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Amyotrophic lateral sclerosis (ALS) is characterised primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. We have shown previously that resting-state EEG captures dysfunction in motor and cognitive networks in ALS. However, the longitudinal development of these dysfunctional patterns, especially in networks linked with cognitive-behavioural functions, remains unclear. Longitudinal studies on non-motor changes in ALS are essential to further develop our understanding of disease progression, improve care and enhance the evaluation of new treatments. To address this gap, we examined 124 ALS individuals with 128-channel resting-state EEG recordings, categorised by cognitive impairment (ALSci, n = 25), behavioural impairment (ALSbi, n = 58), or non-impaired (ALSncbi, n = 53), with 12 participants meeting the criteria for both ALSci and ALSbi. Using linear mixed-effects models, we characterised the general and phenotype-specific longitudinal changes in brain network, and their association with cognitive performance, behaviour changes, fine motor symptoms, and survival. Our findings revealed a significant decline in [Formula: see text]-band spectral power over time in the temporal region along with increased [Formula: see text]-band power in the fronto-temporal region in the ALS group. ALSncbi participants showed widespread β-band synchrony decrease, while ALSci participants exhibited increased co-modulation correlated with verbal fluency decline. Longitudinal network-level changes were specific of ALS subgroups and correlated with motor, cognitive, and behavioural decline, as well as with survival. Spectral EEG measures can longitudinally track abnormal network patterns, serving as a candidate stratification tool for clinical trials and personalised treatments in ALS., (© 2024. The Author(s).)

Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently, we have shown that resting-state EEG can reliably and quantitatively capture abnormal patterns of motor and cognitive network disruption in amyotrophic lateral sclerosis. These network disruptions have been identified across multiple frequency bands, and using measures of neural activity (spectral power) and connectivity (comodulation of activity by amplitude envelope correlation and synchrony by imaginary coherence) on source-localized brain oscillations from high-density EEG. Using data-driven methods (similarity network fusion and spectral clustering), we have now undertaken a clustering analysis to identify disease subphenotypes and to determine whether different patterns of disruption are predictive of disease outcome. We show that amyotrophic lateral sclerosis patients (n = 95) can be subgrouped into four phenotypes with distinct neurophysiological profiles. These clusters are characterized by varying degrees of disruption in the somatomotor (α-band synchrony), frontotemporal (β-band neural activity and γl-band synchrony) and frontoparietal (γl-band comodulation) networks, which reliably correlate with distinct clinical profiles and different disease trajectories. Using an in-depth stability analysis, we show that these clusters are statistically reproducible and robust, remain stable after reassessment using a follow-up EEG session, and continue to predict the clinical trajectory and disease outcome. Our data demonstrate that novel phenotyping using neuroelectric signal analysis can distinguish disease subtypes based exclusively on different patterns of network disturbances. These patterns may reflect underlying disease neurobiology. The identification of amyotrophic lateral sclerosis subtypes based on profiles of differential impairment in neuronal networks has clear potential in future stratification for clinical trials. Advanced network profiling in amyotrophic lateral sclerosis can also underpin new therapeutic strategies that are based on principles of neurobiology and designed to modulate network disruption., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

