Widespread temporo-occipital lobe dysfunction in amyotrophic lateral sclerosis

Appetite loss in patients with motor neuron disease: impact on weight loss and neural correlates of visual food cues

Motor Neuron Disease (MND) is associated with significant non-motor symptoms, including the loss of appetite. Loss of appetite has emerged as a dominant feature of the disease that may contribute to negative energy balance, faster disease progression and earlier death. We examined the prevalence and impact of appetite loss and analysed neural correlates of visual food stimuli with prandial status and appetite in people living with MND (plwMND). 157 plwMND and 120 non-neurodegenerative controls (NND Controls) were assessed for anthropometric, metabolic, appetite and clinical measures. Of these, 35 plwMND and 23 NND Controls underwent further functional MRI assessment of fasting and post-prandial responses to visual food cues. plwMND presented with reduced appetite (P < 0.001), with loss of appetite being more prevalent in plwMND than NND controls [OR = 2.59 (95% CI: = 1.46-4.61)]. Loss of appetite was not associated with hypermetabolism; however, was associated with fat mass loss (P < 0.05). Imaging assessment revealed no overall difference in response between plwMND and NND controls when viewing non-food and food images. In contrast, we found no prandial response in the temporal pole of plwMND compared with NND controls, and decreased activity in the cerebellum relative to appetite in plwMND. Loss of appetite, not hypermetabolism, contributes to negative energy balance in MND. Alterations in the temporal pole and cerebellum could contribute to altered appetite responses in some plwMND-brain regions not widely considered in appetite control-providing additional evidence to support widespread involvement of non-motor areas in the disease.

Cortical thickness correlated with peripheral inflammatory cytokines in amyotrophic lateral sclerosis

Introduction

Amyotrophic lateral sclerosis (ALS) is a rare, devastating neurodegenerative disease that affects upper and lower motor neurons, resulting in muscle atrophy, spasticity, hyperreflexia, and paralysis. Inflammation plays an important role in the development of ALS, and associated with rapid disease progression. Current observational studies indicate the thinning of cortical thickness in patients with ALS is associated with rapid disease progression and cognitive changes. However, the effects of inflammatory cytokines on cortical thickness in patients with ALS are unclear. Here, we investigated the relationship between inflammatory cytokines and cortical thickness in patients with ALS.

Methods

We evaluated 51 patients with ALS for inflammatory cytokines including interleukin (IL)-4, interferon (IFN)-α, IL-1β, IL-2, IL-5, IL-12, tumor necrosis factor (TNF)-α, IL-6, IL-10, IL-8, IL-17, and IFN-γ and analyzed the correlation between these indicators and the ALS functional rating scale-revised (ALSFRS-R) score or disease progression rate (ΔFS score). Twenty-six patients with ALS and 26 controls were studied using whole-cortex analysis, and post-hoc analyses were performed to examine the correlation between brain cortical thickness and ALSFRS-R or ΔFS scores.

Results

IL-4, IFN-α, IL-1β, and IL-2 levels were significantly correlated with ALSFRS-R scores, and the IL-2 level was significantly correlated with ΔFS scores. After controlling for age and sex, the ALS group had thinner cortexes in multiple clusters across the brain than the control group. Further analyses revealed that cortical thickness in the right superior temporal and lingual gyrus regions was inversely correlated with ΔFS scores. There was a significant positive correlation between the clusters in the right lingual cortex and IL-2 level.

Conclusion

These results suggest cortical thickness was reduced in patients with ALS in motor and non-motor cortical areas. Inflammatory factors (especially IL-2) were correlated with cortical thickness, and both were related to the disease progression rate, suggesting IL-2 plays an important role in ALS.

Distinct neural signatures of pulvinar in C9orf72 amyotrophic lateral sclerosis mutation carriers and noncarriers

BACKGROUND AND PURPOSE

Thalamic alterations have been reported as a major feature in presymptomatic and symptomatic patients carrying the C9orf72 mutation across the frontotemporal dementia-amyotrophic lateral sclerosis (ALS) spectrum. Specifically, the pulvinar, a high-order thalamic nucleus and timekeeper for large-scale cortical networks, has been hypothesized to be involved in C9orf72-related neurodegenerative diseases. We investigated whether pulvinar volume can be useful for differential diagnosis in ALS C9orf72 mutation carriers and noncarriers and how underlying functional connectivity changes affect this region.

METHODS

We studied 19 ALS C9orf72 mutation carriers (ALSC9+) accurately matched with wild-type ALS (ALSC9-) and ALS mimic (ALSmimic) patients using structural and resting-state functional magnetic resonance imaging data. Pulvinar volume was computed using automatic segmentation. Seed-to-voxel functional connectivity analyses were performed using seeds from a pulvinar functional parcellation.

