Correlation between structural and functional connectivity impairment in amyotrophic lateral sclerosis

The whole-brain structural and functional connectome in Alzheimer's disease spectrum: A multimodal Bayesian meta-analysis of graph theoretical characteristics

Alzheimer's disease (AD) spectrum is increasingly recognized as a progressive network-disconnection syndrome. Neuroimaging studies using graph theoretical analysis (GTA) have reported alterations in the topological properties of whole-brain structural and functional connectomes in both preclinical AD and AD patients, though findings remain inconsistent. This study aimed to identify robust changes in multimodal GTA metrics across the AD spectrum through a comprehensive literature search and Bayesian random-effects meta-analyses. The analysis included 53 studies (17 functional and 37 structural), involving 1743 AD patients, 1502 preclinical AD patients, and 1824 healthy controls (HC). Results revealed lower structural network integration (evidenced by higher characteristic path length and/or normalized characteristic path length) and segregation (evidenced by lower clustering coefficient and local efficiency) in AD and preclinical AD patients compared to HC. Functional network segregation was also lower in AD patients, while preclinical AD showed preserved functional topology despite structural changes. Moderator analyses identified potential methodological moderators, including neuroimaging technique, node and edge definitions, and network type, although further validation is needed. These findings support the progressive disconnection hypothesis in the AD spectrum and suggest that structural network alterations may precede functional network changes. Furthermore, the results help clarify inconsistencies in previous studies and highlight the utility of graph-based metrics as biomarkers for staging AD progression.

Neuroimaging correlates of domain-specific cognitive deficits in amyotrophic lateral sclerosis

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with frequent extra-motor involvement. In the present study, we investigated whether specific cognitive and behavioral deficits in ALS correlate with distinct extra-motor neurodegeneration patterns on brain MRI.

METHODS

We performed multimodal brain MRI and Edinburgh cognitive and behavioral ALS screen (ECAS) in 293 patients and 237 controls. Follow-up data were acquired from 171 patients with a median duration of 7.9 months. Domain-level cognitive scores from the ECAS were compared with grey and white matter MRI parameters. Interaction analyses between patients and controls were performed to explore whether correlates were specific to ALS, rather than related to normal aging. Follow-up data were used to assess changes of domain-associated brain structures over time.

RESULTS

Language impairment was significantly associated with (left predominant) frontal, temporal, parietal and subcortical grey matter neurodegeneration. Letter fluency with widespread cortical and subcortical grey matter involvement. Memory dysfunction with hippocampal and medial-temporal atrophy. Executive impairment was exclusively correlated with widespread white matter impairment. Visuospatial scores did not correlate with MRI parameters. Interaction analyses between patients and controls showed that most ECAS-MRI correlations were stronger in ALS than in controls (75.7% significant in grey matter, 52.7% in white matter). Longitudinal analyses showed that all grey matter structures associated with cognitive domains worsened over time while, for this study population, ECAS domain scores did not decline significantly.

CONCLUSIONS

MRI can capture the heterogeneity of cognitive and behavioral involvement in ALS and provides a useful longitudinal biomarker for progression of extra-motor neurodegeneration.

Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)

The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.

Neuronal Circuit Dysfunction in Amyotrophic Lateral Sclerosis

The primary neural circuit affected in Amyotrophic Lateral Sclerosis (ALS) patients is the corticospinal motor circuit, originating in upper motor neurons (UMNs) in the cerebral motor cortex which descend to synapse with the lower motor neurons (LMNs) in the spinal cord to ultimately innervate the skeletal muscle. Perturbation of these neural circuits and consequent loss of both UMNs and LMNs, leading to muscle wastage and impaired movement, is the key pathophysiology observed. Despite decades of research, we are still lacking in ALS disease-modifying treatments. In this review, we document the current research from patient studies, rodent models, and human stem cell models in understanding the mechanisms of corticomotor circuit dysfunction and its implication in ALS. We summarize the current knowledge about cortical UMN dysfunction and degeneration, altered excitability in LMNs, neuromuscular junction degeneration, and the non-cell autonomous role of glial cells in motor circuit dysfunction in relation to ALS. We further highlight the advances in human stem cell technology to model the complex neural circuitry and how these can aid in future studies to better understand the mechanisms of neural circuit dysfunction underpinning ALS.

Resting-state fMRI functional connectome of C9orf72 mutation status

OBJECTIVE

The resting-state functional connectome has not been extensively investigated in amyotrophic lateral sclerosis (ALS) spectrum disease, in particular in relationship with patients' genetic status.

METHODS

Here we studied the network-to-network connectivity of 19 ALS patients carrying the C9orf72 hexanucleotide repeat expansion (C9orf72+), 19 ALS patients not affected by C9orf72 mutation (C9orf72-), and 19 ALS-mimic patients (ALSm) well-matched for demographic and clinical variables.

RESULTS

When compared with ALSm, we observed greater connectivity of the default mode and frontoparietal networks with the visual network for C9orf72+ patients (P = 0.001). Moreover, the whole-connectome showed greater node degree (P < 0.001), while sensorimotor cortices resulted isolated in C9orf72+.

INTERPRETATION

Our results suggest a crucial involvement of extra-motor functions in ALS spectrum disease. In particular, alterations of the visual cortex may have a pathogenic role in C9orf72-related ALS. The prominent feature of these patients would be increased visual system connectivity with the networks responsible of the functional balance between internal and external attention.

Structural and Functional Brain Network Connectivity at Different King's Stages in Patients With Amyotrophic Lateral Sclerosis

BACKGROUND AND OBJECTIVES

There is currently no validated disease-stage biomarker for amyotrophic lateral sclerosis (ALS). The identification of quantitative and reproducible markers of disease stratification in ALS is fundamental for study design definition and inclusion of homogenous patient cohorts into clinical trials. Our aim was to assess the rearrangements of structural and functional brain connectivity underlying the clinical stages of ALS, to suggest objective, reproducible measures provided by MRI connectomics mirroring disease staging.

METHODS

In this observational study, patients with ALS and healthy controls (HCs) underwent clinical evaluation and brain MRI on a 3T scanner. Patients were classified into 4 groups, according to the King's staging system. Structural and functional brain connectivity matrices were obtained using diffusion tensor and resting-state fMRI data, respectively. Whole-brain network-based statistics (NBS) analysis and comparisons of intraregional and inter-regional connectivity values using analysis of covariance models were performed between groups. Correlations between MRI and clinical/cognitive measures were tested using Pearson coefficient.

RESULTS

One hundred four patients with ALS and 61 age-matched and sex-matched HCs were included. NBS and regional connectivity analyses demonstrated a progressive decrease of intranetwork and internetwork structural connectivity of sensorimotor regions at increasing ALS stages in our cohort, compared with HCs. By contrast, functional connectivity showed divergent patterns between King's stages 3 (increase in basal ganglia and temporal circuits [p = 0.04 and p = 0.05, respectively]) and 4 (frontotemporal decrease [p = 0.03]), suggesting a complex interplay between opposite phenomena in late stages of the disease. Intraregional sensorimotor structural connectivity was correlated with ALS Functional Rating Scale-revised (ALSFRS-r) score (r = 0.31, p < 0.001) and upper motor neuron burden (r = -0.25, p = 0.01). Inter-regional frontal-sensorimotor structural connectivity was also correlated with ALSFRS-r (r = 0.24, p = 0.02). No correlations with cognitive measures were found.

DISCUSSION

MRI of the brain allows to demonstrate and quantify increasing disruption of structural connectivity involving the sensorimotor networks in ALS, mirroring disease stages. Frontotemporal functional disconnection seems to characterize only advanced disease phases. Our findings support the utility of MRI connectomics to stratify patients and stage brain pathology in ALS in a reproducible way, which may mirror clinical progression.