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., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Objective: To localise and characterise changes in cognitive networks in Amyotrophic Lateral Sclerosis (ALS) using source analysis of mismatch negativity (MMN) waveforms., Rationale: The MMN waveform has an increased average delay in ALS. MMN has been attributed to change detection and involuntary attention switching. This therefore indicates pathological impairment of the neural network components which generate these functions. Source localisation can mitigate the poor spatial resolution of sensor-level EEG analysis by associating the sensor-level signals to the contributing brain sources. The functional activity in each generating source can therefore be individually measured and investigated as a quantitative biomarker of impairment in ALS or its sub-phenotypes., Methods: MMN responses from 128-channel electroencephalography (EEG) recordings in 58 ALS patients and 39 healthy controls were localised to source by three separate localisation methods, including beamforming, dipole fitting and exact low resolution brain electromagnetic tomography., Results: Compared with controls, ALS patients showed significant increase in power of the left posterior parietal, central and dorsolateral prefrontal cortices (false discovery rate = 0.1). This change correlated with impaired cognitive flexibility (rho = 0.45, 0.45, 0.47, p = .042, .055, .031 respectively). ALS patients also exhibited a decrease in the power of dipoles representing activity in the inferior frontal (left: p = 5.16 × 10 -6 , right: p = 1.07 × 10 -5 ) and left superior temporal gyri (p = 9.30 × 10 -6 ). These patterns were detected across three source localisation methods. Decrease in right inferior frontal gyrus activity was a good discriminator of ALS patients from controls (AUROC = 0.77) and an excellent discriminator of C9ORF72 expansion-positive patients from controls (AUROC = 0.95)., Interpretation: Source localization of evoked potentials can reliably discriminate patterns of functional network impairment in ALS and ALS subgroups during involuntary attention switching. The discriminative ability of the detected cognitive changes in specific brain regions are comparable to those of functional magnetic resonance imaging (fMRI). Source analysis of high-density EEG patterns has excellent potential to provide non-invasive, data-driven quantitative biomarkers of network disruption that could be harnessed as novel neurophysiology-based outcome measures in clinical trials., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Amyotrophic lateral sclerosis (ALS) is a terminal progressive adult-onset neurodegeneration of the motor system. Although originally considered a pure motor degeneration, there is increasing evidence of disease heterogeneity with varying degrees of extra-motor involvement. How the combined motor and nonmotor degeneration occurs in the context of broader disruption in neural communication across brain networks has not been well characterized. Here, we have performed high-density crossectional and longitudinal resting-state electroencephalography (EEG) recordings on 100 ALS patients and 34 matched controls, and have identified characteristic patterns of altered EEG connectivity that have persisted in longitudinal analyses. These include strongly increased EEG coherence between parietal-frontal scalp regions (in γ-band) and between bilateral regions over motor areas (in θ-band). Correlation with structural MRI from the same patients shows that disease-specific structural degeneration in motor areas and corticospinal tracts parallels a decrease in neural activity over scalp motor areas, while the EEG over the scalp regions associated with less extensively involved extra-motor regions on MRI exhibit significantly increased neural communication. Our findings demonstrate that EEG-based connectivity mapping can provide novel insights into progressive network decline in ALS. These data pave the way for development of validated cost-effective spectral EEG-based biomarkers that parallel changes in structural imaging.

Background: Amyotrophic lateral sclerosis (ALS) a highly heterogeneous neurodegenerative condition. Accurate diagnostic, monitoring and prognostic biomarkers are urgently needed both for individualised patient care and clinical trials. A multimodal magnetic resonance imaging study is presented, where MRI measures of ALS-associated brain regions are utilised to predict 18-month survival., Methods: A total of 60 ALS patients and 69 healthy controls were included in this study. 20% of the patient sample was utilised as an independent validation sample. Surface-based morphometry and diffusion tensor white matter parameters were used to identify anatomical patterns of neurodegeneration in 80% of the patient sample compared to healthy controls. Binary logistic ridge regressions were carried out to predict 18-month survival based on clinical measures alone, MRI features, and a combination of clinical and MRI data. Clinical indices included age at symptoms onset, site of disease onset, diagnostic delay from first symptom to diagnosis, and physical disability (ALSFRS-r). MRI features included the average cortical thickness of the precentral and paracentral gyri, the average fractional anisotropy, radial-, medial-, and axial diffusivity of the superior and inferior corona radiata, internal capsule, cerebral peduncles and the genu, body and splenium of the corpus callosum., Results: Clinical data alone had a survival prediction accuracy of 66.67%, with 62.50% sensitivity and 70.84% specificity. MRI data alone resulted in a prediction accuracy of 77.08%, with 79.16% sensitivity and 75% specificity. The combination of clinical and MRI measures led to a survival prediction accuracy of 79.17%, with 75% sensitivity and 83.34% specificity., Conclusion: Quantitative MRI measures of ALS-specific brain regions enhance survival prediction in ALS and should be incorporated in future clinical trial designs.

Background: Despite significant advances in quantitative neuroimaging, the diagnosis of ALS remains clinical and MRI-based biomarkers are not currently used to aid the diagnosis. The objective of this study is to develop a robust, disease-specific, multimodal classification protocol and validate its diagnostic accuracy in independent, early-stage and follow-up data sets., Methods: 147 participants (81 ALS patients and 66 healthy controls) were divided into a training sample and a validation sample. Patients in the validation sample underwent follow-up imaging longitudinally. After removing age-related variability, indices of grey and white matter integrity in ALS-specific pathognomonic brain regions were included in a cross-validated binary logistic regression model to determine the probability of individual scans indicating ALS. The following anatomical regions were assessed for diagnostic classification: average grey matter density of the left and right precentral gyrus, the average fractional anisotropy and radial diffusivity of the left and right superior corona radiata, inferior corona radiata, internal capsule, mesencephalic crus of the cerebral peduncles, pontine segment of the corticospinal tract, and the average diffusivity values of the genu, corpus and splenium of the corpus callosum., Results: Using a 50% probability cut-off value of suffering from ALS, the model was able to discriminate ALS patients and HC with good sensitivity (80.0%) and moderate accuracy (70.0%) in the training sample and superior sensitivity (85.7%) and accuracy (78.4%) in the independent validation sample., Conclusions: This diagnostic classification study endeavours to advance ALS biomarker research towards pragmatic clinical applications by providing an approach of automated individual-data interpretation based on group-level observations., Competing Interests: The authors have declared that no competing interests exist.

