify rs-fMRI outcome measures appropriate for clinical trials. Accordingly, we assessed the reproducibility, and characterized the temporal structure of, rs-fMRI outcome measures derived using independent component analysis (ICA). Data was compared to a 21-person dataset acquired on the same scanner in order to confirm that the values of the single-subject RSN measures were within the expected range as assessed from the multi-participant dataset. Fourteen RSNs were identified, and the inter-session reproducibility of outcome measures—network spatial map, temporal signal fluctuation magnitude, and between-network connectivity (BNC)–was high, with executive RSNs showing the highest reproducibility. Analysis of the weekly outcome measures also showed that many rs-fMRI outcome measures had a significant linear trend, annual periodicity, and persistence. Such temporal structure was most prominent in spatial map similarity, and least prominent in BNC. High reproducibility supports the candidacy of rs-fMRI outcome measures as biomarkers, but the presence of significant temporal structure needs to be taken into account when such outcome measures are considered as biomarkers for rehabilitation-style therapeutic interventions in chronic conditions.

Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

Brain functional connectivity (FC) is defined as the coherence in the activity between cerebral areas under a task or in the resting-state (RS). By applying functional magnetic resonance imaging (fMRI), RS FC shows several patterns which define RS brain networks (RSNs) involved in specific functions, because brain function is known to depend not only on the activity within individual regions, but also on the functional interaction of different areas across the whole brain. Region-of-interest analysis and independent component analysis are the two most commonly applied methods for RS investigation. Multiple sclerosis (MS) is characterized by multiple lesions mainly affecting the white matter, determining both structural and functional disconnection between various areas of the central nervous system. The study of RS FC in MS is mainly aimed at understanding alterations in the intrinsic functional architecture of the brain and their role in disease progression and clinical impairment. In this paper, we will examine the results obtained by the application of RS fMRI in different multiple sclerosis (MS) phenotypes and the correlations of FC changes with clinical features in this pathology. The knowledge of RS FC changes may represent a substantial step forward in the MS research field, both for clinical and therapeutic purposes.

Functional connectivity changes and their relationship with clinical disability and white matter integrity in patients with relapsing–remitting multiple sclerosis

Background and objective:

To define the pathological substrate underlying disability in multiple sclerosis by evaluating the relationship of resting-state functional connectivity with microstructural brain damage, as assessed by diffusion tensor imaging, and clinical impairments.

Methods:

Thirty relapsing–remitting patients and 24 controls underwent 3T-MRI; motor abilities were evaluated by using measures of walking speed, hand dexterity and balance capability, while information processing speed was evaluated by a paced auditory serial addiction task. Independent component analysis and tract-based spatial statistics were applied to RS-fMRI and diffusion tensor imaging data using FSL software. Group differences, after dual regression, and clinical correlations were modelled with General-Linear-Model and corrected for multiple comparisons.

Results:

Patients showed decreased functional connectivity in 5 of 11 resting-state-networks (cerebellar, executive-control, medial-visual, basal ganglia and sensorimotor), changes in inter-network correlations and widespread white matter microstructural damage. In multiple sclerosis, corpus callosum microstructural damage positively correlated with functional connectivity in cerebellar and auditory networks. Moreover, functional connectivity within the medial-visual network inversely correlated with information processing speed. White matter widespread microstructural damage inversely correlated with both the paced auditory serial addiction task and hand dexterity.

Conclusions:

Despite the within-network functional connectivity decrease and the widespread microstructural damage, the inter-network functional connectivity changes suggest a global brain functional rearrangement in multiple sclerosis. The correlation between functional connectivity alterations and callosal damage uncovers a link between functional and structural connectivity. Finally, functional connectivity abnormalities affect information processing speed rather than motor abilities.

Disconnection of the hippocampus and amygdala associated with lesion load in relapsing-remitting multiple sclerosis: a structural and functional connectivity study

BACKGROUND AND PURPOSE

Little is known about the functional and structural connectivity (FC and SC) of the hippocampus and amygdala, which are two important structures involved in cognitive processes, or their involvement in relapsing-remitting multiple sclerosis (RRMS). In this study, we aimed to examine the connectivity of white-matter (WM) tracts and the synchrony of intrinsic neuronal activity in outer regions connected with the hippocampus or amygdala in RRMS patients.

PATIENTS AND METHODS

Twenty-three RRMS patients and 23 healthy subjects participated in this study. Diffusion tensor probabilistic tractography was used to examine the SC, the FC correlation coefficient (FC-CC) and combined FC strength (FCS), which was derived from the resting-state functional magnetic resonance imaging used to examine the FC, of the connection between the hippocampus or the amygdala and other regions, and the correlations of these connections with clinical markers.