RESULTS

Pulvinar structural integrity had high discriminative values for ALSC9+ patients compared to ALSmimic (area under the curve [AUC] = 0.86) and ALSC9- (AUC = 0.77) patients, yielding a volume cutpoint of approximately 0.23%. Compared to ALSmimic, ALSC9- showed increased anterior, inferior, and lateral pulvinar connections with bilateral occipital-temporal-parietal regions, whereas ALSC9+ showed no differences. ALSC9+ patients when compared to ALSC9- patients showed reduced pulvinar-occipital connectivity for anterior and inferior pulvinar seeds.

CONCLUSIONS

Pulvinar volume could be a differential biomarker closely related to the C9orf72 mutation. A pulvinar-cortical circuit dysfunction might play a critical role in disease progression and development, in both the genetic phenotype and ALS wild-type patients.

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = -7.40), and the MiToS (p = 0.0025; β = -4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho = -0.6041, p = 0.0003) and MiToS scales (Spearman's rho = -0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.

Functional alterations in large-scale resting-state networks of amyotrophic lateral sclerosis: A multi-site study across Canada and the United States

Amyotrophic lateral sclerosis (ALS) is a multisystem neurodegenerative disorder characterized by progressive degeneration of upper motor neurons and lower motor neurons, and frontotemporal regions resulting in impaired bulbar, limb, and cognitive function. Magnetic resonance imaging studies have reported cortical and subcortical brain involvement in the pathophysiology of ALS. The present study investigates the functional integrity of resting-state networks (RSNs) and their importance in ALS. Intra- and inter-network resting-state functional connectivity (Rs-FC) was examined using an independent component analysis approach in a large multi-center cohort. A total of 235 subjects (120 ALS patients; 115 healthy controls (HC) were recruited across North America through the Canadian ALS Neuroimaging Consortium (CALSNIC). Intra-network and inter-network Rs-FC was evaluated by the FSL-MELODIC and FSLNets software packages. As compared to HC, ALS patients displayed higher intra-network Rs-FC in the sensorimotor, default mode, right and left fronto-parietal, and orbitofrontal RSNs, and in previously undescribed networks including auditory, dorsal attention, basal ganglia, medial temporal, ventral streams, and cerebellum which negatively correlated with disease severity. Furthermore, ALS patients displayed higher inter-network Rs-FC between the orbitofrontal and basal ganglia RSNs which negatively correlated with cognitive impairment. In summary, in ALS there is an increase in intra- and inter-network functional connectivity of RSNs underpinning both motor and cognitive impairment. Moreover, the large multi-center CALSNIC dataset permitted the exploration of RSNs in unprecedented detail, revealing previously undescribed network involvement in ALS.

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.

Resting state functional brain networks associated with emotion processing in frontotemporal lobar degeneration

This study investigated the relationship between emotion processing and resting-state functional connectivity (rs-FC) of the brain networks in frontotemporal lobar degeneration (FTLD). Eighty FTLD patients (including cases with behavioral variant of frontotemporal dementia, primary progressive aphasia, progressive supranuclear palsy syndrome, motor neuron disease) and 65 healthy controls underwent rs-functional MRI. Emotion processing was tested using the Comprehensive Affect Testing System (CATS). In patients and controls, correlations were investigated between each emotion construct and rs-FC changes within critical networks. Mean rs-FC of the clusters significantly associated with CATS scoring were compared among FTLD groups. FTLD patients had pathological CATS scores compared with controls. In controls, increased rs-FC of the cerebellar and visuo-associative networks correlated with better scores in emotion-matching and discrimination tasks, respectively; while decreased rs-FC of the visuo-spatial network was related with better performance in the affect-matching and naming. In FTLD, the associations between rs-FC and CATS scores involved more brain regions, such as orbitofrontal and middle frontal gyri within anterior networks (i.e., salience and default-mode), parietal and somatosensory regions within visuo-spatial and sensorimotor networks, caudate and thalamus within basal-ganglia network. Rs-FC changes associated with CATS were similar among all FTLD groups. In FTLD compared to controls, the pattern of rs-FC associated with emotional processing involves a larger number of brain regions, likely due to functional specificity loss and compensatory attempts. These associations were similar across all FTLD groups, suggesting a common physiopathological mechanism of emotion processing breakdown, regardless the clinical presentation and pattern of atrophy.

Feature selection from magnetic resonance imaging data in ALS: a systematic review

Background:

With the advances in neuroimaging in amyotrophic lateral sclerosis (ALS), it has been speculated that multiparametric magnetic resonance imaging (MRI) is capable to contribute to early diagnosis. Machine learning (ML) can be regarded as the missing piece that allows for the useful integration of multiparametric MRI data into a diagnostic classifier. The major challenges in developing ML classifiers for ALS are limited data quantity and a suboptimal sample to feature ratio which can be addressed by sound feature selection.