Regulation of cortical hyperexcitability in amyotrophic lateral sclerosis: focusing on glial mechanisms

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the loss of both upper and lower motor neurons, resulting in muscle weakness, atrophy, paralysis, and eventually death. Motor cortical hyperexcitability is a common phenomenon observed at the presymptomatic stage of ALS. Both cell-autonomous (the intrinsic properties of motor neurons) and non-cell-autonomous mechanisms (cells other than motor neurons) are believed to contribute to cortical hyperexcitability. Decoding the pathological relevance of these dynamic changes in motor neurons and glial cells has remained a major challenge. This review summarizes the evidence of cortical hyperexcitability from both clinical and preclinical research, as well as the underlying mechanisms. We discuss the potential role of glial cells, particularly microglia, in regulating abnormal neuronal activity during the disease progression. Identifying early changes such as neuronal hyperexcitability in the motor system may provide new insights for earlier diagnosis of ALS and reveal novel targets to halt the disease progression.

Aberrant Multimodal Connectivity Pattern Involved in Default Mode Network and Limbic Network in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that progressively affects bulbar and limb function. Despite increasing recognition of the disease as a multinetwork disorder characterized by aberrant structural and functional connectivity, its integrity agreement and its predictive value for disease diagnosis remain to be fully elucidated. In this study, we recruited 37 ALS patients and 25 healthy controls (HCs). High-resolution 3D T1-weighted imaging and resting-state functional magnetic resonance imaging were, respectively, applied to construct multimodal connectomes. Following strict neuroimaging selection criteria, 18 ALS and 25 HC patients were included. Network-based statistic (NBS) and the coupling of grey matter structural-functional connectivity (SC-FC coupling) were performed. Finally, the support vector machine (SVM) method was used to distinguish the ALS patients from HCs. Results showed that, compared with HCs, ALS individuals exhibited a significantly increased functional network, predominantly encompassing the connections between the default mode network (DMN) and the frontoparietal network (FPN). The increased structural connections predominantly involved the inter-regional connections between the limbic network (LN) and the DMN, the salience/ventral attention network (SVAN) and FPN, while the decreased structural connections mainly involved connections between the LN and the subcortical network (SN). We also found increased SC-FC coupling in DMN-related brain regions and decoupling in LN-related brain regions in ALS, which could differentiate ALS from HCs with promising capacity based on SVM. Our findings highlight that DMN and LN may play a vital role in the pathophysiological mechanism of ALS. Additionally, SC-FC coupling could be regarded as a promising neuroimaging biomarker for ALS and shows important clinical potential for early recognition of ALS individuals.

Age-Related Modifications of Electroencephalogram Coherence in Mice Models of Alzheimer's Disease and Amyotrophic Lateral Sclerosis

Evident similarities in pathological features in aging and Alzheimer's disease (AD) raise the question of a role for natural age-related adaptive mechanisms in the prevention/elimination of disturbances in interrelations between different brain areas. In our previous electroencephalogram (EEG) studies on 5xFAD- and FUS-transgenic mice, as models of AD and amyotrophic lateral sclerosis (ALS), this suggestion was indirectly confirmed. In the current study, age-related changes in direct EEG synchrony/coherence between the brain structures were evaluated.

METHODS

In 5xFAD mice of 6-, 9-, 12-, and 18-month ages and their wild-type (WT_5xFAD) littermates, we analyzed baseline EEG coherence between the cortex, hippocampus/putamen, ventral tegmental area, and substantia nigra. Additionally, EEG coherence between the cortex and putamen was analyzed in 2- and 5-month-old FUS mice.

RESULTS

In the 5xFAD mice, suppressed levels of inter-structural coherence vs. those in WT_5xFAD littermates were observed at ages of 6, 9, and 12 months. In 18-month-old 5xFAD mice, only the hippocampus ventral tegmental area coherence was significantly reduced. In 2-month-old FUS vs. WT_FUS mice, the cortex-putamen coherence suppression, dominated in the right hemisphere, was observed. In 5-month-old mice, EEG coherence was maximal in both groups.

CONCLUSION

Neurodegenerative pathologies are accompanied by the significant attenuation of intracerebral EEG coherence. Our data are supportive for the involvement of age-related adaptive mechanisms in intracerebral disturbances produced by neurodegeneration.

Motor cortex functional connectivity is associated with underlying neurochemistry in ALS

OBJECTIVE

To identify structural and neurochemical properties that underlie functional connectivity impairments of the primary motor cortex (PMC) and how these relate to clinical findings in amyotrophic lateral sclerosis (ALS).

METHODS

52 patients with ALS and 52 healthy controls, matched for age and sex, were enrolled from 5 centres across Canada for the Canadian ALS Neuroimaging Consortium study. Resting-state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy data were acquired. Functional connectivity maps, diffusion metrics and neurometabolite ratios were obtained from the analyses of the acquired multimodal data. A clinical assessment of foot tapping (frequency) was performed to examine upper motor neuron function in all participants.

RESULTS

Compared with healthy controls, the primary motor cortex in ALS showed reduced functional connectivity with sensory (T=5.21), frontal (T=3.70), temporal (T=3.80), putaminal (T=4.03) and adjacent motor (T=4.60) regions. In the primary motor cortex, N-acetyl aspartate (NAA, a neuronal marker) ratios and diffusion metrics (mean, axial and radial diffusivity, fractional anisotropy (FA)) were altered. Within the ALS cohort, foot tapping frequency correlated with NAA (r=0.347) and white matter FA (r=0.537). NAA levels showed associations with disturbed functional connectivity of the motor cortex.

CONCLUSION

In vivo neurochemistry may represent an effective imaging marker of impaired motor cortex functional connectivity in ALS.

FDG-PET shows weak correlation between focal motor weakness and brain metabolic alterations in ALS

Objective: Amyotrophic lateral sclerosis (ALS) is a clinically heterogenous disease, typically presenting with focal motor weakness that eventually generalizes. Weather there is a correlation between focal motor weakness and metabolic alterations in specific areas of the brain has not been thoroughly explored. This study aims to systematically investigate this by using fluorodeoxyglucose-positron emission tomography (FDG-PET), including longitudinal imaging. Methods: This observational imaging study included 131 ALS patients diagnosed and examined with FDG-PET at the ALS Clinical Research Center at the Karolinska University Hospital in Stockholm, Sweden. Thirteen ALS patients had a second scan and were analyzed longitudinally. The findings were compared to 39 healthy controls examined at the University Medical Center of Gröningen, the Netherlands. Results: There was a general pattern of brain metabolic alterations consistent with previously reported findings in ALS, namely hypometabolism in frontal regions and hypermetabolism in posterior regions. A higher symptom burden was associated with increased hypometabolism and decreased hypermetabolism. However, there was no clear correlation between focal motor weakness and specific metabolic alterations, neither when analyzing focal motor weakness with concomitant upper motor neuron signs or when including all focal motor weakness. Longitudinal FDG-PET imaging showed inconsistent results with little correlation between progression of motor weakness and metabolic alterations. Conclusion: Our results support the disease model of ALS as a diffuse process since no clear correlation was seen between focal motor weakness and specific metabolic alterations. However, there is need for further research on a larger number of patients, particularly including longitudinal imaging.

The human functional connectome in neurodegenerative diseases: relationship to pathology and clinical progression

INTRODUCTION

Neurodegenerative diseases can be considered as 'disconnection syndromes,' in which a communication breakdown prompts cognitive or motor dysfunction. Mathematical models applied to functional resting-state MRI allow for the organization of the brain into nodes and edges, which interact to form the functional brain connectome.

AREAS COVERED

The authors discuss the recent applications of functional connectomics to neurodegenerative diseases, from preclinical diagnosis, to follow up along with the progressive changes in network organization, to the prediction of the progressive spread of neurodegeneration, to stratification of patients into prognostic groups, and to record responses to treatment. The authors searched PubMed using the terms 'neurodegenerative diseases' AND 'fMRI' AND 'functional connectome' OR 'functional connectivity' AND 'connectomics' OR 'graph metrics' OR 'graph analysis.' The time range covered the past 20 years.

EXPERT OPINION

Considering the great pathological and phenotypical heterogeneity of neurodegenerative diseases, identifying a common framework to diagnose, monitor and elaborate prognostic models is challenging. Graph analysis can describe the complexity of brain architectural rearrangements supporting the network-based hypothesis as unifying pathogenetic mechanism. Although a multidisciplinary team is needed to overcome the limit of methodologic complexity in clinical application, advanced methodologies are valuable tools to better characterize functional disconnection in neurodegeneration.

