Biology subjects

Hugueville, L.

Publications and source records attributed to Hugueville, L..

7 recordsLinked to original sources

bioRxiv2024

Agency accounts for the effect of FB transparency onmotor imagery neurofeedback performance

ObjectiveNeurofeedback (NF) is a cognitive training procedure based on real-time feedback (FB) of a participants brain activity that they must learn to self-regulate. A classical visual FB delivered in a NF task is a filling gauge reflecting a measure of brain activity. This abstract visual FB is not transparently linked--from the subjects perspective--to the task performed (e.g., motor imagery). This may decrease the sense of agency, that is, the participants reported control over FB. Here, we assessed the influence of FB transparency on NF performance and the role of agency in this relationship. ApproachParticipants performed a NF task using motor imagery to regulate brain activity measured using electroencephalography. In separate blocks, participants experienced three different conditions designed to vary transparency: FB was presented as either 1) a swinging pendulum, 2) a clenching virtual hand, 3) a clenching virtual hand combined with a motor illusion induced by tendon vibration. We measured self-reported agency and user experience after each NF block. Main resultsWe found that FB transparency influences NF performance. Transparent visual FB provided by the virtual hand resulted in significantly better NF performance than the abstract FB of the pendulum. Surprisingly, adding a motor illusion to the virtual hand significantly decreased performance relative to the virtual hand alone. When introduced in incremental linear mixed effect models, self-reported agency was significantly associated with NF performance and it captured the variance related to the effect of FB transparency on NF performance. SignificanceOur results highlight the relevance of transparent FB in relation to the sense of agency. This is likely an important consideration in designing FB to improve NF performance and learning outcomes.

neuroscience↗

bioRxiv2024

Inhibitory control of gait initiation in humans: an electroencephalography study

Response inhibition is a crucial component of executive control. Although mainly studied in upper limb tasks, it is fully implicated in gait initiation. Here, we assessed the influence of proactive and reactive inhibitory control during gait initiation in healthy adult participants. For this purpose, we measured kinematics and electroencephalography (EEG) activity (event-related potential [ERP] and time-frequency data) during a modified Go/NoGo gait initiation task in 23 healthy adults. The task comprised Go-certain, Go-uncertain, and NoGo conditions. Each trial included preparatory and imperative stimuli. Our results showed that go-uncertainty resulted in delayed reaction time (RT), without any difference for the other parameters of gait initiation. Proactive inhibition, i.e. Go uncertain versus Go certain conditions, influenced EEG activity as soon as the preparatory stimulus. Moreover, both proactive and reactive inhibition influenced the amplitude of the ERPs (central P1, occipito-parietal N1, and N2/P3) and theta and alpha/low beta band activities in response to the imperative--Go-uncertain versus Go-certain and NoGo versus Go-uncertain--stimuli. These findings demonstrate that the uncertainty context induced proactive inhibition, as reflected in delayed gait initiation. Proactive and reactive inhibition elicited extended and overlapping modulations of ERP and time-frequency activities. This study shows protracted influence of inhibitory control in gait initiation.

neuroscience↗

bioRxiv2022

Measuring brain critical dynamics to inform Brain-Computer Interfaces

Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces (BCI). To test this hypothesis, we used source-reconstructed magneto/electroencephalography, during resting state and a motor imagery task performed within a BCI protocol. To track the probability that an avalanche would spread across any two regions we built an avalanche transition matrix (ATM) and demonstrated that the edges whose transition probabilities significantly differed between conditions hinged selectively on premotor regions in all subjects. Furthermore, we showed that the topology of the ATMs allows task-decoding above the current gold standard. Hence, our results suggest that Neuronal Avalanches might capture interpretable differences between tasks that can be used to inform brain-computer interfaces.

neuroscience↗

bioRxiv2021

Time course of EEG power during creative problem-solving with insight or remote thinking

Problem-solving often requires creativity and is critical in everyday life. However, the neurocognitive mechanisms underlying creative problem-solving remain poorly understood. Two mechanisms have been highlighted: forming new connections from and between the problem elements and insight solving (with a sudden realization of a solution). We examined EEG activity during an adapted version of a classical insight problem task, the Remote Associates Test, that requires finding a word connecting three words. It allowed us to explore remoteness in semantic connections (by varying the remoteness of the solution word across trials) and insight solving (identified as a "Eureka" moment reported by the participants). Semantic remoteness was associated with a power increase in alpha band (8-12Hz) in a left parieto-temporal cluster, beta band (13-30Hz) in a right fronto-temporal cluster in the early phase of the task, and theta band (3-7Hz) in frontal cluster before the participants responded. Insight solving was associated with power increase preceding the response in alpha and gamma band (31-60Hz) in left temporal clusters and theta band in a frontal cluster. Source reconstructions show the brain regions associated with these clusters. Overall, our findings shed new light on the dynamic of some of the mechanisms involved in creative problem-solving.

neuroscience↗

bioRxiv2020

Selective neuromodulation induced by alpha-based neurofeedback learning: A double-blind randomized study

The neuromodulation induced by neurofeedback training (NFT) remains a matter of debate. Investigating the modulation of brain activity specifically associated with NF requires controlling for multiple factors, such as reward, performance, congruency between task and targeted brain activity. This can be achieved using sham feedback (FB) control condition, equating all aspects of the experiment but the link between brain activity and FB. We aimed at investigating the modulation of individual alpha EEG activity induced by NFT in a double-blind, randomized, sham-controlled study. Forty-eight healthy participants were assigned to either NF (n=25) or control (n=23) group and performed alpha upregulation training (over 12 weeks) with a wearable EEG device. Participants of the NF group received FB based on their individual alpha activity. The control group received the auditory FB of participants of the NF group. An increase of alpha activity across training sessions was observed in the NF group only (p<0.001). This neuromodulation was selective in that it was not observed for theta (4-8Hz) and low beta (13-18Hz) activities. While alpha upregulation was found in the NF group only, psychological outcome variables showed increased feeling of control, decreased anxiety level and increased relaxation feeling in both the NF and control groups, without any significant difference between groups. This is interpreted in terms of learning context and placebo effects. Our results pave the way to self-learnt, NF-based neuromodulation with light-weighted, wearable EEG systems.

neuroscience↗

bioRxiv2020

Visual information routes in the posterior dorsal and ventral face network studied with intracranial neurophysiology, and white matter tract endpoints

Occipito-temporal regions within the face network process perceptual and socio-emotional information, but the dynamics and information flow between different nodes of this network is still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight on the timing of face and social cue processing in the occipito-temporal brain and anchor the superior temporal cortex in dynamic gaze processing.

animal behavior and cognition↗

bioRxiv2018

Spatiotemporal neural correlates of brain-computer interface learning

Brain-computer interfaces have been largely developed to allow communication, control, and neurofeedback in human beings. Despite their great potential, BCIs perform inconsistently across individuals. Moreover, the neural processes activated by training that enable humans to achieve good control remain poorly understood. In this study, we show that BCI skill acquisition is paralleled by a progressive reinforcement of task-related activity and by the reduction of connectivity between regions beyond those primarily targeted during the experiments. Notably, these patterns of activity and connectivity reflect growing automaticity and predict future BCI performance. Altogether, our findings provide new insights in the neural mechanisms underlying BCI learning, which have implications for the use of this technology in a broad range of real-life applications.

neuroscience↗