RESULTS

Compared with healthy subjects, the RRMS patients showed significantly decreased SC and increased FCS of the bilateral hippocampus, and left amygdala. Their slightly increased FC-CC was positively correlated with WM tract damage in the right hippocampus (ρ=0.57, P=0.005); an increased FCS was also positively correlated with WM tract damage in the right amygdala. A relationship was observed between the WM lesion load and SC alterations, including the lg(N tracts) of the right hippocampus (ρ=-0.68, P<0.05), lg(N tracts) (ρ=-0.69, P<0.05), and fractional anisotropy (ρ=-0.68, P<0.05) and radial diffusivity of the left hippocampus (ρ=0.45, P<0.05). A relationship between WM lesion load and FCS of the left amygdale was also observed.

CONCLUSION

The concurrent increased functional connections and demyelination-related structural disconnectivity between the hippocampus or amygdala and other regions in RRMS suggest that the functional-structural relationships require further investigation.

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects.

Altered inter-subregion connectivity of the default mode network in relapsing remitting multiple sclerosis: a functional and structural connectivity study

Background and Purpose

Little is known about the interactions between the default mode network (DMN) subregions in relapsing-remitting multiple sclerosis (RRMS). This study used diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI) to examine alterations of long white matter tracts in paired DMN subregions and their functional connectivity in RRMS patients.

Methods

Twenty-four RRMS patients and 24 healthy subjects participated in this study. The fiber connections derived from DTI tractography and the temporal correlation coefficient derived from rs-fMRI were combined to examine the inter-subregion structural-functional connectivity (SC-FC) within the DMN and its correlations with clinical markers.

Results

Compared with healthy subjects, the RRMS patients showed the following: 1) significantly decreased SC and increased FC in the pair-wise subregions; 2) two significant correlations in SC-FC coupling patterns, including the positive correlation between slightly increased FC value and long white matter tract damage in the PCC/PCUN-MPFC connection, and the negative correlations between significantly increased FC values and long white matter tract damage in the PCC/PCUN-bilateral mTL connections; 3) SC alterations [log(N track) of the PCC/PCUN-left IPL, RD value of the MPFC-left IPL, FA value of the PCC/PCUN-left mTL connections] correlated with EDSS, increases in the RD value of MPFC-left IPL connection was positively correlated to the MFIS; and decreases in the FA value of PCC/PCUN-right IPL connection was negatively correlated with the PASAT; 4) decreased SC (FA value of the MPFC-left IPL, track volume of the PCC/PCUN-MPFC, and log(N track) of PCC/PCUN-left mTL connections) was positively correlated with brain atrophy.

Conclusions

In the connections of paired DMN subregions, we observed decreased SC and increased FC in RRMS patients. The relationship between MS-related structural abnormalities and clinical markers suggests that the disruption of this long-distance “inter-subregion” connectivity (white matter) may significantly impact the integrity of the network's function.

Insights from magnetic resonance imaging

Recent years have witnessed impressive advancements in the use of magnetic resonance imaging (MRI) for the assessment of patients with multiple sclerosis (MS). Complementary to the clinical evaluation, conventional MRI (cMRI) provides crucial pieces of information for the diagnosis of MS, the understanding of its natural history, and monitoring the efficacy of experimental treatments. Measures derived from cMRI present clear advantages over the clinical assessment, including their more objective nature and an increased sensitivity to MS-related changes. However, the correlation between these measures and the clinical manifestations of the disease remains weak, and this can be explained, at least partially, by the limited ability of cMRI to characterize and quantify the heterogeneous features of MS pathology. Quantitative MR-based techniques have the potential to overcome the limitations of cMRI. Magnetization transfer MRI, diffusion-weighted and diffusion tensor MRI with fiber tractography, proton magnetic resonance spectroscopy, T1 and T2 relaxation time measurement, and functional MRI are contributing to elucidate the mechanisms that underlie injury, repair, and functional adaptation in patients with MS. All conventional and nonconventional MR techniques will benefit from the use of high-field MR systems (3.0T or more).

Clinical applications of the functional connectome

Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis.

Neuroimaging biomarkers of neurodegenerative diseases and dementia

Neurodegenerative disorders leading to dementia are common diseases that affect many older and some young adults. Neuroimaging methods are important tools for assessing and monitoring pathological brain changes associated with progressive neurodegenerative conditions. In this review, the authors describe key findings from neuroimaging studies (magnetic resonance imaging and radionucleotide imaging) in neurodegenerative disorders, including Alzheimer's disease (AD) and prodromal stages, familial and atypical AD syndromes, frontotemporal dementia, amyotrophic lateral sclerosis with and without dementia, Parkinson's disease with and without dementia, dementia with Lewy bodies, Huntington's disease, multiple sclerosis, HIV-associated neurocognitive disorder, and prion protein associated diseases (i.e., Creutzfeldt-Jakob disease). The authors focus on neuroimaging findings of in vivo pathology in these disorders, as well as the potential for neuroimaging to provide useful information for differential diagnosis of neurodegenerative disorders.