MRI Clustering Reveals Three ALS Subtypes With Unique Neurodegeneration Patterns

OBJECTIVE

The purpose of this study was to identify subtypes of amyotrophic lateral sclerosis (ALS) by comparing patterns of neurodegeneration using brain magnetic resonance imaging (MRI) and explore their phenotypes.

METHODS

We performed T1-weighted and diffusion tensor imaging in 488 clinically well-characterized patients with ALS and 338 control subjects. Measurements of whole-brain cortical thickness and white matter connectome fractional anisotropy were adjusted for disease-unrelated variation. A probabilistic network-based clustering algorithm was used to divide patients into subgroups of similar neurodegeneration patterns. Clinical characteristics and cognitive profiles were assessed for each subgroup. In total, 512 follow-up scans were used to validate clustering results longitudinally.

RESULTS

The clustering algorithm divided patients with ALS into 3 subgroups of 187, 163, and 138 patients. All subgroups displayed involvement of the precentral gyrus and are characterized, respectively, by (1) pure motor involvement (pure motor cluster [PM]), (2) orbitofrontal and temporal involvement (frontotemporal cluster [FT]), and (3) involvement of the posterior cingulate cortex, parietal white matter, temporal operculum, and cerebellum (cingulate-parietal-temporal cluster [CPT]). These subgroups had significantly distinct clinical profiles regarding male-to-female ratio, age at symptom onset, and frequency of bulbar symptom onset. FT and CPT revealed higher rates of cognitive impairment on the Edinburgh cognitive and behavioral ALS screen (ECAS). Longitudinally, clustering remained stable: at 90.4% of their follow-up visits, patients clustered in the same subgroup as their baseline visit.

INTERPRETATION

ALS can manifest itself in 3 main patterns of cerebral neurodegeneration, each associated with distinct clinical characteristics and cognitive profiles. Besides the pure motor and frontotemporal dementia (FTD)-like variants of ALS, a new neuroimaging phenotype has emerged, characterized by posterior cingulate, parietal, temporal, and cerebellar involvement. ANN NEUROL 2022;92:1030-1045.

Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.

Classification of amyotrophic lateral sclerosis by brain volume, connectivity, and network dynamics

Emerging studies corroborate the importance of neuroimaging biomarkers and machine learning to improve diagnostic classification of amyotrophic lateral sclerosis (ALS). While most studies focus on structural data, recent studies assessing functional connectivity between brain regions by linear methods highlight the role of brain function. These studies have yet to be combined with brain structure and nonlinear functional features. We investigate the role of linear and nonlinear functional brain features, and the benefit of combining brain structure and function for ALS classification. ALS patients (N = 97) and healthy controls (N = 59) underwent structural and functional resting state magnetic resonance imaging. Based on key hubs of resting state networks, we defined three feature sets comprising brain volume, resting state functional connectivity (rsFC), as well as (nonlinear) resting state dynamics assessed via recurrent neural networks. Unimodal and multimodal random forest classifiers were built to classify ALS. Out-of-sample prediction errors were assessed via five-fold cross-validation. Unimodal classifiers achieved a classification accuracy of 56.35-61.66%. Multimodal classifiers outperformed unimodal classifiers achieving accuracies of 62.85-66.82%. Evaluating the ranking of individual features' importance scores across all classifiers revealed that rsFC features were most dominant in classification. While univariate analyses revealed reduced rsFC in ALS patients, functional features more generally indicated deficits in information integration across resting state brain networks in ALS. The present work undermines that combining brain structure and function provides an additional benefit to diagnostic classification, as indicated by multimodal classifiers, while emphasizing the importance of capturing both linear and nonlinear functional brain properties to identify discriminative biomarkers of ALS.

Amyotrophic Lateral Sclerosis-Frontotemporal Dementia: Shared and Divergent Neural Correlates Across the Clinical Spectrum

BACKGROUND AND OBJECTIVES

A significant overlap between amyotrophic lateral sclerosis (ALS) and behavioral variant of frontotemporal dementia (bvFTD) has been observed at clinical, genetic, and pathologic levels. Within this continuum of presentations, the presence of mild cognitive or behavioral symptoms in patients with ALS has been consistently reported, although it is unclear whether this is to be considered a distinct phenotype or rather a natural evolution of ALS. Here, we used mathematical modeling of MRI connectomic data to decipher common and divergent neural correlates across the ALS-frontotemporal dementia (FTD) spectrum.

METHODS

We included 83 patients with ALS, 35 patients with bvFTD, and 61 healthy controls, who underwent clinical, cognitive, and MRI assessments. Patients with ALS were classified according to the revised Strong criteria into 54 ALS with only motor deficits (ALS-cn), 21 ALS with cognitive or behavioral involvement (ALS-ci/bi), and 8 ALS with bvFTD (ALS-FTD). First, we assessed the functional and structural connectivity patterns across the ALS-FTD spectrum. Second, we investigated whether and where MRI connectivity alterations of patients with ALS with any degree of cognitive impairment (i.e., ALS-ci/bi and ALS-FTD) resembled more the pattern of damage of one (ALS-cn) or the other end (bvFTD) of the spectrum, moving from group-level to single-subject analysis.

RESULTS

As compared with controls, extensive structural and functional disruption of the frontotemporal and parietal networks characterized bvFTD (bvFTD-like pattern), while a more focal structural damage within the sensorimotor-basal ganglia areas characterized ALS-cn (ALS-cn-like pattern). ALS-ci/bi patients demonstrated an ALS-cn-like pattern of structural damage, diverging from ALS-cn with similar motor impairment for the presence of enhanced functional connectivity within sensorimotor areas and decreased functional connectivity within the bvFTD-like pattern. On the other hand, patients with ALS-FTD resembled both structurally and functionally the bvFTD-like pattern of damage with, in addition, the structural ALS-cn-like damage in the motor areas.

DISCUSSION

Our findings suggest a maladaptive role of functional rearrangements in ALS-ci/bi concomitantly with similar structural alterations compared to ALS-cn, supporting the hypothesis that ALS-ci/bi might be considered as a phenotypic variant of ALS, rather than a consequence of disease worsening.

Functional connectivity in Parkinson's disease candidates for deep brain stimulation

This study aimed to identify functional neuroimaging patterns anticipating the clinical indication for deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). A cohort of prospectively recruited patients with PD underwent neurological evaluations and resting-state functional MRI (RS-fMRI) at baseline and annually for 4 years. Patients were divided into two groups: 19 patients eligible for DBS over the follow-up and 41 patients who did not meet the criteria to undergo DBS. Patients selected as candidates for DBS did not undergo surgery at this stage. Sixty age- and sex-matched healthy controls performed baseline evaluations. Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity at baseline and at each time point. At baseline, network analysis showed a higher mean nodal strength, local efficiency, and clustering coefficient of the occipital areas in candidates for DBS over time relative to controls and patients not eligible for DBS. The occipital hyperconnectivity pattern was confirmed by regional analysis. At baseline, a decreased functional connectivity between basal ganglia and sensorimotor/frontal networks was found in candidates for DBS compared to patients not eligible for surgery. In the longitudinal analysis, patient candidate for DBS showed a progressively decreased topological brain organization and functional connectivity, mainly in the posterior brain networks, and a progressively increased connectivity of basal ganglia network compared to non-candidates for DBS. RS-fMRI may support the clinical indication to DBS and could be useful in predicting which patients would be eligible for DBS in the earlier stages of PD.

Abnormal Stability of Dynamic Functional Architecture in Amyotrophic Lateral Sclerosis: A Preliminary Resting-State fMRI Study

Purpose: Static and dynamic analyses for identifying functional connectivity (FC) have demonstrated brain dysfunctions in amyotrophic lateral sclerosis (ALS). However, few studies on the stability of dynamic FC have been conducted among ALS patients. This study explored the change of functional stability in ALS and how it correlates with disease severity.

