Estimation of neuromuscular intention using electromyography (EMG) and pattern recognition is still an open problem. One of the reasons is that the pattern-recognition approach is greatly influenced by temporal changes in electromyograms caused by the variations in the conductivity of the skin and/or electrodes, or physiological changes such as muscle fatigue. This paper proposes novel features for task identification extracted from the high-density electromyographic signal (HD-EMG) by applying the mean shift channel selection algorithm evaluated using a simple and fast classifier-linear discriminant analysis. HD-EMG was recorded from eight subjects during four upper-limb isometric motor tasks (flexion/extension, supination/pronation of the forearm) at three different levels of effort. Task and effort level identification showed very high classification rates in all cases. This new feature performed remarkably well particularly in the identification at very low effort levels. This could be a step towards the natural control in everyday applications where a subject could use low levels of effort to achieve motor tasks. Furthermore, it ensures reliable identification even in the presence of myoelectric fatigue and showed robustness to temporal changes in EMG, which could make it suitable in long-term applications.
Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.
Sleep deprivation (SD) has adverse effects on mental and physical health, affecting the cognitive abilities and emotional states. Specifically, cognitive functions and alertness are known to decrease after SD. The aim of this work was to identify the directional information transfer after SD on scalp EEG signals using transfer entropy (TE). Using a robust methodology based on EEG recordings of 18 volunteers deprived from sleep for 36 h, TE and spectral analysis were performed to characterize EEG data acquired every 2 h. Correlation between connectivity measures and subjective somnolence was assessed. In general, TE showed medium-and long-range significant decreases originated at the occipital areas and directed towards different regions, which could be interpreted as the transfer of predictive information from parieto-occipital activity to the rest of the head. Simultaneously, short-range increases were obtained for the frontal areas, following a consistent and robust time course with significant maps after 20 h of sleep deprivation. Changes during sleep deprivation in brain network were measured effectively by TE, which showed increased local connectivity and diminished global integration. TE is an objective measure that could be used as a potential measure of sleep pressure and somnolence with the additional property of directed relationships.
Bachiller, A.; Romero, S.; Molina, V.; Alonso, J.F.; Mañanas, M.A.; Poza, J.; Hornero, R. Schizophrenia research Vol. 169, p. 318-325 DOI: 10.1016/j.schres.2015.09.028 Data de publicació: 2015-12 Article en revista
The present study investigates the neural substrates underlying cognitive processing in schizophrenia (Sz) patients. To this end, an auditory 3-stimulus oddball paradigm was used to identify P3a and P3b components, elicited by rare-distractor and rare-target tones, respectively. Event-related potentials (ERP) were recorded from 31 Sz patients and 38 healthy controls. The P3a and P3b brain-source generators were identified by time-averaging of low-resolution brain electromagnetic tomography (LORETA) current density images. In contrast with the commonly used fixed window of interest (WOI), we proposed to apply an adaptive WOI, which takes into account subjects’ P300 latency variability. Our results showed different P3a and P3b source activation patterns in both groups. P3b sources included frontal, parietal and limbic lobes, whereas P3a response generators were localized over bilateral frontal and superior temporal regions. These areas have been related to the discrimination of auditory stimulus and to the inhibition (P3a) or the initiation (P3b) of motor response in a cognitive task. In addition, differences in source localization between Sz and control groups were observed. Sz patients showed lower P3b source activity in bilateral frontal structures and the cingulate. P3a generators were less widespread for Sz patients than for controls in right superior, medial and middle frontal gyrus. Our findings suggest that target and distractor processing involves distinct attentional subsystems, both being altered in Sz. Hence, the study of neuroelectric brain information can provide further insights to understand cognitive processes and underlying mechanisms in Sz.
Background: Psychedelics induce intense modifications in the sensorium, the sense of "self," and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects.; Methods: Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine.; Results: The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced.; Conclusions: These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain.