Here, we aimed to characterized microstate dynamics induced by open-monitoring meditation (OM), which emphasizes a non-reactive stance toward lived experience, while participants were passively exposed to auditory stimuli. We recorded EEG signals from eighteen trained meditators before, during, and after an OM, that we compared to a matched control group at rest. To characterize brain state, we used a multidimensional-based analysis including source localization EEG microstates, phenomenological reports and personality trait questionnaires. We showed that microstate A was negatively correlated with mindfulness trait and decreased in frequency after OM compared to before in meditators. Microstate B was longer and was positively correlated to non-reactivity trait after OM in the meditator group. Microstate C was less frequent and shorter at rest before OM in meditators compared to non-meditators, and decreased in frequency after OM in meditators. Further, the occurrence of microstate C was negatively correlated to non-reactivity trait of meditators. Source localization analysis revealed that the mindfulness trait effect on microstate C at rest was explained by lower activity of the salience network (identified in the anterior cingulate cortex, thalamus and insula), while the mindfulness state effect relied on a strong contribution of (anterior and posterior) cerebellum during OM. While the decreased microstate A occurrence would be related to the mitigation of phonological aspect of thinking processes, the decrease of microstate C occurrence would represent an index of the cognitive defusion enabled by non-reactive monitoring underlying mindfulness meditation, for which the cerebellum appears to play a crucial role.SIGNIFICANCE STATEMENTWhile benefit of mindfulness meditations are extensively documented in wide range of scientific field, their neural mechanisms remain difficult to catch. Here, we characterize EEG microstate dynamics induced by open-monitoring meditation (OM) triangulated by multimodal approach including source localization, phenomenological reports and personality trait questionnaires. We found that temporal parameters of microstates related to phonological processes and mind wandering are negatively correlated to mindfulness trait and are modulated by OM. Source localization analysis revealed that the trait effect at rest was explained by lower activity of the salience network, while the state effect relied on a strong contribution of the cerebellum during OM. These findings suggested that EEG microstates could represent biomarkers of the cognitive effects of mindfulness.

Present work studies hand articular kinematics for opposition movements of the thumb and flexion-extension movements of the fingers. We gathered data by means of Motion capture (MOCAP) photogrammetry and passive markers on the participant hand located in anatomical points recommended by International Society of Biomechanics (ISB). We collected data from nine participants who did not have any neuronal, rheumatologic or traumatological problems. Cycles were demarcated for the study's ranges of movement and analyzed with the rotation of three-dimensional joints method. Subsequently, obtained data was fed in a virtual model in 3D through the software "OpenSim" to simulate the obtained ranges of movement and compared with similar studies. We found that with the proposed methodology, ranges of movement for each hand joint in the performed exercises are acceptable between subjects and according to similar studies. This will allow a later study of greater scope focused in the comparison of people suffering from hand disorders compared to a population standard.

In marketing, there are many methods to relate reactions to products to customer preference. Current electroencephalography (EEG) signal analysis in the neuromarketing field focuses mainly on correlations between selected electrodes and hemisphere-based analysis on single scalp measures. The present study shows microstate analysis of brain EEG signals in goal-oriented videos. We measured a 16 channel EEG with an Emotiv EPOC+ device. We used two oriented videos from the Ecuadorian Government to publicize Ecuador as a tourist destination. We used a Topographic Atomize and Agglomerate Hierarchical Clustering (TAAHC) microstate analysis for the duration of the EEG as the participants watched each video. We picked the four predominant, in total time and repeatability, microstate maps that represent more than 50% of the entire recording time. We also show, in time, how topographies are represented along the video, which in a later step could be correlated with the images observed in the videos. We show the existing relations between the existing microstates. A microstate analysis of brain signal behavior across time might be a valid methodology and useful tool to analyze videos with marketing purposes.