Methods: We gathered resting-state functional magnetic resonance data from 20 patients with ALS and 22 healthy controls (HCs). The disease severity was assessed with the Revised ALS Functional Rating Scale (ALSFRS-R). We used a sliding window correlation approach to identify dynamic FC and measured the concordance of dynamic FC over time to obtain the functional stability of each voxel. We assessed the between-group difference in functional stability by voxel-wise two-sample t-test. The correlation between the functional stability index and ALSFRS-R in ALS patients was evaluated using Spearman's correlation analysis.

Results: Compared with the HC group, the ALS group had significantly increased functional stability in the left pre-central and post-central gyrus and right temporal pole while decreased functional stability in the right middle and inferior frontal gyrus. The results revealed a significant correlation between ALSFRS-R and the mean functional stability in the right temporal pole (r = −0.452 and P = 0.046) in the ALS patients.

Conclusions: ALS patients have abnormal stability of brain functional architecture, which is associated with the severity of the disease.

Dynamic Changes in Functional Network Connectivity Involving Amyotrophic Lateral Sclerosis and Its Correlation With Disease Severity

BACKGROUND

Aberrant static functional connectivity (FC) has been well demonstrated in amyotrophic lateral sclerosis (ALS); however, ALS-related alterations in FC dynamic properties remain unclear, although dynamic FC analyses contribute to uncover mechanisms underlying neurodegenerative disorders.

PURPOSE

To explore dynamic functional network connectivity (dFNC) in ALS and its correlation with disease severity.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-two ALS patients and 45 healthy controls.

FIELD STRENGTH/SEQUENCE

Multiband resting-state functional images using gradient echo echo-planar imaging and T1-weighted images were acquired at 3.0 T.

ASSESSMENT

Disease severity was evaluated with the revised ALS Functional Rating Scale (ALSFRS-R) and patients were stratified according to diagnostic category. Independent component analysis was conducted to identify the components of seven intrinsic brain networks (ie, visual/sensorimotor (SMN)/auditory/cognitive-control (CCN)/default-mode (DMN)/subcortical/cerebellar networks). A sliding-window correlation approach was used to compute dFNC. FNC states were determined by k-mean clustering, and state-specific FNC and dynamic indices (fraction time/mean dwell time/transition number) were calculated.

STATISTICAL TESTS

Two-sample t test used for comparisons on dynamic measures and Spearman's correlation analysis.

RESULTS

ALS patients showed increased FNC between DMN-SMN in state 1 and between CCN-SMN in state 4. Patients remained in state 2 (showing the weakest FNC) for a significantly longer time (mean dwell time: 49.8 ± 40.1 vs. 93.6 ± 126.3; P < 0.05) and remained in state 1 (showing a relatively strong FNC) for a shorter time (fraction time: 0.27 ± 0.25 vs. 0.13 ± 0.20; P < 0.05). ALS patients exhibited less temporal variability in their FNC (transition number: 10.2 ± 4.4 vs. 7.8 ± 3.8; P < 0.05). A significant correlation was observed between ALSFRS-R and mean dwell time in state 2 (r = -0.414, P < 0.05) and transition number (r = 0.452, P < 0.05). No significant between-subgroup difference in dFNC properties was found (all P > 0.05).

DATA CONCLUSION

Our findings suggest aberrant dFNC properties in ALS, which is associated with disease severity.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 3.

Hypothalamus and weight loss in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating progressive neurodegenerative disorder. While initially pathophysiology was thought to be restricted to motor deficits, it is increasingly recognized that patients develop prominent changes in weight and eating behavior that result from and mediate the underlying neurodegenerative process. These changes include alterations in metabolism, lipid levels, and insulin resistance. Emerging research suggests that these alterations may be mediated through changes in the hypothalamic function, with atrophy of the hypothalamus shown in both ALS patients and also presymptomatic genetic at-risk patients. This chapter reviews the evidence for hypothalamic involvement in ALS, including melanocortin pathways and potential treatment targets.

Frontal Functional Network Disruption Associated with Amyotrophic Lateral Sclerosis: An fNIRS-Based Minimum Spanning Tree Analysis

Recent evidence increasingly associates network disruption in brain organization with multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a rare terminal disease. However, the comparability of brain network characteristics across different studies remains a challenge for conventional graph theoretical methods. One suggested method to address this issue is minimum spanning tree (MST) analysis, which provides a less biased comparison. Here, we assessed the novel application of MST network analysis to hemodynamic responses recorded by functional near-infrared spectroscopy (fNIRS) neuroimaging modality, during an activity-based paradigm to investigate hypothetical disruptions in frontal functional brain network topology as a marker of the executive dysfunction, one of the most prevalent cognitive deficit reported across ALS studies. We analyzed data recorded from nine participants with ALS and ten age-matched healthy controls by first estimating functional connectivity, using phase-locking value (PLV) analysis, and then constructing the corresponding individual and group MSTs. Our results showed significant between-group differences in several MST topological properties, including leaf fraction, maximum degree, diameter, eccentricity, and degree divergence. We further observed a global shift toward more centralized frontal network organizations in the ALS group, interpreted as a more random or dysregulated network in this cohort. Moreover, the similarity analysis demonstrated marginally significantly increased overlap in the individual MSTs from the control group, implying a reference network with lower topological variation in the healthy cohort. Our nodal analysis characterized the main local hubs in healthy controls as distributed more evenly over the frontal cortex, with slightly higher occurrence in the left prefrontal cortex (PFC), while in the ALS group, the most frequent hubs were asymmetrical, observed primarily in the right prefrontal cortex. Furthermore, it was demonstrated that the global PLV (gPLV) synchronization metric is associated with disease progression, and a few topological properties, including leaf fraction and tree hierarchy, are linked to disease duration. These results suggest that dysregulation, centralization, and asymmetry of the hemodynamic-based frontal functional network during activity are potential neuro-topological markers of ALS pathogenesis. Our findings can possibly support new bedside assessments of the functional status of ALS' brain network and could hypothetically extend to applications in other neurodegenerative diseases.

Static and dynamic alterations in the amplitude of low-frequency fluctuation in patients with amyotrophic lateral sclerosis

Background

Static changes in local brain activity in patients suffering from amyotrophic lateral sclerosis (ALS) have been studied. However, the dynamic characteristics of local brain activity are poorly understood. Whether dynamic alterations could differentiate patients with ALS from healthy controls (HCs) remains unclear.

Methods

A total of 54 patients with ALS (mean age = 48.71 years, male/female = 36/18) and 54 (mean age = 48.30 years, male/female = 36/18) HCs underwent magnetic resonance imaging scans. To depict static alterations in cortical activity, amplitude of low-frequency fluctuations (ALFF) which measures the total power of regional activity was computed. Dynamic ALFF (d-ALFF) from all subjects was calculated using a sliding-window approach. Statistical differences in ALFF and d-ALFF between both groups were used as features to explore whether they could differentiate ALS from HC through support vector machine method.

Results

In contrast with HCs, patients with ALS displayed increased ALFF in the right inferior temporal gyrus and bilateral frontal gyrus and decreased ALFF in the left middle occipital gyrus and left precentral gyrus. Furthermore, patients with ALS demonstrated lower d-ALFF in widespread regions, including the right lingual gyrus, left superior temporal gyrus, bilateral precentral gyrus, and left paracentral lobule by comparison with HCs. In addition, the ALFF in the left superior orbitofrontal gyrus had a tendency of correlation with ALSFRS-R score and disease progression rate. The classification performance in distinguishing ALS was higher with both features of ALFF and d-ALFF than that with a single approach.

Conclusions

Decreased dynamic brain activity in the precentral gyrus, paracentral gyrus, lingual gyrus, and temporal regions was found in the ALS group. The combined ALFF and d-ALFF could distinguish ALS from HCs with a higher accuracy than ALFF and d-ALFF alone. These findings may provide important evidence for understanding the neuropathology underlying ALS.

Is it accurate to classify ALS as a neuromuscular disorder?

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is a fatal disorder characterized by the progressive loss of upper and lower motor neurons. ALS has traditionally been classified within the domain of neuromuscular diseases, which are a unique spectrum of disorders that predominantly affect the peripheral nervous system. However, over the past decades compounding evidence has emerged that there is extensive involvement of the central nervous system. Therefore, one can question whether it remains accurate to classify ALS as a neuromuscular disorder.

AREAS COVERED

In this review, the authors sought to discuss current approaches toward disease classification and how we should classify ALS based on novel insights from clinical, imaging, pathophysiological, neuropathological and genetic studies.

EXPERT OPINION

ALS exhibits the cardinal features of a neurodegenerative disease. Therefore, classifying ALS as a neuromuscular disease in the strict sense has become untenable. Diagnosing ALS however does require significant neuromuscular expertise and therefore neuromuscular specialists remain best equipped to evaluate this category of patients. Designating motor neuron diseases as a separate category in the ICD-11 is justified and adequately deals with this issue. However, to drive effective therapy development the fields of motor neuron disease and neurodegenerative disorders must come together.

The Distinct Traits of the UNC13A Polymorphism in Amyotrophic Lateral Sclerosis

Objective

The rs12608932 single nucleotide polymorphism in UNC13A is associated with amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) susceptibility, and may underlie differences in treatment response. We aimed to characterize the clinical, cognitive, behavioral, and neuroimaging phenotype of UNC13A in patients with ALS.

Methods

We included 2,216 patients with ALS without a C9orf72 mutation to identify clinical characteristics associated with the UNC13A polymorphism. A subcohort of 428 patients with ALS was used to study cognitive and behavioral profiles, and 375 patients to study neuroimaging characteristics. Associations were analyzed under an additive genetic model.

Results

Genotyping rs12608932 resulted in 854 A/A, 988 A/C, and 374 C/C genotypes. The C allele was associated with a higher age at symptom onset (median years A/A 63.5, A/C 65.6, and C/C 65.5; p < 0.001), more frequent bulbar onset (A/A 29.6%, A/C 31.8%, and C/C 43.1%; p < 0.001), higher incidences of ALS‐FTD (A/A 4.3%, A/C 5.2%, and C/C 9.5%; p = 0.003), lower forced vital capacity at diagnosis (median percentage A/A 92.0, A/C 90.0, and C/C 86.5; p < 0.001), and a shorter survival (median in months A/A 33.3, A.C 30.7, and C/C 26.6; p < 0.001). UNC13A was associated with lower scores on ALS‐specific cognition tests (means A/A 79.5, A/C 78.1, and C/C 76.6; p = 0.037), and more frequent behavioral disturbances (A/A 16.7%, A/C 24.4%, and C/C 27.7%; p = 0.045). Thinner left inferior temporal and right fusiform cortex were associated with the UNC13A single nucleotide polymorphism (SNP; p = 0.045 and p = 0.036).

Interpretation

Phenotypical distinctions associated with UNC13A make it an important factor to take into account in clinical trial design, studies on cognition and behavior, and prognostic counseling. ANN NEUROL 2020;88:796–806

2-Deoxy-2-[18 F]fluoro-d-glucose positron emission tomography, cortical thickness and white matter graph network abnormalities in brains of patients with amyotrophic lateral sclerosis and frontotemporal dementia suggest early neuronopathy rather than axonopathy

BACKGROUND AND PURPOSE

Amyotrophic lateral sclerosis (ALS) is a motor neuron disorder, although extra-motor degeneration is well recognized, especially in frontotemporal regions manifested as ALS with frontotemporal dementia (ALS-FTD). Previous neuroimaging studies of the brains of ALS-FTD patients have measured abnormalities of either grey matter (GM) or white matter (WM) structures but not of both together. Therefore, the aim was to evaluate both GM and WM in the same ALS-FTD patient using functional and structural neuroimaging. By doing so, insights could be gained into whether neurodegeneration in ALS-FTD is primarily a neuronopathy or axonopathy.

METHODS

After high-resolution brain 2-deoxy-2-[¹⁸ F]fluoro-D-glucose (¹⁸ F-FDG) positron emission tomography (PET) and magnetic resonance imaging (MRI) scans were obtained in ALS-FTD patients and in age- and sex-matched neurological controls, changes in metabolic rate, cortical thickness (CT) and WM network analysis using graph theory were analyzed.

RESULTS

Significant reductions in ¹⁸ F-FDG PET metabolism, CT and WM connections were observed in motor and extra-motor brain regions of ALS-FTD patients compared to controls. Both CT and underlying WM networks were abnormal in frontal, temporal, parietal and occipital lobes of ALS-FTD patients with 86 of 90 brain regions showing reductions of CT.

CONCLUSION

Abnormalities in significantly fewer WM networks underlying the affected cortical regions suggest that neurodegeneration in brains of ALS-FTD patients is primarily a 'neuronopathy' rather than an 'axonopathy.'

Connectome-Based Propagation Model in Amyotrophic Lateral Sclerosis

OBJECTIVE

Clinical trials in amyotrophic lateral sclerosis (ALS) continue to rely on survival or functional scales as endpoints, despite the emergence of quantitative biomarkers. Neuroimaging-based biomarkers in ALS have been shown to detect ALS-associated pathology in vivo, although anatomical patterns of disease spread are poorly characterized. The objective of this study is to simulate disease propagation using network analyses of cerebral magnetic resonance imaging (MRI) data to predict disease progression.

METHODS

Using brain networks of ALS patients (n = 208) and matched controls across longitudinal time points, network-based statistics unraveled progressive network degeneration originating from the motor cortex and expanding in a spatiotemporal manner. We applied a computational model to the MRI scan of patients to simulate this progressive network degeneration. Simulated aggregation levels at the group and individual level were validated with empirical impairment observed at later time points of white matter and clinical decline using both internal and external datasets.

RESULTS

We observe that computer-simulated aggregation levels mimic true disease patterns in ALS patients. Simulated patterns of involvement across cortical areas show significant overlap with the patterns of empirically impaired brain regions on later scans, at both group and individual levels. These findings are validated using an external longitudinal dataset of 30 patients.

INTERPRETATION

Our results are in accordance with established pathological staging systems and may have implications for patient stratification in future clinical trials. Our results demonstrate the utility of computational models in ALS to predict disease progression and underscore their potential as a prognostic biomarker. ANN NEUROL 2020;87:725-738.

Advanced neuroimaging approaches in amyotrophic lateral sclerosis: refining the clinical diagnosis

Introduction: In the last decade, multiparametric magnetic resonance imaging (MRI) has achieved tremendous advances in applications to amyotrophic lateral sclerosis (ALS) to increase the understanding of the associated pathophysiology. The aim of this review is to summarize recent progress in the development of MRI-based techniques aiming to support the clinical diagnosis in ALS.Areas covered: The review of structural and functional MRI applications to ALS and its variants (restricted phenotypes) is focused on the potential of MRI techniques which contribute to the diagnostic work-up of patients with the clinical presentation of a motor neuron disease. The potential of specific MRI methods for patient diagnosis and monitoring is discussed, and the future design of clinical MRI applications to ALS is conceptualized.Expert opinion: Current multiparametric MRI allows for the use as a clinical biological marker and a technical instrument in the clinical diagnosis of patients with ALS and also of patients with ALS variants. Composite neuroimaging indices of specific anatomical areas derived from different MRI techniques might guide in the diagnostic applications to ALS. Such a development of ALS-specific MRI-based composite scores with sufficient discriminative power versus ALS mimics at an individual level requires standardized advanced protocols and comprehensive analysis approaches.