Methods:

We conducted a systematic review to collect MRI biomarkers that could be used as features by searching the online database PubMed for entries in the recent 4 years that contained cross-sectional neuroimaging data of subjects with ALS and an adequate control group. In addition to the qualitative synthesis, a semi-quantitative analysis was conducted for each MRI modality that indicated which brain regions were most commonly reported.

Results:

Our search resulted in 151 studies with a total of 221 datasets. In summary, our findings highly resembled generally accepted neuropathological patterns of ALS, with degeneration of the motor cortex and the corticospinal tract, but also in frontal, temporal, and subcortical structures, consistent with the neuropathological four-stage model of the propagation of pTDP-43 in ALS.

Conclusions:

These insights are discussed with respect to their potential for MRI feature selection for future ML-based neuroimaging classifiers in ALS. The integration of multiparametric MRI including DTI, volumetric, and texture data using ML may be the best approach to generate a diagnostic neuroimaging tool for ALS.

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.

Cognitive Profiles of Amyotrophic Lateral Sclerosis Differ in Resting-State Functional Connectivity: An fMRI Study

Background

Half of all amyotrophic lateral sclerosis-frontotemporal spectrum disorder (ALS-FTSD) patients are classified as cognitively impaired, of which 10% have frontotemporal dementia (FTD), and an additional 40% suffer from a frontotemporal syndrome not severe enough to be described as dementia (cognitively impaired/ALSci). As changes in cerebral function measured by resting-state magnet resonance imaging (rs-fMRI) are known in ALS, we investigated whether group differences in resting-state functional connectivity (RSFC) networks could be observed between ALS patients with different cognitive profiles against healthy controls (HC). Furthermore, we correlated cognition and motor functioning with network connectivity.

Methods

Healthy controls, 69, and 97 ALS patients underwent functional MRI scanning and cognitive assessment. The ALS patients were categorized as non-impaired (ALSni; n = 68), cognitively impaired (ALSci; n = 21), and ALS-FTD (n = 8). Group differences in connectivity of the default mode network (DMN), motor network (MN), and ventral attention network (VAN) were investigated using a full-factorial model; correlations between global cognitive performance, shifting, and motor symptom severity were established using Pearson’s correlation.

Results

At a liberal alpha level of uncorrected p < 0.005 and a cluster size exceeding 20 voxels, we found widespread decreases in functional connectivity in all three networks when comparing ALS patients to HC. Similar patterns of hypoconnectivity in the bilateral motor cortices and frontotemporal emerged when comparing the ALSci and ALS-FTD patients to those not cognitively impaired. Hyperconnectivity in the DMN temporal gyrus correlated with worse global cognition; moreover, hyperconnectivity in the VAN thalamus, insula, and putamen correlated with worse shifting ability. Better-preserved motor function correlated with higher MN connectivity. Only the motor-related effects prevailed at a more conservative significance level of p_FDR< 0.001.

Conclusion

Resting-state functional connectivity differs between cognitive profiles of ALS and is directly associated with clinical presentation, specifically with motor function, and cognitive shifting.

Longitudinal changes in network homogeneity in presymptomatic C9orf72 mutation carriers

The risk for carriers of repeat expansion mutations in C9orf72 to develop amyotrophic lateral sclerosis and frontotemporal dementia increases with age. Functional magnetic resonance imaging studies have shown reduced connectivity in symptomatic carriers, but it is not known whether connectivity declines throughout life as an acceleration of the normal aging pattern. In this study, we examined intra-network homogeneity (NeHo) in 5 functional networks in 15 presymptomatic C9+ carriers over an 18-month period and compared to repeated scans in 34 healthy controls and 27 symptomatic C9+ carriers. The longitudinal trajectory of NeHo in the somatomotor, dorsal attention, and default mode networks in presymptomatic carriers differed from aging controls and symptomatic carriers. In somatomotor networks, NeHo increased over time in regions adjacent to regions where symptomatic carriers had reduced NeHo. In the default network, the posterior cingulate exhibited age-dependent increases in NeHo. These findings are evidence against the proposal that the decline in functional connectivity seen in symptomatic carriers represents a lifelong acceleration of the healthy aging process.

Reduced Occipital Cortex Excitability in Amyotrophic Lateral Sclerosis

PURPOSE

In addition to motor cortex involvement, sensory abnormalities have been demonstrated in amyotrophic lateral sclerosis (ALS), including structural and metabolic alterations in the occipital cortex. The aim of this study was to examine occipital excitability changes in ALS.

