Electroencephalography microstates highlight specific mindfulness traits.

The present study aimed to investigate the spontaneous dynamics of large-scale brain networks underlying mindfulness as a dispositional trait, through resting-state electroencephalography (EEG) microstates analysis. Eighteen participants had attended a standardized mindfulness-based stress reduction training (MBSR), and 18 matched waitlist individuals (CTRL) were recorded at rest while they were passively exposed to auditory stimuli. Participants' mindfulness traits were assessed with the Five Facet Mindfulness Questionnaire (FFMQ). To further explore the relationship between microstate dynamics at rest and mindfulness traits, participants were also asked to rate their experience according to five phenomenal dimensions. After training, MBSR participants showed a highly significant increase in FFMQ score, as well as higher observing and non-reactivity FFMQ sub-scores than CTRL participants. Microstate analysis revealed four classes of microstates (A-D) in global clustering across all subjects. The MBSR group showed lower duration, occurrence and coverage of microstate C than the control group. Moreover, these microstate C parameters were negatively correlated to non-reactivity sub-scores of FFMQ across participants, whereas the microstate A occurrence was negatively correlated to FFMQ total score. Further analysis of participants' self-reports suggested that MBSR participants showed a better sensory-affective integration of auditory interferences. In line with previous studies, our results suggest that temporal dynamics of microstate C underlie specifically the non-reactivity trait of mindfulness. These findings encourage further research into microstates in the evaluation and monitoring of the impact of mindfulness-based interventions on the mental health and well-being of individuals.

From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation.

Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

Brain potential responses involved in decision-making in weightlessness.

The brain is essential to human adaptation to any environment including space. We examined astronauts' brain function through their electrical EEG brain potential responses related to their decision of executing a docking task in the same virtual scenario in Weightlessness and on Earth before and after the space stay of 6 months duration. Astronauts exhibited a P300 component in which amplitude decreased during, and recovered after, their microgravity stay. This effect is discussed as a post-value-based decision-making closing mechanism; The P300 amplitude decrease in weightlessness is suggested as an emotional stimuli valence reweighting during which orbitofrontal BA10 would play a major role. Additionally, when differentiating the bad and the good docks on Earth and in Weightlessness and keeping in mind that astronauts were instantaneously informed through a visual cue of their good or bad performance, it was observed that the good dockings resulted in earlier voltage redistribution over the scalp (in the 150-250 ms period after the docking) than the bad dockings (in the 250-400 ms) in Weightlessness. These results suggest that in Weightlessness the knowledge of positive or negative valence events is processed differently than on Earth.

Spatiotemporal brain signal associated with high and low levels of proactive motor response inhibition.

Proactive motor response inhibition is used to strategically restrain actions in preparation for stopping. In this study, we first examined the event related potential (ERP) elicited by low and high level of proactive response inhibition, as assessed by the stop-signal task. Corroborating previous studies, we found an increased amplitude of the contingent negative variation (CNV) in the high level of proactive inhibition. As the main goal of the present study, swLORETA was used to determine the neural generators characterising CNV differences between low and high levels of proactive inhibition. Results showed that the higher level of proactive inhibition involved numerous generators, including within the middle and medial frontal gyrus. Importantly, we observed that the lower level of proactive inhibition also involved a specific neural generator, within the frontopolar cortex. Altogether, present findings identified the specific brain sources of ERP signals involved in the later phase of motor preparation under low or high levels of proactive motor response inhibition.

"Cerebellar contribution to visuo-attentional alpha rhythm: insights from weightlessness".

Human brain adaptation in weightlessness follows the necessity to reshape the dynamic integration of the neural information acquired in the new environment. This basic aspect was here studied by the electroencephalogram (EEG) dynamics where oscillatory modulations were measured during a visuo-attentional state preceding a visuo-motor docking task. Astronauts in microgravity conducted the experiment in free-floating aboard the International Space Station, before the space flight and afterwards. We observed stronger power decrease (~ERD: event related desynchronization) of the ~10 Hz oscillation from the occipital-parietal (alpha ERD) to the central areas (mu ERD). Inverse source modelling of the stronger alpha ERD revealed a shift from the posterior cingulate cortex (BA31, from the default mode network) on Earth to the precentral cortex (BA4, primary motor cortex) in weightlessness. We also observed significant contribution of the vestibular network (BA40, BA32, and BA39) and cerebellum (lobule V, VI). We suggest that due to the high demands for the continuous readjustment of an appropriate body posture in free-floating, this visuo-attentional state required more contribution from the motor cortex. The cerebellum and the vestibular network involvement in weightlessness might support the correction signals processing necessary for postural stabilization, and the increased demand to integrate incongruent vestibular information.

Adaptive changes of rhythmic EEG oscillations in space implications for brain-machine interface applications.

The dramatic development of brain machine interfaces has enhanced the use of human brain signals conveying mental action for controlling external actuators. This chapter will outline current evidences that the rhythmic electroencephalographic activity of the brain is sensitive to microgravity environment. Experiments performed in the International Space Station have shown significant changes in the power of the astronauts' alpha and mu oscillations in resting condition, and other adaptive modifications in the beta and gamma frequency range during the immersion in virtual navigation. In this context, the dynamic aspects of the resting or default condition of the awaken brain, the influence of the "top-down" dynamics, and the possibility to use a more constrained configuration by a new somatosensory-evoked potential (gating approach) are discussed in the sense of future uses of brain computing interface in space mission. Although, the state of the art of the noninvasive BCI approach clearly demonstrates their ability and the great expectance in the field of rehabilitation for the restoration of defective communication between the brain and external world, their future application in space mission urgently needs a better understanding of brain neurophysiology, in particular in aspects related to neural network rhythmicity in microgravity.