Changes in functional and structural brain connectome along the Alzheimer's disease continuum

The aim of this study was two-fold: (i) to investigate structural and functional brain network architecture in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), stratified in converters (c-aMCI) and non-converters (nc-aMCI) to AD; and to assess the relationship between healthy brain network functional connectivity and the topography of brain atrophy in patients along the AD continuum. Ninety-four AD patients, 47 aMCI patients (25 c-aMCI within 36 months) and 53 age- and sex-matched healthy controls were studied. Graph analysis and connectomics assessed global and local, structural and functional topological network properties and regional connectivity. Healthy topological features of brain regions were assessed based on their connectivity with the point of maximal atrophy (epicenter) in AD and aMCI patients. Brain network graph analysis properties were severely altered in AD patients. Structural brain network was already altered in c-aMCI patients relative to healthy controls in particular in the temporal and parietal brain regions, while functional connectivity did not change. Structural connectivity alterations distinguished c-aMCI from nc-aMCI cases. In both AD and c-aMCI, the point of maximal atrophy was located in left hippocampus (disease-epicenter). Brain regions most strongly connected with the disease-epicenter in the healthy functional connectome were also the most atrophic in both AD and c-aMCI patients. Progressive degeneration in the AD continuum is associated with an early breakdown of anatomical brain connections and follows the strongest connections with the disease-epicenter. These findings support the hypothesis that the topography of brain connectional architecture can modulate the spread of AD through the brain.

Dominant Heterogeneity of Upper and Lower Motor Neuron Degeneration to Motor Manifestation of Involved Region in Amyotrophic Lateral Sclerosis

The aim of this study was to localize the anatomic distribution of upper motor neuron (UMN) loss through examining cortical thickness at the clinical onset of amyotrophic lateral sclerosis (ALS) and explore motor manifestation in functionally impaired body region attribute to impairment of lower motor neuron (LMN) or UMN or mixed LMN and UMN? The clinical features, cortical thickness of corresponding areas from different body regions in MRI and electromyography (EMG) data were collected from 108 classical ALS patients. The cortical thickness was thinner in ALS group than control group in bilateral head-face and upper-limb areas (p < 0.05). In head-face area, the cortical thickness of bulbar-onset group was significantly lower than that of control groups (p < 0.05). In upper-limb areas, the cortical thickness of cervical-onset group was significantly thinner than that of control group. Notably, the bulbar ALSFRS-R subscore was correlated with cortical thickness in bilateral head-face areas (p < 0.05). The bulbar ALSFRS-R subscore of the positive LMN damage group was lower compared to that of the negative LMN damage group (P < 0.001). The limb ALSFRS-R subscore correlated with compound muscle action potential (CMAP) amplitudes of median, ulnar, peroneal, and tibial nerves (P < 0.001), but was not related to cortical thickness. In conclusion, the UMN degeneration in ALS was derived from focal initiation, bulbar- and cervical-onset may date from head-face and upper-limb areas in motor homunculus cortex, respectively. The bulbar dysfunction was resulted from the mixed UMN and LMN impairment, while limb dysfunction derived mostly from LMN loss.

Cross-sectional and longitudinal assessment of the upper cervical spinal cord in motor neuron disease

Background

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease characterized by both upper and lower motor neuron degeneration. While neuroimaging studies of the brain can detect upper motor neuron degeneration, these brain MRI scans also include the upper part of the cervical spinal cord, which offers the possibility to expand the focus also towards lower motor neuron degeneration. Here, we set out to investigate cross-sectional and longitudinal disease effects in the upper cervical spinal cord in patients with ALS, progressive muscular atrophy (PMA: primarily lower motor neuron involvement) and primary lateral sclerosis (PLS: primarily upper motor neuron involvement), and their relation to disease severity and grey and white matter brain measurements.

Methods

We enrolled 108 ALS patients without C9orf72 repeat expansion (ALS C9–), 26 ALS patients with C9orf72 repeat expansion (ALS C9+), 28 PLS patients, 56 PMA patients and 114 controls. During up to five visits, longitudinal T1-weighted brain MRI data were acquired and used to segment the upper cervical spinal cord (UCSC, up to C3) and individual cervical segments (C1 to C4) to calculate cross-sectional areas (CSA). Using linear (mixed-effects) models, the CSA differences were assessed between groups and correlated with disease severity. Furthermore, a relationship between CSA and brain measurements was examined in terms of cortical thickness of the precentral gyrus and white matter integrity of the corticospinal tract.

Results

Compared to controls, CSAs at baseline showed significantly thinner UCSC in all groups in the MND spectrum. Over time, ALS C9– patients demonstrated significant thinning of the UCSC and, more specifically, of segment C3 compared to controls. Progressive thinning over time was also observed in C1 of PMA patients, while ALS C9+ and PLS patients did not show any longitudinal changes. Longitudinal spinal cord measurements showed a significant relationship with disease severity and we found a significant correlation between spinal cord and motor cortex thickness or corticospinal tract integrity for PLS and PMA, but not for ALS patients.

Discussion

Our findings demonstrate atrophy of the upper cervical spinal cord in the motor neuron disease spectrum, which was progressive over time for all but PLS patients. Cervical spinal cord imaging in ALS seems to capture different disease effects than brain neuroimaging. Atrophy of the cervical spinal cord is therefore a promising additional biomarker for both diagnosis and disease progression and could help in the monitoring of treatment effects in future clinical trials.

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Atrophy of upper cervical spinal cord is shown in the motor neuron disease spectrum.

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Progressive cervical spinal cord thinning occurs over time for all but PLS patients.

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Cervical spinal cord imaging is a potential biomarker for disease progression in ALS.

Patterned functional network disruption in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor function, with additional evidence of extensive nonmotor involvement. Despite increasing recognition of the disease as a multisystem network disorder characterised by impaired connectivity, the precise neuroelectric characteristics of impaired cortical communication remain to be fully elucidated. Here, we characterise changes in functional connectivity using beamformer source analysis on resting‐state electroencephalography recordings from 74 ALS patients and 47 age‐matched healthy controls. Spatiospectral characteristics of network changes in the ALS patient group were quantified by spectral power, amplitude envelope correlation (co‐modulation) and imaginary coherence (synchrony). We show patterns of decreased spectral power in the occipital and temporal (δ‐ to β‐band), lateral/orbitofrontal (δ‐ to θ‐band) and sensorimotor (β‐band) regions of the brain in patients with ALS. Furthermore, we show increased co‐modulation of neural oscillations in the central and posterior (δ‐, θ‐ and γ_l‐band) and frontal (δ‐ and γ_l‐band) regions, as well as decreased synchrony in the temporal and frontal (δ‐ to β‐band) and sensorimotor (β‐band) regions. Factorisation of these complex connectivity patterns reveals a distinct disruption of both motor and nonmotor networks. The observed changes in connectivity correlated with structural MRI changes, functional motor scores and cognitive scores. Characteristic patterned changes of cortical function in ALS signify widespread disease‐associated network disruption, pointing to extensive dysfunction of both motor and cognitive networks. These statistically robust findings, that correlate with clinical scores, provide a strong rationale for further development as biomarkers of network disruption for future clinical trials.

Motor and extra-motor gray matter integrity may underlie neurophysiologic parameters of motor function in amyotrophic lateral sclerosis: a combined voxel-based morphometry and transcranial stimulation study

The association between gray matter (GM) density and neurophysiologic changes is still unclear in amyotrophic lateral sclerosis (ALS). We evaluated the relationship between GM density and motor system integrity combining voxel-based morphometry (VBM) and transcranial magnetic stimulation (TMS) in ALS. We included 17 ALS patients and 22 healthy controls (HC) who underwent 3D-T1-weighted imaging. Among the ALS group, we applied left motor cortex single-pulse TMS. We used whole-brain VBM comparing ALS and HC in GM density. We also conducted regression analysis to examine correlations between GM density and the following TMS parameters: motor evoked potential (MEP)/M ratio and central motor conduction time (CMCT). We found significantly decreased GM density in ALS patients in several frontal, temporal, parietal/occipital and cerebellar regions (p < 0.001 uncorrected; cluster-extent threshold k = 100 voxels per cluster). With regards to TMS parameters, ALS patients showed mostly increased MEP/M ratio and modest prolongation of CMCT. MEP/M ratio was associated with GM density in (a) rolandic operculum/inferior frontal gyrus/precentral gyrus; anterior cingulate gyrus; inferior temporal gyrus; superior parietal lobule; cuneus; superior occipital gyrus and cerebellum (positive association) and (b) paracentral lobule/supplementary motor area (negative association). CMCT was associated with GM density in (a) inferior frontal gyrus and middle cingulated gyrus (positive association) and (b) superior parietal lobule; cuneus and cerebellum (negative association). Our findings support a significant interaction between motor and extra-motor structural and functional changes and highlight that motor and extra-motor GM integrity may underlie TMS parameters of motor function in ALS patients.