METHODS

Twenty-one patients with ALS and 16 healthy subjects were enrolled into the study. Phosphene experience and phosphene threshold were studied to assess occipital excitability. Cognitive function was evaluated in both groups by means of Montreal Cognitive Assessment and Addenbrooke's Cognitive Examination-Revised visuospatial score tests.

RESULTS

Phosphene was experienced in 13 (81.3%) healthy subjects and 9 (42.9%) patients with ALS (P = 0.04). The mean phosphene threshold was not significantly different between the two groups. No correlation existed between phosphene threshold and motor cortical excitability parameters, ALS Functional Rating Scale Revised, Montreal Cognitive Assessment, and Addenbrooke's Cognitive Examination-Revised scores.

CONCLUSIONS

Visual cortex is affected, and the occipital excitability is reduced in ALS, without any relation to motor cortical excitability changes, providing another clue suggestive of sensory involvement in ALS.

Resting State Functional Connectivity Is Decreased Globally Across the C9orf72 Mutation Spectrum

A repeat expansion mutation in the C9orf72 gene causes amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), or symptoms of both, and has been associated with gray and white matter changes in brain MRI scans. We used graph theory to examine the network properties of brain function at rest in a population of mixed-phenotype C9orf72 mutation carriers (C9+). Twenty-five C9+ subjects (pre-symptomatic, or diagnosed with ALS, behavioral variant FTD (bvFTD), or both ALS and FTD) and twenty-six healthy controls underwent resting state fMRI. When comparing all C9+ subjects with healthy controls, both global and connection-specific decreases in resting state connectivity were observed, with no substantial reorganization of network hubs. However, when analyzing subgroups of the symptomatic C9+ patients, those with bvFTD (with and without comorbid ALS) show remarkable reorganization of hubs compared to patients with ALS alone (without bvFTD), indicating that subcortical regions become more connected in the network relative to other regions. Additionally, network connectivity measures of the right hippocampus and bilateral thalami increased with increasing scores on the Frontal Behavioral Inventory, indicative of worsening behavioral impairment. These results indicate that while C9orf72 mutation carriers across the ALS-FTD spectrum have global decreased resting state brain connectivity, phenotype-specific effects can also be observed at more local network levels.

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.

Dynamic alterations of spontaneous neural activity in patients with amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a multi-system disease featured by movement disorder. Studies on ALS using static neuroimaging indexes demonstrated inconsistent results. However, recent work indicated that the intrinsic brain activity was time-varying, and the abnormal temporal dynamics of brain activity in ALS remains unknown. Resting-state functional magnetic resonance imaging data were first obtained from 54 patients with ALS and 54 healthy controls (HCs). Then the dynamic regional homogeneity (d-ReHo) was calculated and compared between the two groups. Correlation analyses between altered d-ReHo and clinical scores were further performed. Compared with HCs, ALS patients showed higher d-ReHo in the left lingual gyrus while lower d-ReHo in the left rectus gyrus and left parahippocampal gyrus. Moreover, the d-ReHo in the left lingual gyrus exhibited correlation with disease progression rate in ALS at a trend level. Our findings suggested that altered dynamics in intrinsic brain activity might be a potential biomarker for diagnosing of ALS.

Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study

OBJECTIVE

Advanced neuroimaging techniques may offer the potential to monitor disease spreading in amyotrophic lateral sclerosis (ALS). We aim to investigate brain functional and structural magnetic resonance imaging (MRI) changes in a cohort of ALS patients, examined at diagnosis and clinically monitored over 18 months, in order to early discriminate fast progressors (FPs) from slow progressors (SPs). Methods: Resting state functional MRI (RS-fMRI), diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) analyses were performed at baseline in 54 patients with ALS and 22 HCs. ALS patients were classified a posteriori into FPs (n = 25) and SPs (n = 29) based on changes in Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score from baseline to the 18-month assessment (ΔALSFRS-R), applying a k-means clustering algorithm. Results: At diagnosis, when compared to HCs, ALS patients showed reduced functional connectivity in both motor and extra-motor networks. When compared to SPs, at baseline, FPs showed decreased function connectivity in paracentral lobule (sensorimotor network), precuneus (in the default mode network), middle frontal gyri (frontoparietal networks) and increased functional connectivity in insular cortices (salience network). Structural analyses did not reveal significant differences in gray and white matter damage by comparing FPs to SPs. Receiver operating characteristic (ROC) curve analysis showed that functional connectivity increase in the left insula at baseline best discriminated FPs and SPs (area under the curve 78%). Conclusions: Impairment of extra-motor networks may appear early in ALS patients with faster disease progression, suggesting that a more widespread functional connectivity damage may be an indicator of poorer prognosis.

