scholarly journals Permutation Entropy and Statistical Complexity in Mild Cognitive Impairment and Alzheimer’s Disease: An Analysis Based on Frequency Bands

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 116 ◽  
Author(s):  
Ignacio Echegoyen ◽  
David López-Sanz ◽  
Johann H. Martínez ◽  
Fernando Maestú ◽  
Javier M. Buldú
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Frequency Band ◽  
Local Level ◽  
Permutation Entropy ◽  
Frequency Bands ◽  
Individual Level ◽  
Statistical Complexity

We present one of the first applications of Permutation Entropy (PE) and Statistical Complexity (SC) (measured as the product of PE and Jensen-Shanon Divergence) on Magnetoencephalography (MEG) recordings of 46 subjects suffering from Mild Cognitive Impairment (MCI), 17 individuals diagnosed with Alzheimer’s Disease (AD) and 48 healthy controls. We studied the differences in PE and SC in broadband signals and their decomposition into frequency bands ( δ , θ , α and β ), considering two modalities: (i) raw time series obtained from the magnetometers and (ii) a reconstruction into cortical sources or regions of interest (ROIs). We conducted our analyses at three levels: (i) at the group level we compared SC in each frequency band and modality between groups; (ii) at the individual level we compared how the [PE, SC] plane differs in each modality; and (iii) at the local level we explored differences in scalp and cortical space. We recovered classical results that considered only broadband signals and found a nontrivial pattern of alterations in each frequency band, showing that SC does not necessarily decrease in AD or MCI.

scholarly journals Using a Digital Neuro Signature to measure longitudinal individual-level change in Alzheimer’s disease: the Altoida large cohort study

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Irene B. Meier ◽  
Max Buegler ◽  
Robbert Harms ◽  
Azizi Seixas ◽  
Arzu Çöltekin ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Disease Risk ◽  
Intraindividual Variability ◽  
Cognitive Test ◽  
Individual Level ◽  
Level Change ◽  
Neuropsychological Assessments

AbstractConventional neuropsychological assessments for Alzheimer’s disease are burdensome and inaccurate at detecting mild cognitive impairment and predicting Alzheimer’s disease risk. Altoida’s Digital Neuro Signature (DNS), a longitudinal cognitive test consisting of two active digital biomarker metrics, alleviates these limitations. By comparison to conventional neuropsychological assessments, DNS results in faster evaluations (10 min vs 45–120 min), and generates higher test-retest in intraindividual assessment, as well as higher accuracy at detecting abnormal cognition. This study comparatively evaluates the performance of Altoida’s DNS and conventional neuropsychological assessments in intraindividual assessments of cognition and function by means of two semi-naturalistic observational experiments with 525 participants in laboratory and clinical settings. The results show that DNS is consistently more sensitive than conventional neuropsychological assessments at capturing longitudinal individual-level change, both with respect to intraindividual variability and dispersion (intraindividual variability across multiple tests), across three participant groups: healthy controls, mild cognitive impairment, and Alzheimer’s disease. Dispersion differences between DNS and conventional neuropsychological assessments were more pronounced with more advanced disease stages, and DNS-intraindividual variability was able to predict conversion from mild cognitive impairment to Alzheimer’s disease. These findings are instrumental for patient monitoring and management, remote clinical trial assessment, and timely interventions, and will hopefully contribute to a better understanding of Alzheimer’s disease.

scholarly journals TMS-EEG Biomarkers of Amnestic Mild Cognitive Impairment Due to Alzheimer’s Disease: A Proof-of-Concept Six Years Prospective Study

2021 ◽  
Vol 13 ◽  
Author(s):  
Florinda Ferreri ◽  
Andrea Guerra ◽  
Luca Vollero ◽  
David Ponzo ◽  
Sara Määtta ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Sensorimotor Cortex ◽  
Amnestic Mild Cognitive Impairment ◽  
Additional Parameter ◽  
Sensorimotor Network ◽  
Individual Level ◽  
Gamma Frequency

Background: Early and affordable identification of subjects with amnestic mild cognitive impairment (aMCI) who will convert to Alzheimer’s disease (AD) is a major scientific challenge.Objective: To investigate the neurophysiological hallmarks of sensorimotor cortex function in aMCI under the hypothesis that some may represent the plastic rearrangements induced by neurodegeneration, hence predictors of future conversion to AD. We sought to determine (1) whether the sensorimotor network shows peculiar alterations in patients with aMCI and (2) if sensorimotor network alterations predict long-term disease progression at the individual level.Methods: We studied several transcranial magnetic stimulation (TMS)-electroencephalogram (EEG) parameters of the sensorimotor cortex in a group of patients with aMCI and followed them for 6 years. We then identified aMCI who clinically converted to AD [prodromal to AD-MCI (pAD-MCI)] and those who remained cognitively stable [non-prodromal to AD-MCI (npAD-MCI)].Results: Patients with aMCI showed reduced motor cortex (M1) excitability and disrupted EEG synchronization [decreased intertrial coherence (ITC)] in alpha, beta and gamma frequency bands compared to the control subjects. The degree of alteration in M1 excitability and alpha ITC was comparable between pAD-MCI and npAD-MCI. Importantly, beta and gamma ITC impairment in the stimulated M1 was greater in pAD-MCI than npAD-MCI. Furthermore, an additional parameter related to the waveform shape of scalp signals, reflecting time-specific alterations in global TMS-induced activity [stability of the dipolar activity (sDA)], discriminated npAD-MCI from MCI who will convert to AD.Discussion: The above mentioned specific cortical changes, reflecting deficit of synchronization within the cortico-basal ganglia-thalamo-cortical loop in aMCI, may reflect the pathological processes underlying AD. These changes could be tested in larger cohorts as neurophysiological biomarkers of AD.

scholarly journals Visually guided reaching in Alzheimer's disease and mild cognitive impairment

2020 ◽  
Author(s):  
Alexandra Grace Mitchell ◽  
Stephanie Rossit ◽  
Suvankar Pal ◽  
Michael Hornberger ◽  
Annie Warman ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Posterior Parietal Cortex ◽  
Peripheral Vision ◽  
Control Group ◽  
Optic Ataxia ◽  
Individual Level ◽  
Radial Depth

Recent evidence has implicated areas within the posterior parietal cortex (PPC), as among the first to show pathophysiological changes in Alzheimer’s disease. Focal brain damage to the PPC can cause optic ataxia, a specific deficit in reaching to peripheral targets. Visuomotor deficits in optic ataxia are often only detected when reaching to objects in peripheral vision, therefore this condition can often go unnoticed. The present study investigated whether peripheral misreaching is a feature of Alzheimer’s disease. Reaching ability was assessed in individuals with a clinical diagnosis of mild-to-moderate Alzheimer’s and mild cognitive impairment (MCI), compared to a control group of healthy, older adults. Participants were required to reach to targets presented in central vision or in the periphery using two reaching tasks; one in the lateral plane and another presented in radial depth. Case-control comparisons identified 1/10 MCI and 3/17 Alzheimer’s patients with severe peripheral reaching deficits at the individual level, but group-level comparisons did not find significantly higher peripheral reaching error in neither Alzheimer’s nor MCI groups. However, exploratory analyses showed significantly increased reach duration in both Alzheimer’s and MCI groups relative to controls. We conclude that Alzheimer’s disease may lead to a visuomotor impairment that is compensated for by a slowing down of the reach movement to maintain accuracy. However, these findings suggest that peripheral reaching deficits similar to what is observed in optic ataxia are unlikely to be a common feature of Alzheimer’s disease.

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