Imaging Cerebral Activity in Amyotrophic Lateral Sclerosis

Advances in neuroimaging, complementing histopathological insights, have established a multi-system involvement of cerebral networks beyond the traditional neuromuscular pathological view of amyotrophic lateral sclerosis (ALS). The development of effective disease-modifying therapy remains a priority and this will be facilitated by improved biomarkers of motor system integrity against which to assess the efficacy of candidate drugs. Functional MRI (FMRI) is an established measure of both cerebral activity and connectivity, but there is an increasing recognition of neuronal oscillations in facilitating long-distance communication across the cortical surface. Such dynamic synchronization vastly expands the connectivity foundations defined by traditional neuronal architecture. This review considers the unique pathogenic insights afforded by the capture of cerebral disease activity in ALS using FMRI and encephalography.

Neuroimaging in aging and neurologic diseases

Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.

Monitoring Value of Multimodal Magnetic Resonance Imaging in Disease Progression of Amyotrophic Lateral Sclerosis: A Prospective Observational Study

Background:

Ongoing efforts have been made to identify new neuroimaging markers to track amyotrophic lateral sclerosis (ALS) progression. This study aimed to explore the monitoring value of multimodal magnetic resonance imaging (MRI) in the disease progression of ALS.

Methods:

From September 2015 to March 2017, ten patients diagnosed with ALS in Peking Union Medical College Hospital completed head MRI scans at baseline and during follow-up. Multimodal MRI analyses, including gray matter (GM) volume measured by voxel-based morphometry; cerebral blood flow (CBF) evaluated by arterial spin labeling; functional connectivity, including low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), measured by resting-state functional MRI; and integrity of white-matter (WM) fiber tracts evaluated by diffusion tensor imaging, were performed in these patients. Comparisons of imaging metrics were made between baseline and follow-up using paired t-test.

Results:

In the longitudinal comparisons, the brain structure (GM volume of the right precentral gyri, left postcentral gyri, and right thalami) and perfusion (CBF of the bilateral temporal poles, left precentral gyri, postcentral gyri, and right middle temporal gyri) in both motor and extramotor areas at follow-up were impaired to different extents when compared with those at baseline (all P < 0.05, false discovery rate adjusted). Functional connectivity was increased in the motor areas (fALFF of the right precentral gyri and superior frontal gyri, and ReHo of right precentral gyri) and decreased in the extramotor areas (fALFF of the bilateral middle frontal gyri and ReHo of the right precuneus and cingulate gyri) (all P < 0.001, unadjusted). No significant changes were detected in terms of brain WM measures.

Conclusion:

Multimodal MRI could be used to monitor short-term brain changes in ALS patients.

Neurodegeneration of brain networks in the amyotrophic lateral sclerosis-frontotemporal lobar degeneration (ALS-FTLD) continuum: evidence from MRI and MEG studies

Brain imaging techniques, especially those based on magnetic resonance imaging (MRI) and magnetoencephalography (MEG), have been increasingly applied to study multiple large-scale distributed brain networks in healthy people and neurological patients. With regard to neurodegenerative disorders, amyotrophic lateral sclerosis (ALS), clinically characterized by the predominant loss of motor neurons and progressive weakness of voluntary muscles, and frontotemporal lobar degeneration (FTLD), the second most common early-onset dementia, have been proven to share several clinical, neuropathological, genetic, and neuroimaging features. Specifically, overlapping or mildly diverging brain structural and functional connectivity patterns, mostly evaluated by advanced MRI techniques-such as diffusion tensor and resting-state functional MRI (DT-MRI, RS-fMRI)-have been described comparing several ALS and FTLD populations. Moreover, though only pioneering, promising clues on connectivity patterns in the ALS-FTLD continuum may derive from MEG investigations. We will herein overview the current state of knowledge concerning the most advanced neuroimaging findings associated with clinical and genetic patterns of neurodegeneration across the ALS-FTLD continuum, underlying the possibility that network-based approaches may be useful to develop novel biomarkers of disease for adequately designing and monitoring more appropriate treatment strategies.

Imaging Biomarkers for the Diagnosis and Prognosis of Neurodegenerative Diseases. The Example of Amyotrophic Lateral Sclerosis

The term amyotrophic lateral sclerosis (ALS) comprises a heterogeneous group of fatal neurodegenerative disorders of largely unknown etiology characterized by the upper motor neurons (UMN) and/or lower motor neurons (LMN) degeneration. The development of brain imaging biomarkers is essential to advance in the diagnosis, stratification and monitoring of ALS, both in the clinical practice and clinical trials. In this review, the characteristics of an optimal imaging biomarker and common pitfalls in biomarkers evaluation will be discussed. Moreover, the development and application of the most promising brain magnetic resonance (MR) imaging biomarkers will be reviewed. Finally, the integration of both qualitative and quantitative multimodal brain MR biomarkers in a structured report will be proposed as a support tool for ALS diagnosis and stratification.

Altered white matter microarchitecture in amyotrophic lateral sclerosis: A voxel-based meta-analysis of diffusion tensor imaging

Background

The results of recent diffusion tensor imaging (DTI) studies on amyotrophic lateral sclerosis (ALS) are inconclusive and controversial. We performed a voxel-based meta-analysis to identify a statistical consensus among published DTI studies of altered white matter (WM) microarchitecture in ALS.

Methods

A systematic search was conducted for relevant studies that used voxel-wise analyses of WM microarchitecture in patients with ALS. Anisotropic effect size-signed differential mapping (AES-SDM) was applied to analyze fractional anisotropy (FA) differences between ALS patients and healthy controls. Meta-regression analysis was used to explore the effects of clinical characteristics on WM integrity in patients with ALS.

Results

A total of 14 studies with 16 datasets that included 396 patients and 360 healthy controls were identified. The pooled meta-analysis revealed that patients with ALS exhibited significant FA reductions in two clusters relative to healthy controls. The largest cluster exhibited a peak coordinate in the left corona radiata, extending to the body and splenium of the corpus callosum, left superior longitudinal fasciculus, posterior limb of the internal capsule, right corona radiata, and bilateral cingulate gyrus. The other cluster exhibited decreased FA in the right corticospinal tract that extended to the right cerebral peduncle. The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) score was positively correlated with the FA reduction in the left corona radiata. Mean age and illness duration were not linearly correlated with the FA reductions.

Conclusions

This study provides a thorough profile of WM microarchitecture alterations in patients with ALS and further evidence that the neuronal degeneration is not limited to the corticospinal tract but also includes extra-motor areas, which supports the view that ALS is a multisystem degenerative disorder that involves the white matter.

Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.

Reduced striato-cortical and inhibitory transcallosal connectivity in the motor circuit of Huntington's disease patients

Huntington's disease (HD) is a neurodegenerative disorder which is primarily associated with striatal degeneration. However, the alterations in connectivity of this structure in HD have been underinvestigated. In this study, we analyzed the functional and structural connectivity of the left putamen, while participants performed a finger-tapping task. Using fMRI and DW-MRI, 30 HD gene expansion carriers (HDGEC) and 29 healthy participants were scanned. Psychophysiological interaction analysis and DTI-based tractography were employed to examine functional and structural connectivity, respectively. Manifest HDGEC exhibited a reduced functional connectivity of the left putamen with the left and the right primary sensorimotor areas (SM1). Based on this result, the inhibitory functional connectivity between the left SM1 and the right SM1 was explored, appearing to be also decreased. In addition, the tract connecting these areas (motor corpus callosum), and the tract connecting the left putamen with the left SM1 appeared disrupted in HDGEC compared to controls. Significant correlations were found between measures of functional and structural connectivity of the motor corpus callosum, showing a coupling of both types of alterations in this tract. The observed reduction of functional and structural connectivity was associated with worse motor scores, which highlights the clinical relevance of these results. Hum Brain Mapp 39:54-71, 2018. © 2017 Wiley Periodicals, Inc.