Involvement of the dentate nucleus in the pathophysiology of amyotrophic lateral sclerosis: A multi-center and multi-modal neuroimaging study

•

This original research article highlights cerebellar structural and functional connectivity abnormalities implicated in the pathophysiology of ALS.

•

In this study, resting-state functional MRI (rs-FMRI), diffusion tensor imaging (DTI), and 3D T1W structural images were examined.

•

Functional connectivity was investigated between the cerebral cortex and cerebellum targeting the dentate nucleus (DN).

•

Microstructural white matter diffusivity was examined along the cerebellar peduncles connecting the DN with the cerebral cortex and brain stem.

•

Grey matter volumes of the cerebellar lobules and DN were determined.

•

Overall, we provide evidence supporting involvement of the DN and associated cerebellar white matter tracts in the pathophysiology of ALS.

Amyotrophic lateral sclerosis (ALS) is characterized primarily by motor neuron but also frontotemporal lobar degeneration. Although the cerebellum is involved in both motor and cognitive functions, little is known of its role in ALS. We targeted the dentate nucleus (DN) in the cerebellum and the associated white matter fibers tracts connecting the DN to the rest of the brain using multimodal imaging techniques to examine the cerebellar structural and functional connectivity patterns in ALS patients and hypothesized that the DN is implicated in the pathophysiology of ALS. A cohort of 127 participants (56 healthy subjects (HS); 71 ALS patients) were recruited across Canada through the Canadian ALS Neuroimaging Consortium (CALSNIC). Resting state functional MRI, diffusion tensor imaging (DTI), and 3D weighted T1 structural images were acquired on a 3-tesla scanner. The DN in the cerebellum was used as a seed to evaluate the whole brain cerebral resting-state functional connectivity (rsFC). The superior cerebellar peduncle (SCP), middle cerebellar peduncle (MCP) and inferior cerebellar peduncle (ICP) were used as a region of interest in DTI to evaluate the structural integrity of the DN with the cortex and brain stem. Cerebellar volumetric analysis was done to examine the lobular and DN grey matter (GM) changes in ALS patients. Lastly, an association between DN rsFC and structural alterations were explored. DN rsFC was reduced with cerebrum (supplementary motor area, precentral gyrus, frontal, posterior parietal, temporal), lobule IV, and brain stem, and increased with parieto-occipital region. DN rsFC and white matter (WM) diffusivity alterations at SCP, MCP, and ICP were accompanied by correlations with ALSFRS-R. There were no DN volumetric changes. Notably, DN rsFC correlated with WM abnormalities at superior cerebellar peduncle. The DN plays a pathophysiological role in ALS. Impaired rsFC is likely due to the observed cerebellar peduncular WM damage given the lack of GM atrophy of the DN. This study demonstrates altered cerebellar rsFC connectivity with motor and extra-motor regions in ALS, and impaired rsFC is likely due to the observed cerebellar peduncular WM damage given the lack of GM atrophy of the DN. The correlation between the altered DN connectivity, and the behavioral data support the hypothesis that the DN plays a pathophysiological role in ALS.

Semantic deficits in ALS related to right lingual/fusiform gyrus network involvement

BACKGROUND

The clinicopathological continuity between amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) is well known. Although ALS demonstrates language symptoms similar to FTLD, including semantic dementia, word reading impairments in ALS have not been well studied. "Jukujikun" are Kanji-written words with irregular pronunciation comparable to "exception words" and useful for detecting semantic deficits in Japan. We conducted a cross-sectional study to investigate Jukujikun reading impairments and related network changes in ALS.

METHODS

We enrolled 71 ALS patients and 69 healthy controls (HCs). Age-, sex-, and education matched HCs were recruited from another cohort study concurrently with patient registration. We examined neuropsychological factors including low frequency Jukujikun reading. We performed resting-state functional magnetic resonance imaging with voxel-based graph analysis on a subset of participants who agreed.

FINDINGS

Low frequency Jukujikun score was decreased in ALS (15·0[11·0-19·0](median[25-75 percentile])) compared with HCs (19·0[17·3-20·0]) (p < 0·001, effect size = 0·43). Fifty-two percent of ALS (N = 37) with low frequency Jukujikun score ≤ 5th percentile of HCs was classified as ALS with positive Jukujikun deficit (ALS-JD+). Compared with HCs, ALS-JD+ showed decreased degree centrality in the right lingual/fusiform gyrus, where connectivities with regions associated with word perception, semantic processing, or speech production were decreased. They also showed increased degree centrality in the left inferior/middle temporal gyrus, associated with increased connectivities involving semantic processing.

