Independent component analysis (ICA) is a novel technique that calculates independent components from mixed signals. A hypothetical clinical application is to remove artifacts in EEG. The goal of this study was to apply ICA to standard EEG recordings to eliminate well-known artifacts, thus quantifying its efficacy in an objective way. Eighty samples of recordings with spikes and evident artifacts of electrocardiogram (EKG), eye movements, 50-Hz interference, muscle, or electrode artifact were studied. ICA components were calculated using the Joint Approximate Diagonalization of Eigen-matrices (JADE) algorithm. The signal was reconstructed excluding those components related to the artifacts. A normalized correlation coefficient was used as a measure of the changes caused by the suppression of these components. ICA produced an evident clearing-up of signals in all the samples. The morphology and the topography of the spike were very similar before and after the removal of the artifacts. The correlation coefficient showed that the rest of the signal did not change significantly. Two examiners independently looked at the samples to identify the changes in the morphology and location of the discharge and the artifacts. In conclusion, ICA proved to be a useful tool to clean artifacts in short EEG samples, without having the disadvantages associated with the digital filters. The distortion of the interictal activity measured by correlation analysis was minimal.

We studied the effect of stimulus predictability on the alpha and beta changes observed in central regions during stimulus-induced movement paradigms. Six young volunteers were instructed to extend briskly their dominant wrist as soon as possible after hearing a 2000 Hz sound. Two sequences of stimuli were presented to each subject, the first rhythmic at 1/6 s and the second with random intervals between 5 and 13s. A time-frequency analysis of nonphase-locked activity in the 7-37 Hz range was performed on stimulus-centred EEG sweeps using wavelet filters and Gabor transforms. During the sequence of predictable rhythmic stimuli, stimulus-induced movements were accompanied by a decrease in beta activity that began contralaterally about 1 s prior to the stimulus and extended to both sides later on. This decrease was followed by a rebound after the end of the movement. In the alpha band, the decrease observed started just after the sound. During the sequence of non-predictable, random stimuli, stimulus-induced movements were accompanied by a shorter and smaller alpha and beta-ERD, that started after the stimulus. The presence of a pre-stimulus beta ERD only in the rhythmic predictable paradigm suggests that central pre-movement beta ERD may be an indicator of motor preparation, and could be used for objective evaluation of time estimation and motor timing. The minimal differences observed in the alpha changes in both paradigms suggest that alpha-ERD may not be linked to motor preparation.

Background: The World Health Organization proposed the concept of intrinsic capacity (IC; the composite of all the physical and mental capacities of the individual) as central for healthy ageing. However, little research has investigated the interaction and joint associations of IC with cardiovascular disease (CVD) incidence and CVD mortality in middle‐ and older‐aged adults.Methods: Using data from 443 130 UK Biobank participants, we analysed seven biomarkers capturing the level of functioning of five domains of IC to calculate a total IC score (ranging from 0 [better IC] to +4 points [poor IC]). Associations between IC score and incidence of six long‐term CVD conditions (hypertension, stroke/transient ischaemic attack stroke, peripheral vascular disease, atrial fibrillation/flutter, coronary artery disease and heart failure), and grouped mortality from these conditions were estimated using Cox proportional models, with a 1‐year landmark analysis to triangulate the findings.Results: Over 10.6 years of follow‐up, CVD morbidity grouped (n = 384 380 participants for the final analytic sample) was associated with IC scores (0 to +4): mean hazard ratio (HR) [95% confidence interval, CI] 1.11 [1.08–1.14], 1.20 [1.16–1.24], 1.29 [1.23–1.36] and 1.56 [1.45–1.59] in men (C‐index = 0.68), and 1.17 [1.13–1.20], 1.30 [1.26–1.36], 1.52 [1.45–1.59] and 1.78 [1.67–1.89] in women (C‐index = 0.70). In regard to mortality, our results indicated that the higher IC score (+4 points) was associated with a significant increase in subsequent CVD mortality (mean HR [95% CI]: 2.10 [1.81–2.43] in men [C‐index = 0.75] and 2.29 [1.85–2.84] in women [C‐index = 0.78]). Results of all sensitivity analyses by full sample, sex and age categories were largely consistent independent of major confounding factors (P < 0.001).Conclusions: IC deficit score is a powerful predictor of functional trajectories and vulnerabilities of the individual in relation to CVD incidence and premature death. Monitoring an individual's IC score may provide an early‐warning system to initiate preventive efforts.