Correlations Between Disability Score, Optical Coherence Tomography and Microperimetry in Patients with Multiple Sclerosis.

Purpose: To characterize ocular motility disturbances through Microperimetry (MP) in patients with Multiple Sclerosis (MS) trying to detect those capable of influencing the disability to improve the accuracy of assessing visual impact in EDSS scale. MP results were compare with some structural parameters obtained by OCT.

Patients And Methods: Cross-sectional analytical and correlational case-control study approved by Ethical Committee.

Accounting for Visual Field Abnormalities when Using Eye-tracking to Diagnose Reading Problems in Neurological Degeneration.

State-of-the-art eye trackers provide valuable information for diagnosing reading problems by measuring and interpreting people's gaze paths as they read through text. Abnormal conditions such as visual field defects, however, can seriously confound most of today's existing methods for interpreting reading gaze patterns. Our objective was to research how visual field defects impact reading gaze path patterns, so the effects of such neurological pathologies can be explicitly incorporated into more comprehensive reading diagnosis methodologies.

Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses.

The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as "canonical" frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study, we introduce a new data-driven method to automatically identify frequency ranges based on the topological similarity of the frequency-dependent functional neural network.

High Frequential Resolution Networks: Considerations on a New Functional Brain Connectivity Framework.

Connectivity analyses are widely used to assess the interaction brain networks. This type of analyses is usually conducted considering the well-known classical frequency bands: delta, theta, alpha, beta, and gamma. However, this parcellation of the frequency content can bias the analyses, since it does not consider the between-subject variability or the particular idiosyncrasies of the connectivity patterns that occur within a band.

Exploring the Alterations in the Distribution of Neural Network Weights in Dementia Due to Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder which has become an outstanding social problem. The main objective of this study was to evaluate the alterations that dementia due to AD elicits in the distribution of functional network weights. Functional connectivity networks were obtained using the orthogonalized Amplitude Envelope Correlation (AEC), computed from source-reconstructed resting-state eletroencephalographic (EEG) data in a population formed by 45 cognitive healthy elderly controls, 69 mild cognitive impaired (MCI) patients and 81 AD patients.

Global Impact of COVID-19 on Stroke Care and IV Thrombolysis.

Objective: To measure the global impact of COVID-19 pandemic on volumes of IV thrombolysis (IVT), IVT transfers, and stroke hospitalizations over 4 months at the height of the pandemic (March 1 to June 30, 2020) compared with 2 control 4-month periods.

Methods: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases.

Abnormal meta-state activation of dynamic brain networks across the Alzheimer spectrum.

The characterization of the distinct dynamic functional connectivity (dFC) patterns that activate in the brain during rest can help to understand the underlying time-varying network organization. The presence and behavior of these patterns (known as meta-states) have been widely studied by means of functional magnetic resonance imaging (fMRI). However, modalities with high-temporal resolution, such as electroencephalography (EEG), enable the characterization of fast temporally evolving meta-state sequences.

Characterization of the dynamic behavior of neural activity in Alzheimer's disease: exploring the non-stationarity and recurrence structure of EEG resting-state activity.

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 ([Formula: see text]) and the median of the recurrence point density ([Formula: see text]), two novel metrics based on recurrence quantification analysis.

Analysis of Volume Conduction Effects on Different Functional Connectivity Metrics: Application to Alzheimer's Disease EEG Signals.

The aim of this study was to evaluate the effect of volume conduction on different connectivity metrics: Amplitude Envelope Correlation (AEC), Phase Lag Index (PLI), and Magnitude Squared Coherence (MSCOH). These measures were applied to: (i) a synthetic model of 64 coupled oscillators; and (ii) a resting-state EEG database of 72 patients with dementia due to Alzheimer's disease (AD) and 37 cognitively healthy controls. Our results revealed that AEC and PLI are weakly influenced by the simulated volume conduction compared to MSCOH, although the three metrics are not immune to this effect.

Characterization of EEG Resting-state Activity in Alzheimer's Disease by Means of Recurrence Plot Analyses.

The main objective of this study was to characterize EEG resting-state activity in 55 Alzheimer's disease (AD) patients and 29 healthy controls by means of TREND, a measure based on recurrence quantification analysis. TREND was computed from 60-second recordings of consecutive EEG activity, divided into non-overlapping windows of length 1, 2, 3, 5, 10, 15, 20 and 60 seconds. This measure was computed in the conventional EEG frequency bands (delta, theta, alpha, beta-1, beta-2 and gamma).

Characterizing the fluctuations of dynamic resting-state electrophysiological functional connectivity: reduced neuronal coupling variability in mild cognitive impairment and dementia due to Alzheimer's disease.

Objective: The characterization of brain functional connectivity is a helpful tool in the study of the neuronal substrates and mechanisms that are altered in Azheimer's disease (AD) and mild cognitive impairment (MCI). Recently, there has been a shift towards the characterization of dynamic functional connectivity (dFC), discarding the assumption of connectivity stationarity during the resting-state. The majority of these studies have been performed with functional magnetic resonance imaging recordings, with only a small subset being based on magnetoencephalography/electroencephalography (MEG/EEG).