INTERPRETATION

Dysfunction of the "hub" in the right lingual/fusiform gyrus can affect semantic deficit in ALS. Considering neuropsychological symptoms as network impairments is vital for understanding various diseases. FUND: MHLW and MEXT, Japan.

Differential tractography as a track-based biomarker for neuronal injury

Diffusion MRI tractography has been used to map the axonal structure of the human brain, but its ability to detect neuronal injury is yet to be explored. Here we report differential tractography, a new type of tractography that utilizes repeat MRI scans and a novel tracking strategy to map the exact segment of fiber pathways with a neuronal injury. We examined differential tractography on multiple sclerosis, Huntington's disease, amyotrophic lateral sclerosis, and epileptic patients. The results showed that the affected pathways shown by differential tractography matched well with the unique clinical symptoms of the patients, and the false discovery rate of the findings could be estimated using a sham setting to provide a reliability measurement. This novel approach enables a quantitative and objective method to monitor neuronal injury in individuals, allowing for diagnostic and prognostic evaluation of brain diseases.

Structural and functional papez circuit integrity in amyotrophic lateral sclerosis

Cognitive impairment in amyotrophic lateral sclerosis (ALS) is heterogeneous but now recognized as a feature in non-demented patients and no longer exclusively attributed to executive dysfunction. However, despite common reports of temporal lobe changes and memory deficits in ALS, episodic memory has been less explored. In the current study, we examined how the Papez circuit-a circuit known to participate in memory processes-is structurally and functionally affected in ALS patients (n = 20) compared with healthy controls (n = 15), and whether these changes correlated with a commonly used clinical measure of episodic memory. Our multimodal MRI approach (cortical volume, voxel-based morphometry, diffusion tensor imaging and resting state functional magnetic resonance) showed reduced gray matter in left hippocampus, left entorhinal cortex and right posterior cingulate as well as increased white matter fractional anisotropy and decreased mean diffusivity in the left cingulum bundle (hippocampal part) of ALS patients compared with controls. Interestingly, thalamus, mammillary bodies and fornix were preserved. Finally, we report a decreased functional connectivity in ALS patients in bilateral hippocampus, bilateral anterior and posterior parahippocampal gyrus and posterior cingulate. The results revealed that ALS patients showed statistically significant structural changes, but more important, widespread prominent functional connectivity abnormalities across the regions comprising the Papez circuit. The decreased functional connectivity found in the Papez network may suggest these changes could be used to assess risk or assist early detection or development of memory symptoms in ALS patients even before structural changes are established.

Strong-Weak Pruning for Brain Network Identification in Connectome-Wide Neuroimaging: Application to Amyotrophic Lateral Sclerosis Disease Stage Characterization

Magnetic resonance imaging allows acquiring functional and structural connectivity data from which high-density whole-brain networks can be derived to carry out connectome-wide analyses in normal and clinical populations. Graph theory has been widely applied to investigate the modular structure of brain connections by using centrality measures to identify the "hub" of human connectomes, and community detection methods to delineate subnetworks associated with diverse cognitive and sensorimotor functions. These analyses typically rely on a preprocessing step (pruning) to reduce computational complexity and remove the weakest edges that are most likely affected by experimental noise. However, weak links may contain relevant information about brain connectivity, therefore, the identification of the optimal trade-off between retained and discarded edges is a subject of active research. We introduce a pruning algorithm to identify edges that carry the highest information content. The algorithm selects both strong edges (i.e. edges belonging to shortest paths) and weak edges that are topologically relevant in weakly connected subnetworks. The newly developed "strong-weak" pruning (SWP) algorithm was validated on simulated networks that mimic the structure of human brain networks. It was then applied for the analysis of a real dataset of subjects affected by amyotrophic lateral sclerosis (ALS), both at the early (ALS2) and late (ALS3) stage of the disease, and of healthy control subjects. SWP preprocessing allowed identifying statistically significant differences in the path length of networks between patients and healthy subjects. ALS patients showed a decrease of connectivity between frontal cortex to temporal cortex and parietal cortex and between temporal and occipital cortex. Moreover, degree of centrality measures revealed significantly different hub and centrality scores between patient subgroups. These findings suggest a widespread alteration of network topology in ALS associated with disease progression.