A large multiparametric MRI study has been undertaken to evaluate anatomical patterns of basal ganglia, white matter and cortical grey matter involvement in ALS. Unaffected brain regions are mapped in patients with significant disability. Multiple white matter diffusivity measures, cortical grey matter density alterations, basal ganglia volumes and subcortical grey matter atrophy patterns are evaluated. Results demonstrated a strikingly selective anatomical vulnerability pattern in ALS that preferentially affects specific grey matter structures, commissural white matter tracts and basal ganglia regions, suggestive of networkwise neurodegeneration in ALS. In conclusion, ALS pathology exhibits predilection for selective and inter-connected anatomical sites that can be comprehensively characterized in vivo by multiparametric neuroimaging. The systematic characterization of unaffected brain regions in ALS has implications for the development of classifier analyses and elucidation of disease biology. The involvement and sparing of contiguous brain regions raises important pathophysiological, phylogenetic and ontogenetic questions regarding ALS pathogenesis and disease spread.

Objective: Although a systematic spread of pathologic TDP-43 expression throughout the CNS in amyotrophic lateral sclerosis (ALS) has been proposed, the relationship between cognition and the extent and neuroanatomic distribution of TDP-43 pathology has not received considerable attention., Methods: We investigated the association between cognitive functioning and the extent of TDP-43 pathology in postmortem CNS tissue from 18 patients with ALS stratified into 3 groups based on detailed prospective neuropsychological testing (cognitively not impaired, n = 6; cognitively impaired, n = 6; ALS- frontotemporal dementia [FTD], n = 6) and analyzed these cases for clinicopathologic correlations., Results: Our findings demonstrate a close relationship between cognition and the extent of TDP-43 pathology in non-primary motor areas with a striking difference between ALS-FTD and the 2 other cognitive groups. The specificity of our results was underscored by 2 key findings: first, the absence of an Alzheimer pathology effect, a common confounder in older patients; second, the lack of correlations between the primary motor regions with the highest TDP-43 intensity and cognitive status., Conclusions: Our data suggest a distinct dynamic of TDP-43 progression and distribution in ALS-FTD in contrast to ALS without FTD., (© 2016 American Academy of Neurology.)

Background and Purpose: Magnetic resonance diffusivity indices have been repeatedly proposed as biomarkers of neurodegeneration in amyotrophic lateral sclerosis (ALS), but no consensus exists as to which diffusivity parameter is the most sensitive to identify early degenerative changes. Despite numerous studies, surprisingly little is known of the segmental vulnerability of the corticospinal tracts and corpus callosum. Our objective was to characterize the core three-dimensional white matter signature of ALS, to describe phenotype-specific patterns of white matter degeneration and to evaluate the diffusivity profile of individual patients and controls in specific white matter segments., Methods: A large neuroimaging study was undertaken with 62 patients and 55 age-matched healthy controls. White matter alterations were explored based on fractional anisotropy and radial, mean and axial diffusivity indices. Atlas-based region of interest analyses were carried out in the corona radiata, internal capsules, cerebral peduncles, and in the splenium, body and genu of the corpus callosum. Percentage change and receiver operating characteristic (ROC) curves were used to characterize disease-state discriminating diffusivity measures and white matter regions., Results: Bulbar onset patients exhibit extensive corticobulbar tract involvement in the genu of the internal capsule and in the lateral fibres of the corona radiata subjacent to the bulbar representation of the motor homunculus. Spinal onset patients show predominantly posterior internal capsule involvement and medial corona radiata pathology. ROC curve analyses revealed that diffusivity measures of the cerebral crura best discriminate patients and controls (area under the curve 80.1%)., Conclusions: Amyotrophic lateral sclerosis is associated with a core, disease-specific three-dimensional white matter signature which is best demonstrated by radial diffusivity measurements. The main ALS motor phenotypes are manifestations of the relatively selective involvement of corticospinal and corticobulbar fibres., (© 2016 EAN.)

