Patterned functional network disruption in amyotrophic lateral sclerosis

Abstract

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.

Keywords: EEG; amyotrophic lateral sclerosis; functional connectivity; motor neurone disease; resting state; source localisation.

Figure 1

In amyotrophic lateral sclerosis (ALS), spectral power is significantly decreased between δ and β frequency bands. Notice the dominant decrease in the posterior and temporal regions. Statistical difference between healthy controls (n = 47) and ALS patients (n = 74) was assessed in the six defined frequency bands using empirical Bayesian inference (EBI). False discovery rate (FDR) was set to 10%, yielding an estimated statistical power of 1–β = .82 and posterior probability of P ₁ = .64 (across all frequency bands). AUC, area under the receiver operating characteristic curve. No changes were detected in the γ frequency bands; therefore, they are not shown. Frequency bands: δ (2–4 Hz), θ (5–7 Hz), α (8–13 Hz) and β (14–30 Hz) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

In amyotrophic lateral sclerosis (ALS), the average co‐modulation is significantly increased in the δ, θ and γ frequency bands. Notice the increase of amplitude envelope correlation (AEC) in the central and posterior regions (δ‐, θ‐ and γ_l‐band) and frontal regions (δ‐ and γ_l‐band). Statistical difference between healthy controls (n = 47) and ALS patients (n = 74) was assessed in the six defined frequency bands using empirical Bayesian inference (EBI). False discovery rate (FDR) was set to 10%, yielding an estimated statistical power of 1–β = .93 and posterior probability of P ₁ = .71 (across all frequency bands). AUC, area under the receiver operating characteristic curve. Frequency bands: δ (2–4 Hz), θ (5–7 Hz), α (8–13 Hz), β (14–30 Hz) and γ (γ_l: 31–47 Hz, γ_h: 53–97 Hz) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

In amyotrophic lateral sclerosis (ALS), the average synchrony is significantly decreased in the δ and β frequency bands. Notice the decrease of imaginary coherence (iCoh) in temporal and frontal lobes (δ‐, θ‐ and α‐band), and in the sensorimotor cortex (β‐band). Statistical difference between healthy controls (n = 47) and ALS patients (n = 74) was assessed in the six defined frequency bands using empirical Bayesian inference (EBI). False discovery rate (FDR) was set to 10%, yielding an estimated statistical power of 1–β = .55 and posterior probability of P ₁ = .77 (across all frequency bands). AUC, area under the receiver operating characteristic curve. No changes were detected in the γ frequency bands; therefore, they are not shown. Frequency bands: δ (2–4 Hz), θ (5–7 Hz), α (8–13 Hz) and β (14–30 Hz) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

The increase of point‐to‐point co‐modulation and the decrease of point‐to‐point synchrony have a widespread pattern in amyotrophic lateral sclerosis (ALS) patients. Note that the widespread patterns of increased co‐modulation [amplitude envelope correlation (AEC)] are predominantly in the θ‐ and γ_l‐bands, while synchrony [imaginary coherence (iCoh)] patterns were predominantly in the δ‐ and β‐bands. Statistical difference between healthy controls (n = 47) and ALS patients (n = 74) was assessed separately in the six defined frequency bands using empirical Bayesian inference (EBI). False discovery rate (FDR) was set to 10% (in each frequency band), yielding an estimated statistical power of 1–β = .96 and posterior probability of P ₁ = .56 in the θ‐band AEC and an estimated statistical power of 1–β = .89 and posterior probability of P ₁ = .7 in the γ_l‐band AEC. For synchrony measures, the 10% FDR threshold yielded an estimated statistical power of 1–β = .39 and posterior probability of P ₁ = .8 in the δ‐band iCoh and an estimated statistical power of 1–β = .16 and posterior probability of P ₁ = .83 in the β‐band iCoh. AUC, area under the receiver operating characteristic curve. No changes were detected in the other frequency bands; therefore, they are not shown. The abbreviations ‘Front’, ‘Cntr/Prtl’, ‘Occp’, ‘Tmp’ and ‘Subcort’ stand for frontal, central/parietal, occipital, temporal and subcortical, respectively. For the order of ROIs used in the connectivity matrix, see Figure S2, Supporting Information. Frequency bands: δ (2–4 Hz), θ (5–7 Hz), β (14–30 Hz) and γ_l (31–47 Hz) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 5

The connectivity modules reveal the (sub‐)network with frequency‐specific increase of co‐modulation and decrease of synchrony in amyotrophic lateral sclerosis (ALS). The factorised (sub‐)networks resemble the occipital network (a), motor loops of basal ganglia and/or thalamus (b), frontal network (c), sensorimotor network (d), frontoparietal network (e), frontotemporal network (f) and combined occipitofrontal and uncinate fasciculus (g). The connectivity modules from non‐negative matrix factorisation analysis of the affected co‐modulation or synchrony in ALS reveal the altered brain networks, while the changes in module's weights show the increase or decrease in the activity of these networks. Statistical analysis between ALS patients and healthy controls (n _c = 47 and n _p = 47) of the weights corresponding to the connectivity modules reached significance in all cases (marked with asterisk) as controlled by adaptive false discovery rate (aFDR) at q = 0.05. Frequency bands: δ (2–4 Hz), θ (5–7 Hz), β (14–30 Hz) and γ_l (31–47 Hz) [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 6

The observed electroencephalography (EEG) spectral power and connectivity changes are not different between amyotrophic lateral sclerosis (ALS) subgroups. The comparison shows the differences between healthy controls and ALS subgroups. Statistical difference between healthy controls and pooled ALS patients was assessed using Mann–Whitney U test, whereas statistical difference between patient subgroups was assessed using two‐way analysis of variance (ANOVA) in all three measures, each in two frequency bands with the most prominent changes (see Figures 1, 2, 3). None of the measures showed statistically significant difference among ALS subgroups. Spectral power data were log‐transformed for plotting purposes. The abbreviations ‘HC’, ‘SPN’, ‘BULB’, ‘C9‐’ and ‘C9+’ stand for healthy controls, spinal, bulbar, C9ORF72‐negative and C9ORF72‐postive, respectively. The number of ALS patients in each subgroup are N = 55, 15, 63 and 7, respectively. There are six C9ORF72‐postive patients in the spinal and one in the bulbar subgroup. Frequency bands: δ (2–4 Hz), θ (5–7 Hz) and β (14–30 Hz)

Figure 7

The changes in electroencephalography (EEG) connectivity correlate with the structural atrophy in MRI in the motor (a) and cognitive (b) networks, as well as measures of functional motor impairment [(c) amyotrophic lateral sclerosis Functional Rating Scale (ALSFRS‐R)], functional cognitive impairment [(d and e) standardised neuropsychological battery scores]. The values of r and p correspond to Spearman's partial correlation corrected for age (a–c) and Spearman's correlation (d and e), whereas 1‐β_0.05 represents statistical power at 0.05. The number of ALS patients used in the analyses are N = 37, 37, 61, 34 and 34, respectively. The shown p‐values are adaptive false discovery rate (aFDR) corrected at q = 0.05. Frequency bands: δ (2–4 Hz), θ (5–7 Hz), β (14–30 Hz) and γ_l (31–47 Hz) [Color figure can be viewed at http://wileyonlinelibrary.com]