Tracking a Fast-Moving Disease: Longitudinal Markers, Monitoring, and Clinical Trial Endpoints in ALS

Amyotrophic lateral sclerosis (ALS) encompasses a heterogeneous group of phenotypes with different progression rates, varying degree of extra-motor involvement and divergent progression patterns. The natural history of ALS is increasingly evaluated by large, multi-time point longitudinal studies, many of which now incorporate presymptomatic and post-mortem assessments. These studies not only have the potential to characterize patterns of anatomical propagation, molecular mechanisms of disease spread, but also to identify pragmatic monitoring markers. Sensitive markers of progressive neurodegenerative change are indispensable for clinical trials and individualized patient care. Biofluid markers, neuroimaging indices, electrophysiological markers, rating scales, questionnaires, and other disease-specific instruments have divergent sensitivity profiles. The discussion of candidate monitoring markers in ALS has a dual academic and clinical relevance, and is particularly timely given the increasing number of pharmacological trials. The objective of this paper is to provide a comprehensive and critical review of longitudinal studies in ALS, focusing on the sensitivity profile of established and emerging monitoring markers.

Regional Dynamics of the Resting Brain in Amyotrophic Lateral Sclerosis Using Fractional Amplitude of Low-Frequency Fluctuations and Regional Homogeneity Analyses

Resting-state functional magnetic resonance imaging has been playing an important role in the study of amyotrophic lateral sclerosis (ALS). Although functional connectivity is widely studied, the patterns of spontaneous neural activity of the resting brain are important mechanisms that have been used recently to study a variety of conditions but remain less explored in ALS. Here we have used fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) to study the regional dynamics of the resting brain of nondemented ALS patients compared with healthy controls. As expected, we found the sensorimotor network with changes in fALFF and ReHo, and also found the default mode network (DMN), frontoparietal network (FPN), and salience network (SN) altered and the cerebellum, although no structural changes between ALS patients and controls were reported in the regions with fALFF and ReHo changes. We show an altered pattern in the spontaneous low-frequency oscillations that is not confined to the motor areas and reveal a more widespread involvement of nonmotor regions, including those responsible for cognition.

The changing landscape of motor neuron disease imaging: the transition from descriptive studies to precision clinical tools

PURPOSE OF REVIEW

Neuroimaging in motor neuron disease (MND) has traditionally been seen as an academic tool with limited direct relevance to individualized patient care. This has changed radically in recent years as computational imaging has emerged as a viable clinical tool with true biomarker potential. This transition is not only fuelled by technological advances but also by important conceptual developments.

RECENT FINDINGS

The natural history of MND is now evaluated by presymptomatic, postmortem and multi-timepoint longitudinal imaging studies. The anatomical spectrum of MND imaging has also been expanded from an overwhelmingly cerebral focus to innovative spinal and muscle applications. In contrast to the group-comparisons of previous studies, machine-learning and deep-learning approaches are increasingly utilized to model real-life diagnostic dilemmas and aid prognostic classification. The focus from evaluating focal structural changes has shifted to the appraisal of network integrity by connectivity-based approaches. The armamentarium of MND imaging has also been complemented by novel PET-ligands, spinal toolboxes and the availability of magnetoencephalography and high-field magnetic resonance (MR) imaging platforms.

SUMMARY

In addition to the technological and conceptual advances, collaborative multicentre research efforts have also gained considerable momentum. This opinion-piece reviews emerging trends in MND imaging and their implications to clinical care and drug development.

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.

Abnormal topological organization of structural covariance networks in amyotrophic lateral sclerosis

Neuroimaging studies of patients with amyotrophic lateral sclerosis (ALS) have shown widespread alterations in structure, function, and connectivity in both motor and non-motor brain regions, suggesting multi-systemic neurobiological abnormalities that might impact large-scale brain networks. Here, we examined the alterations in the topological organization of structural covariance networks of ALS patients (N = 60) compared with normal controls (N = 60). We found that structural covariance networks of ALS patients showed a consistent rearrangement towards a regularized architecture evidenced by increased path length, clustering coefficient, small-world index, and modularity, as well as decreased global efficiency, suggesting inefficient global integration and increased local segregation. Locally, ALS patients showed decreased nodal degree and betweenness in the gyrus rectus and/or Heschl's gyrus, and increased betweenness in the supplementary motor area, triangular part of the inferior frontal gyrus, supramarginal gyrus and posterior cingulate cortex. In addition, we identified a different number and distribution of hubs in ALS patients, showing more frontal and subcortical hubs than in normal controls. In conclusion, we reveal abnormal topological organization of structural covariance networks in ALS patients, and provide network-level evidence for the concept that ALS is a multisystem disorder with a cerebral involvement extending beyond the motor areas.

Abnormal Functional Connectivity Density in Amyotrophic Lateral Sclerosis

Purpose: Amyotrophic lateral sclerosis (ALS) is a motor neuro-degenerative disorder that also damages extra-motor neural pathways. A significant proportion of existing evidence describe alterations in the strengths of functional connectivity, whereas the changes in the density of these functional connections have not been explored. Therefore, our study seeks to identify ALS-induced alternations in the resting-state functional connectivity density (FCD).