Background/aims: A substantial proportion of amyotrophic lateral sclerosis (ALS) patients develop cognitive impairments. Longitudinal investigations of cognition in ALS have shown mixed results. While some authors report that cognitive performance remains stable as the disease progresses, others have found evidence for deterioration in various domains. Our objective was to investigate cognitive performance in ALS longitudinally, using the example of executive functions., Methods: 93 ALS patients and 73 age-, sex- and education-matched healthy controls underwent up to four neuropsychological evaluations, separated by 3- to 6-month intervals. We examined whether performance declined longitudinally on seven tests assessing various sub-components of executive functioning. Furthermore, we assigned an executive-performance-based 'cognitive status' to each participant for every evaluation, examining whether cognitive deterioration (if present) was modulated by their baseline cognitive status and whether cognitive status changed over time., Results: Regardless of their cognitive status at baseline, ALS patients showed no significant decline in the sub-components of executive functioning., Conclusion: Our findings imply that the executive deficits which develop in some ALS patients emerge before motor symptoms and remain stable after an initial decline. The discrepancy between this trajectory and the progressive decline in motor functions may result from a differential vulnerability of motor and non-motor prefrontal neurons to the pathomechanism of ALS., (© 2015 S. Karger AG, Basel.)

Pronounced cognitive and behavioural impairments in amyotrophic lateral sclerosis (ALS) concern executive functions and executive behaviour. The valid measurement is challenging as motor disabilities may mask everyday functioning. The aim of this study was to determine a detailed characteristic pattern of executive impairment in ALS in order to effectively interpret their clinical impact. We investigated 98 ALS patients without or with frontotemporal dementia (FTD), and 70 healthy controls using a comprehensive neuropsychological test battery focusing on executive functions and executive behaviour. We analysed the impairment of executive functions and their clinical significance for patients' daily routines. Results demonstrated that around 70% of cognitively impaired ALS patients without FTD showed disturbances in executive functioning. Behavioural abnormalities primarily manifested in symptoms of apathy. Patients without FTD were most impaired in the executive domain regarding initiation and shifting; this contrasted their almost preserved processes relating to updating, inhibition, and complex problem solving. ALS-FTD patients showed deficits in all analysed processes. Our study suggests that executive dysfunctioning in cognitively impaired ALS patients without FTD does not preferentially affect the more complex regulatory processes. These findings indicate potential mechanisms for ALS patients to compensate for executive dysfunction in daily routine.

Background: A relevant fraction of patients with amyotrophic lateral sclerosis (ALS) exhibit a fronto-temporal pattern of cognitive and behavioural disturbances with pronounced deficits in executive functioning and cognitive control of behaviour. Structural imaging shows a decline in fronto-temporal brain areas, but most brain imaging studies did not evaluate cognitive status. We investigated microstructural white matter changes underlying cognitive impairment using diffusion tensor imaging (DTI) in a large cohort of ALS patients., Methods: We assessed 72 non-demented ALS patients and 65 matched healthy control subjects using a comprehensive neuropsychological test battery and DTI. We compared DTI measures of fiber tract integrity using tract-based spatial statistics among ALS patients with and without cognitive impairment and healthy controls. Neuropsychological performance and behavioural measures were correlated with DTI measures., Results: Patients without cognitive impairment demonstrated white matter changes predominantly in motor tracts, including the corticospinal tract and the body of corpus callosum. Those with impairments (ca. 30%) additionally presented significant white matter alterations in extra-motor regions, particularly the frontal lobe. Executive and memory performance and behavioural measures were correlated with fiber tract integrity in large association tracts., Conclusion: In non-demented cognitively impaired ALS patients, white matter changes measured by DTI are related to disturbances of executive and memory functions, including prefrontal and temporal regions. In a group comparison, DTI is able to observe differences between cognitively unimpaired and impaired ALS patients.

To determine longitudinal rates of cortical atrophy in classical Amyotrophic lateral sclerosis (ALS) and ALS variants. Rates of cortical thinning were determined between 2 scans, 3-15 months apart, in 77 ALS patients: 51 classical, 12 upper motor neuron (UMN), and 14 lower motor neuron (LMN) ALS variants. Cortical thickness at the first assessment was compared with 60 healthy controls matched by age and gender. Atrophy rates were compared between patient sub-groups and correlated with disease duration, progression, and severity. Using a cross-sectional analysis, we found a significant difference in cortical thickness between ALS patients and controls in the motor and extra-motor areas (left medial orbito frontal gyrus, left inferior parietal gyrus, bilateral insular cortex, right fusiform gyrus, bilateral precuneus). Using a longitudinal analysis, we found a significant decline of cortical thickness in frontal, temporal, and parietal regions over the course of the study in ALS patients. Effects were independent of the clinical subtype, with exception of the precentral gyrus (p < 0.001). The LMN ALS variants demonstrated the highest rates of cortical thinning in the precentral gyrus, the UMN-dominant subjects exhibited intermediate rates of atrophy, and the classical ALS patients exhibited no such change. Atrophy of the precentral gyrus in classical ALS indicates a floor effect at the first assessment, resulting in a lack of further atrophy over time. Structural loss of the precentral gyrus appears to be an early sign of classical ALS. Over time, patterns of cortical thinning in extra-motor areas can be identified in ALS, regardless of the phenotype.

Background: Recent work suggests that ALS and frontotemporal dementia can occur together and share at least in part the same underlying pathophysiology. However, it is unclear at present whether memory deficits in ALS stem from a temporal lobe dysfunction, or are rather driven by frontal executive dysfunction. In this study we sought to investigate the nature of memory deficits by analyzing the neuropsychological performance of 40 ALS patients in comparison to 39 amnestic mild cognitive impairment (aMCI) patients and 40 healthy controls (HC). The neuropsychological battery tested for impairment in executive functions, as well as memory and visuo-spatial skills, the results of which were compared across study groups. In addition, we calculated composite scores for memory (learning, recall, recognition) and executive functions (verbal fluency, cognitive flexibility, working memory). We hypothesized that the nature of memory impairment in ALS will be different from those exhibited by aMCI patients., Results: Patient groups exhibited significant differences in their type of memory deficit, with the ALS group showing impairment only in recognition, whereas aMCI patients showed short and delayed recall performance deficits as well as reduced short-term capacity. Regression analysis revealed a significant impact of executive function on memory performance exclusively for the ALS group, accounting for one fifth of their memory performance. Interestingly, merging all sub scores into a single memory and an executive function score obscured these differences., Conclusion: The presented results indicate that the interpretation of neuropsychological scores needs to take the distinct cognitive profiles in ALS and aMCI into consideration. Importantly, the observed memory deficits in ALS were distinctly different from those observed in aMCI and can be explained only to some extent in the context of comorbid (coexisting) executive dysfunction. These findings highlight the qualitative differences in temporal lobe dysfunction between ALS and aMCI patients, and support temporal lobe dysfunction as a mechanism underlying the distinct cognitive impairments observed in ALS.

Clinical, genetic, and pathological findings suggest a close relationship between amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). We studied the patterns of cortical atrophy across the spectrum between ALS and ALS-FTD. A surface-based morphometry analysis based on an age- and sex-matched sample of 81 ALS patients and 62 healthy control subjects (HC) was conducted. In addition, we used an age-matched subsample of 57 ALS patients and 31 HC to compare cortical thickness between 3 groups of neuropsychologically characterized ALS patients: (1) cognitively unimpaired; (2) cognitively impaired; and (3) ALS-FTD patients. Compared with HC, the entire sample of patients demonstrated cortical thinning in the bilateral precentral gyrus, right precuneus, and right frontal and temporal lobes. ALS-FTD patients showed cortical thinning in regions including the frontal and temporal gyri and the posterior cingulate cortex. Cognitively impaired ALS patients showed cortical thinning in regions largely overlapping with those found in ALS-FTD, but changes were less widespread. In conclusion, the cognitive status of ALS subjects is associated with different patterns of cortical atrophy., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Amyotrophic lateral sclerosis (ALS) is characterised by degeneration of upper (UMN) and lower motor neurons (LMN).We aimed to relate clinical variables to cortical thinning of the primary motor cortex (PMC). The PMC was defined as the region of interest in high-resolution structural MRI scans. We related vertex-wise measures of cortical thinning to UMN involvement, bulbar/limb onset, the total ALS functional rating scale (ALSFRS-R), and its bulbar and upper limb subscore. In total, 93 ALS patients were recruited (60 with classical ALS; 17 with dominant UMN, e.g., primary lateral sclerosis; 16 with pure LMN variant, e.g., progressive muscular atrophy, flail arm or leg syndrome) and compared to 67 age and gender matched healthy controls. The UMN signs in the bulbar regions were associated with bilateral thinning within the bulbar segment on the motor cortex, and UMN signs in spinal regions were associated with thinning in the limb segment of the motor cortex. The site of disease onset (bulbar/lower limb) exhibited the most pronounced thinning in the corresponding part of the motor cortex. According to our analysis, dominant UMN patients demonstrated the most distinct thinning followed by classical ALS patients. Pure LMN variants did not differ from healthy controls. The bulbar subscore of the ALSFRS-R correlated with thinning of the left inferior PMC. Focal morphological changes within the PMC correspond to clinically measured impairments and depend on disease phenotype. Measuring cortical thickness may potentially offer an objective in vivo marker to quantify disease pathology.