Measuring Alterations of Spontaneous EEG Neural Coupling in Alzheimer's Disease and Mild Cognitive Impairment by Means of Cross-Entropy Metrics.

Alzheimer's Disease (AD) represents the most prevalent form of dementia and is considered a major health problem due to its high prevalence and its economic costs. An accurate characterization of the underlying neural dynamics in AD is crucial in order to adopt effective treatments. In this regard, mild cognitive impairment (MCI) is an important clinical entity, since it is a risk-state for developing dementia.

Assessment of EEG Connectivity Patterns in Mild Cognitive Impairment Using Phase Slope Index.

Mild cognitive impairment (MCI) is a pathology characterized by an abnormal cognitive state. MCI patients are considered to be at high risk for developing dementia. The aim of this study is to characterize the changes that MCI causes in the patterns of brain information flow.

Detection of maltreatment of people with dementia in Spain: usefulness of the Caregiver Abuse Screen (CASE).

The objective of our study is to validate the Caregiver Abuse Screen (CASE) as an instrument for detecting the maltreatment of people with dementia in Spain. In total, 326 informal caregivers of people with different types of dementia were interviewed in several cities in northwest Spain. The caregivers were selected from outpatient neurology clinics and associations of relatives of people with Alzheimer's disease and other dementias.

Automated Multiclass Classification of Spontaneous EEG Activity in Alzheimer's Disease and Mild Cognitive Impairment.

The discrimination of early Alzheimer's disease (AD) and its prodromal form (i.e., mild cognitive impairment, MCI) from cognitively healthy control (HC) subjects is crucial since the treatment is more effective in the first stages of the dementia.

Phase-amplitude coupling analysis of spontaneous EEG activity in Alzheimer's disease.

This study was aimed at exploring phase-amplitude coupling (PAC) patterns of neural activity in dementia due to Alzheimer's disease (AD). For this task, five minutes of spontaneous electroencephalographic (EEG) activity from 22 patients with mild AD and 16 cognitively healthy controls were studied. To assess PAC patterns, phase-locking value was computed between the phase of low frequencies and the power of high frequencies within each sensor.

Bispectral analysis of spontaneous EEG activity from patients with moderate dementia due to Alzheimer's disease.

Dementia due to Alzheimer's disease (AD) is a common disorder with a great impact on the patients' quality of life. The aim of this pilot study was to characterize spontaneous electroencephalography (EEG) activity in dementia due to AD using bispectral analysis. Five minutes of EEG activity were recorded from 17 patients with moderate dementia due to AD and 19 age-matched controls.

Spatio-Temporal Fluctuations of Neural Dynamics in Mild Cognitive Impairment and Alzheimer's Disease.

Background: An accurate characterization of neural dynamics in mild cognitive impairment (MCI) is of paramount importance to gain further insights into the underlying neural mechanisms in Alzheimer's disease (AD). Nevertheless, there has been relatively little research on brain dynamics in prodromal AD. As a consequence, its neural substrates remain unclear.

Analysis of spontaneous EEG activity in Alzheimer's disease using cross-sample entropy and graph theory.

The aim of this pilot study was to analyze spontaneous electroencephalography (EEG) activity in Alzheimer's disease (AD) by means of Cross-Sample Entropy (Cross-SampEn) and two local measures derived from graph theory: clustering coefficient (CC) and characteristic path length (PL). Five minutes of EEG activity were recorded from 37 patients with dementia due to AD and 29 elderly controls. Our results showed that Cross-SampEn values were lower in the AD group than in the control one for all the interactions among EEG channels.

Prevalence of dementia and subtypes in Valladolid, northwestern Spain: the DEMINVALL study.

Objective: To describe the prevalence of dementia and subtypes in a general elderly population in northwestern Spain and to analyze the influence of socio-demographic factors.

Methods: Cross-sectional, two-phase, door-to-door, population-based study. A total of 870 individuals from a rural region and 2,119 individuals from an urban region of Valladolid, Spain, were involved.

Design, methods and demographic findings of the DEMINVALL survey: a population-based study of Dementia in Valladolid, Northwestern Spain.

Background: This article describes the rationale and design of a population-based survey of dementia in Valladolid (northwestern Spain). The main aim of the study was to assess the epidemiology of dementia and its subtypes. Prevalence of anosognosia in dementia patients, nutritional status, diet characteristics, and determinants of non-diagnosed dementia in the community were studied.

Complete bilateral ophthalmoplegia resistant to caloric stimulation in bilateral paramedian midbrain-thalamic infarction.

A 79-year-old woman who developed bilateral paramedian midbrain-thalamic infarction manifested complete bilateral ophthalmoplegia resistant to caloric stimulation, indicating impairment of the vestibulo-ocular reflex (VOR). Previous reports have mentioned this phenomenon but have not explicitly reported the results of caloric testing. Why a lesion apparently confined to the upper brainstem should produce impairment of the horizontal VOR remains unexplained.