Alzheimer’s disease (AD) is a neurodegenerative disorder with high prevalence, known for its highly disabling symptoms. The aim of this study was to characterize the alterations in the irregularity and the complexity of the brain activity along the AD continuum. Both irregularity and complexity can be studied applying entropy-based measures throughout multiple temporal scales. In this regard, multiscale sample entropy (MSE) and refined multiscale spectral entropy (rMSSE) were calculated from electroencephalographic (EEG) data. Five minutes of resting-state EEG activity were recorded from 51 healthy controls, 51 mild cognitive impaired (MCI) subjects, 51 mild AD patients (ADMIL), 50 moderate AD patients (ADMOD), and 50 severe AD patients (ADSEV). Our results show statistically significant differences (p-values < 0.05, FDR-corrected Kruskal–Wallis test) between the five groups at each temporal scale. Additionally, average slope values and areas under MSE and rMSSE curves revealed significant changes in complexity mainly for controls vs. MCI, MCI vs. ADMIL and ADMOD vs. ADSEV comparisons (p-values < 0.05, FDR-corrected Mann–Whitney U-test). These findings indicate that MSE and rMSSE reflect the neuronal disturbances associated with the development of dementia, and may contribute to the development of new tools to track the AD progression.

Objective. The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due to Alzheimer’s disease (AD). Approach. Magnitude squared coherence (MSCOH), imaginary part of coherence (iCOH), lagged coherence (lagCOH), amplitude envelope correlation (AEC), synchronization likelihood (SL), phase lag index (PLI), phase locking value (PLV), and corrected imaginary PLV (ciPLV) were applied to: (i) synthetic signals generated with a Kuramoto-based model of several coupled oscillators; and (ii) a resting-state EEG database of real recordings from 51 cognitively healthy controls, 51 mild cognitive impairment (MCI) subjects, 51 mild AD (ADmil) patients, 50 moderate AD (ADmod) patients, and 50 severe AD (ADsev) patients. Main results. Our results using synthetic signals showed that PLI was the least affected parameter by spurious influences in a simulated volume conduction environment. Results using real EEG recordings showed that spontaneous activity of MCI patients is characterized by a significant coupling increase in the band. As dementia progresses, this increase in the band became more pronounced, and a significant widespread decrease in band appeared at the last stage of dementia. Significance. Our results revealed that the estimation of functional EEG connectivity using PLI could reduce the bias introduced by the spurious influence of volume conduction, and it could increase the insight into the underlying brain dynamics at different stages of the AD continuum.

Fibronectin fibrillogenesis is the physiological process by which cells elaborate a fibrous FN matrix. Poly(ethyl acrylate), PEA, has been described to induce a similar process upon simple adsorption of fibronectin (FN) from a protein solution -in the absence of cells -leading to the so-called material-driven fibronectin fibrillogenesis. Poly(methyl acrylate), PMA, is a polymer with very similar chemistry to PEA, on which FN is adsorbed keeping the globular conformation of the protein in solution. We have used radical polymerisation to synthesise copolymers with controlled EA/MA ratio seeking to modulate the degree of FN fibrillogenesis. The physico-chemical properties of the system were studied using dynamicmechanical analysis, differential scanning calorimetry and water contact angle. Both the degree of FN fibrillogenesis and the availability of the integrin binding region of FN directly depend on the percentage of EA in the copolymer, whereas the same total amount of FN was adsorbed regardless the EA/MA ratio. Cell morphology adhesion and differentiation of murine C2C12 were shown to depend on the degree of FN fibrillogenesis previously attained on the material surface. Myogenic differentiation was enhanced on the copolymers with higher EA content, i.e. more interconnected FN fibrils.

Alzheimer’s disease (AD) is the most prevalent cause of dementia, being considered a major health problem, especially in developed countries. Late-onset AD is the most common form of the disease, with symptoms appearing after 65 years old. Genetic determinants of AD risk are vastly unknown, though, ε 4 allele of the ApoE gene has been reported as the strongest genetic risk factor for AD. The objective of this study was to analyze the relationship between brain complexity and the presence of ApoE ε 4 alleles along the AD continuum. For this purpose, resting-state electroencephalography (EEG) activity was analyzed by computing Lempel-Ziv complexity (LZC) from 46 healthy control subjects, 49 mild cognitive impairment subjects, 45 mild AD patients, 44 moderate AD patients and 33 severe AD patients, subdivided by ApoE status. Subjects with one or more ApoE ε 4 alleles were included in the carriers subgroups, whereas the ApoE ε 4 non-carriers subgroups were formed by subjects without any ε 4 allele. Our results showed that AD continuum is characterized by a progressive complexity loss. No differences were observed between AD ApoE ε 4 carriers and non-carriers. However, brain activity from healthy subjects with ApoE ε 4 allele (carriers subgroup) is more complex than from non-carriers, mainly in left temporal, frontal and posterior regions (p-values < 0.05, FDR-corrected Mann–Whitney U-test). These results suggest that the presence of ApoE ε 4 allele could modify the EEG complexity patterns in different brain regions, as the temporal lobes. These alterations might be related to anatomical changes associated to neurodegeneration, increasing the risk of suffering dementia due to AD before its clinical onset. This interesting finding might help to advance in the development of new tools for early AD diagnosis.

Objective. Mild cognitive impairment (MCI) and dementia due to Alzheimer’s disease (AD) have been shown to induce perturbations to normal neuronal behavior and disrupt neuronal networks. Recent work suggests that the dynamic properties of resting-state neuronal activity could be affected by MCI and AD-induced neurodegeneration. The aim of the study was to characterize these properties from different perspectives: (i) using the Kullback–Leibler divergence (KLD), a measure of non-stationarity derived from the continuous wavelet transform; and (ii) using the entropy of the recurrence point density () and the median of the recurrence point density (), two novel metrics based on recurrence quantification analysis. Approach. KLD, and were computed for 49 patients with dementia due to AD, 66 patients with MCI due to AD and 43 cognitively healthy controls from 60 s electroencephalographic (EEG) recordings with a 10 s sliding window with no overlap. Afterwards, we tested whether the measures reflected alterations to normal neuronal activity induced by MCI and AD. Main results. Our results showed that frequency-dependent alterations to normal dynamic behavior can be found in patients with MCI and AD, both in non-stationarity and recurrence structure. Patients with MCI showed signs of patterns of abnormal state recurrence in the theta (4–8 Hz) and beta (13–30 Hz) frequency bands that became more marked in AD. Moreover, abnormal non-stationarity patterns were found in MCI patients, but not in patients with AD in delta (1–4 Hz), alpha (8–13 Hz), and gamma (30–70 Hz). Significance. The alterations in normal levels of non-stationarity in patients with MCI suggest an initial increase in cortical activity during the development of AD. This increase could possibly be due to an impairment in neuronal inhibition that is not present during later stages. MCI and AD induce alterations to the recurrence structure of cortical activity, suggesting that normal state switching during rest may be affected by these pathologies.