Abnormal cortical brain integration of somatosensory afferents in ALS

OBJECTIVES

Infraclinical sensory alterations have been reported at early stages of amyotrophic lateral sclerosis (ALS). While previous studies mainly focused on early somatosensory evoked potentials (SEPs), late SEPs, which reflect on cortical pathways involved in cognitive-motor functions, are relatively underinvestigated. Early and late SEPs were compared to assess their alterations in ALS.

METHODS

Median and ulnar nerves were electrically stimulated at the wrist, at 9 times the perceptual threshold, in 21 ALS patients without clinical evidence of sensory deficits, and 21 age- and gender-matched controls. SEPs were recorded at the Erb point using surface electrodes and using a needle inserted in the scalp, in front of the primary somatosensory area (with reference electrode on the ear lobe).

RESULTS

Compared to controls, ALS patients showed comparable peripheral (N9) and early cortical component (N20, P25, N30) reductions, while the late cortical components (N60, P100) were more depressed than the early ones.

CONCLUSIONS

The peripheral sensory alteration likely contributed to late SEP depression to a lesser extent than that of early SEPs.

SIGNIFICANCE

Late SEPs may provide new insights on abnormal cortical excitability affecting brain areas involved in cognitive-motor functions.

Hubness of strategic planning and sociality influences depressive mood and anxiety in College Population

Depressive mood and anxiety can reduce cognitive performance. Conversely, the presence of a biased cognitive tendency may serve as a trigger for depressive mood-anxiety. Previous studies have largely focused on group-wise correlations between clinical-neurocognitive variables. Using network analyses for intra-individual covariance, we sought to decipher the most influential clinical-neurocognitive hub in the differential severity of depressive-anxiety symptoms in a college population. Ninety college students were evaluated for depressive-anxiety symptoms, Minnesota multiphasic personality inventory-2(MMPI-2), and neuro-cognition. Weighted and undirected version of the intra-individual covariance networks, comprised of 18 clinical-neurocognitive variables satisfied small-worldness and modular organization in the sparsity range of K = 0.20-0.21. Furthermore, betweenness centrality of perseverative error for the Wisconsin card sorting test was reduced in more depressive individuals; higher anxiety was related to the increased betweenness centrality of MMPI-2 clinical scale 0(Si). Elevated edge-betweenness centrality of covariance between the MMPI-2 clinical scale 7(Pt) versus commission error of the continuous performance test predicted more anxiety higher than depressive mood. With intra-individual covariance network of clinical-neurocognitive variables, this study demonstrated critical drivers of depressive mood[attenuated influence of strategic planning] or anxiety[domination of social introversion/extroversion, in addition to the influence of compulsivity-impulsivity covariance as a shortcut component among various clinical-neurocognitive features].

The two-year progression of structural and functional cerebral MRI in amyotrophic lateral sclerosis

MRI has emerged as one of several urgently needed candidate disease progression biomarkers for the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), not least due to its unique ability to non-invasively assess structural and functional cerebral pathology. We sought to identify the extent of detectable change in cerebral MRI metrics over a more prolonged period.

Analysis of multi-modal MRI data was performed in a cohort of sixteen patients (13 ALS and 3 with primary lateral sclerosis) in whom it was possible to acquire six-monthly images over two years. Structural brain changes were assessed using voxel-based morphometry of grey matter and shape analysis of sub-cortical grey matter structures, tract-based spatial statistics of diffusion tensor imaging (DTI) metrics optimized for longitudinal analysis in the white matter, as well as whole brain voxel-wise statistics of DTI metrics. Changes in resting state functional MRI (rs-fMRI) were investigated via independent component and dual regression analyses of functional connectivity (FC), controlled for confounding effects of grey matter decline. Both linear changes with time and brain changes correlated with revised ALS functional rating score (ALSFRS-R) decline were studied.

Widespread and progressive reductions in grey matter were observed in the precentral gyri and posterior cingulate cortex, as well as progressive local atrophy of the thalamus, caudate, and pallidum bilaterally, and right putamen, hippocampus and amygdala. The most prominent DTI tract-based changes were in the superior longitudinal fasciculi and corpus callosum. More widespread areas of DTI changes included the thalami and caudate nuclei, hippocampi and parahippocampal gyri, insular cortices, anterior and posterior cingulate gyri, frontal operculum and cerebellum. FC decreases were noted between the sensorimotor resting state network and the frontal pole, between a network comprising both thalami and an area in the visual cortex, in relation to both time from baseline and ALSFRS-R decline. FC increases between the left primary motor cortex and left fronto-parietal network were seen for both statistical approaches.

A longer period of follow-up, though necessarily involving more slowly-progressive cases, demonstrated widespread changes in both grey and white matter structural MRI measures. The mixed picture of regional decreases and increases in FC is compatible with compensatory change, in what should be viewed as a brain-based disease characterised by larger-scale disintegration of motor and frontal projection cerebral networks.

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Analysis of serial MRI data (6-monthly over 2 years) was performed in ALS patients.

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Widespread progressive structural and functional brain changes were observed.

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Changes during this unprecedented study period involved basal ganglia regions.

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The results revealed novel longitudinal functional connectivity insights.

Frequency-Specific Abnormalities of Intrinsic Functional Connectivity Strength among Patients with Amyotrophic Lateral Sclerosis: A Resting-State fMRI Study

The classical concept that amyotrophic lateral sclerosis (ALS) is a degenerative disorder characterized by the loss of upper and lower motor neurons is agreed. However, more and more studies have suggested the involvement of some extra-motor regions. The aim of this study is to investigate the frequency-related alteration pattern of intrinsic functional connectivity strength (FCS) at the voxel-wise level in the relatively early-stage of ALS on a whole brain scale. In this study, 21 patients with ALS and 21 well-matched healthy control subjects were enrolled to examine the intrinsic FCS in the different frequencies (slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz, and typical band: 0.01-0.1 Hz). Compared with the control subjects, the ALS patients showed a significantly decreased FCS in the left prefrontal cortex (PFC) and the bilateral superior frontal gyrus. In the slow-5 band, the patients with ALS showed decreased FCS in the left lingual gyrus, as well as increased FCS in the left postcentral gyrus/paracentral lobule (PoCG/PARC). In the slow-4 band, the ALS patients presented decreased FCS in the left and right ventrolateral PFC. Moreover, the increased FCS in the left PoCG/PARC in the slow-5 band was positively correlated with the ALSFRS-r score (P = 0.015). Our results demonstrated that the FCS changes in ALS were wide spread and frequency dependent. These findings may provide some evidences that ALS patients have the consistent impairment in some extra-motor regions at a relatively early-stage.

Cortical influences drive amyotrophic lateral sclerosis

The early motor manifestations of sporadic amyotrophic lateral sclerosis (ALS), while rarely documented, reflect failure of adaptive complex motor skills. The development of these skills correlates with progressive evolution of a direct corticomotoneuronal system that is unique to primates and markedly enhanced in humans. The failure of this system in ALS may translate into the split hand presentation, gait disturbance, split leg syndrome and bulbar symptomatology related to vocalisation and breathing, and possibly diffuse fasciculation, characteristic of ALS. Clinical neurophysiology of the brain employing transcranial magnetic stimulation has convincingly demonstrated a presymptomatic reduction or absence of short interval intracortical inhibition, accompanied by increased intracortical facilitation, indicating cortical hyperexcitability. The hallmark of the TDP-43 pathological signature of sporadic ALS is restricted to cortical areas as well as to subcortical nuclei that are under the direct control of corticofugal projections. This provides anatomical support that the origins of the TDP-43 pathology reside in the cerebral cortex itself, secondarily in corticofugal fibres and the subcortical targets with which they make monosynaptic connections. The latter feature explains the multisystem degeneration that characterises ALS. Consideration of ALS as a primary neurodegenerative disorder of the human brain may incorporate concepts of prion-like spread at synaptic terminals of corticofugal axons. Further, such a concept could explain the recognised widespread imaging abnormalities of the ALS neocortex and the accepted relationship between ALS and frontotemporal dementia.

Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc.