Biology subjects

Vidaurre, C.

Publications and source records attributed to Vidaurre, C..

3 recordsLinked to original sources

bioRxiv2024

Cardiac Cycle Modulates Alpha and Beta Suppression during Motor Imagery.

IntroductionThe baroreceptor hypothesis posits that baroreceptors, located on the cardiac walls, are most active during systole, translating cardiac contraction information to the brain. Studies within this context have suggested that the systolic phase, characterised by increased noise, may compromise the processing of sensory stimuli. Although the effect of systolic and diastolic cardiac cycle phases on cognition, perception, and action has been widely documented, there remains a gap in applying these interoceptive insights to enhance assistive technologies such as brain-computer interfaces (BCIs). In the context of BCIs, motor imagery (MI) --the mental rehearsal of movement--serves as a widely used control paradigm, yet its modulation through the cardiac cycle has not been empirically tested. Bridging this gap, this study examined how the cardiac cycle phases influence MI by assessing their effect on contralateral suppression of alpha (8-13 Hz) and beta (14-30 Hz) activity in primary sensorimotor cortices. Materials & MethodsTwenty-nine participants performed left/right thumb abductions based on the direction of an arrow presented on the screen to get familiarised with kinesthetic sensations. They then completed a MI task of the same movements. We recorded both electroencephalography (EEG) and electrocardiography (ECG), focusing our analysis on data epochs aligned with the experimental cue, based on whether it occurred during the systolic or diastolic phase of the cardiac cycle. Time-frequency analysis of source-reconstructed data assessed cue-induced changes in power spectral density (PSD) within the alpha and beta bands in the postcentral and precentral gyrus. ResultsWe found that alpha and beta suppression in the contralateral primary motor and somatosensory cortex was more pronounced when the cue fell during the diastolic phase of the cardiac cycle than during the systolic phase. Validating the main results, an analysis with circular statistics revealed that trials with particularly pronounced contralateral alpha and beta suppression featured cues with latencies clustering during diastole, the quietest time of the cardiac cycle. Accompanying the EEG effects, EMG activity on the side of the movement was enhanced during diastole. ConclusionThese findings provide evidence that MI performance can be enhanced by considering the cardiac cycle phases, offering promising implications for BCI-based applications. O_LIKey point 1: The phases of the cardiac cycle influence motor imagery performance. C_LIO_LIKey point 2: Alpha and beta contralateral suppression over sensorimotor cortices is more pronounced when movement direction is cued during diastole. C_LIO_LIKey point 3: Contralateral suppression is more likely to cluster during the quietest time of the diastolic phase: between the T-wave and the P-wave. C_LI

neuroscience↗

bioRxiv2023

Sensorimotor brain-computer interface performance depends on signal-to-noise ratio but not connectivity of the mu rhythm in a multiverse analysis of longitudinal data

ObjectiveServing as a channel for communication with locked-in patients or control of prostheses, sensorimotor brain-computer interfaces (BCIs) decode imaginary movements from the recorded activity of the users brain. However, many individuals remain unable to control the BCI, and the underlying mechanisms are unclear. The users BCI performance was previously shown to correlate with the resting-state signal-to-noise ratio (SNR) of the mu rhythm and the phase synchronization (PS) of the mu rhythm between sensorimotor areas. Yet, these predictors of performance were primarily evaluated in a single BCI session, while the longitudinal aspect remains rather uninvestigated. In addition, different analysis pipelines were used to estimate PS in source space, potentially hindering the reproducibility of the results. ApproachTo systematically address these issues, we performed an extensive validation of the relationship between pre-stimulus SNR, PS, and session-wise BCI performance using a publicly available dataset of 62 human participants performing up to 11 sessions of BCI training. We performed the analysis in sensor space using the surface Laplacian and in source space by combining 24 processing pipelines in a multiverse analysis. This way, we could investigate how robust the observed effects were to the selection of the pipeline. Main resultsOur results show that SNR had both between- and within-subject effects on BCI performance for the majority of the pipelines. In contrast, the effect of PS on BCI performance was less robust to the selection of the pipeline and became non-significant after controlling for SNR. SignificanceTaken together, our results demonstrate that changes in neuronal connectivity within the sensorimotor system are not critical for learning to control a BCI, and interventions that increase the SNR of the mu rhythm might lead to improvements in the users BCI performance.

neuroscience↗

bioRxiv2020

Sensorimotor functional connectivity: a neurophysiological factor related to BCI performance

Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. For BCIs based on the modulation of sensorimotor rhythms as measured by means of electroen-cephalography (EEG), about 20% of potential users do not obtain enough accuracy to gain reliable control of the system. This lack of efficiency of BCI systems to decode users intentions requires the identification of neuro-physiological factors determining good and poor BCI performers. Given that the neuronal oscillations, used in BCI, demonstrate rich a repertoire of spatial interactions, we hypothesized that neuronal activity in sensorimotor areas would define some aspects of BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in calibration and an online feedback session in the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post-as well as pre-stimulus connectivity in the calibration recordings is significantly correlated to online feedback performance in and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study shows that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sen-sorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance.

neuroscience↗