Methods: Two groups comprising of 38 ALS patients and 35 healthy participants (age and gender matched) were subjected to the resting-state functional magnetic resonance imaging (MRI) scanning. An ultra-fast graph theory method known as FCD mapping was utilized to calculate the voxel-wise short- and long-range FCD values of the brain for each participant. FCD values of patients and controls were compared based on voxels in order to discern cerebral regions that possessed significant FCD alterations. For areas demonstrating a group effect of atypical FCD in ALS, seed-based functional connectivity analysis was then investigated. Partial correlation analyses were carried out between aberrant FCDs and several clinical variables, controlling for age, gender, and total intracranial volume.

Results: Patients with ALS were found to have decreased short-range FCD in the primary motor cortex and increased long-range FCD in the premotor cortex. Extra-motor areas that also displayed extensive FCD alterations encompassed the temporal cortex, insula, cingulate gyrus, occipital cortex, and inferior parietal lobule. Seed-based correlation analysis further demonstrated that these regions also possessed disrupted functional connectivity. However, no significant correlations were identified between aberrant FCDs and clinical variables.

Conclusion: FCD changes in the regions identified represent communication deficits and impaired functional brain dynamics, which might underlie the motor, motor control, language, visuoperceptual and high-order cognitive deficits in ALS. These findings support the fact that ALS is a disorder affecting multiple systems. We gain a deeper insight of the neural mechanisms underlying ALS.

The Clinical and Radiological Spectrum of Hippocampal Pathology in Amyotrophic Lateral Sclerosis

Hippocampal pathology in Amyotrophic Lateral Sclerosis (ALS) remains surprisingly under recognized despite compelling evidence from neuropsychology, neuroimaging and neuropathology studies. Hippocampal dysfunction contributes significantly to the clinical heterogeneity of ALS and requires structure-specific cognitive and neuroimaging tools for accurate in vivo evaluation. Recent imaging studies have generated unprecedented insights into the presymptomatic and longitudinal processes affecting this structure and have contributed to the characterisation of both focal and network-level changes. Emerging neuropsychology data suggest that memory deficits in ALS may be independent from executive dysfunction. In the era of precision medicine, where the development of individualized care strategies and patient stratification for clinical trials are key priorities, the comprehensive review of hippocampal dysfunction in ALS is particularly timely.

Dissecting the pathobiology of altered MRI signal in amyotrophic lateral sclerosis: A post mortem whole brain sampling strategy for the integration of ultra-high-field MRI and quantitative neuropathology

BACKGROUND

Amyotrophic lateral sclerosis (ALS) is a clinically and histopathologically heterogeneous neurodegenerative disorder, in which therapy is hindered by the rapid progression of disease and lack of biomarkers. Magnetic resonance imaging (MRI) has demonstrated its potential for detecting the pathological signature and tracking disease progression in ALS. However, the microstructural and molecular pathological substrate is poorly understood and generally defined histologically. One route to understanding and validating the pathophysiological correlates of MRI signal changes in ALS is to directly compare MRI to histology in post mortem human brains.

RESULTS

The article delineates a universal whole brain sampling strategy of pathologically relevant grey matter (cortical and subcortical) and white matter tracts of interest suitable for histological evaluation and direct correlation with MRI. A standardised systematic sampling strategy that was compatible with co-registration of images across modalities was established for regions representing phosphorylated 43-kDa TAR DNA-binding protein (pTDP-43) patterns that were topographically recognisable with defined neuroanatomical landmarks. Moreover, tractography-guided sampling facilitated accurate delineation of white matter tracts of interest. A digital photography pipeline at various stages of sampling and histological processing was established to account for structural deformations that might impact alignment and registration of histological images to MRI volumes. Combined with quantitative digital histology image analysis, the proposed sampling strategy is suitable for routine implementation in a high-throughput manner for acquisition of large-scale histology datasets. Proof of concept was determined in the spinal cord of an ALS patient where multiple MRI modalities (T1, T2, FA and MD) demonstrated sensitivity to axonal degeneration and associated heightened inflammatory changes in the lateral corticospinal tract. Furthermore, qualitative comparison of R2* and susceptibility maps in the motor cortex of 2 ALS patients demonstrated varying degrees of hyperintense signal changes compared to a control. Upon histological evaluation of the same region, intensity of signal changes in both modalities appeared to correspond primarily to the degree of microglial activation.

CONCLUSION

The proposed post mortem whole brain sampling methodology enables the accurate intraindividual study of pathological propagation and comparison with quantitative MRI data, to more fully understand the relationship of imaging signal changes with underlying pathophysiology in ALS.