Alix Lamouroux

Neurofeedback-induced network plasticity in motor and default mode networks correlates with motor recovery after stroke

Alix Lamouroux, Julie Coloigner, Pierre Maurel, Nicolas Farrugia et autres

Abstract Stroke often results in long-term motor impairments, necessitating innovative rehabilitation strategies. Neurofeedback (NF) has emerged as a promising tool to promote functional recovery after stroke by enabling patients to modulate targeted brain activity. In this study, we investigated how NF training …

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Reliable measurement of brain connectivity after stroke : methods and application to neurofeedback rehabilitation

Alix Lamouroux

Mesure fiable de la connectivité cérébrale après AVC : méthodes et application à la rééducation par neurofeedback L’AVC est une cause majeure de déficiences motrices durables, nécessitant des stratégies de rééducation innovantes. La connectivité fonctionnelle mesurée par IRMf est un marqueur pertinent …

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Data-Driven Identification of Functional Network Changes in Neurofeedback Stroke Rehabilitation: a Clinical Validation of Network-Based Statistics

Alix Lamouroux, Julie Coloigner, Pierre Maurel, Nicolas Farrugia et autres

Functional connectivity (FC) analysis is crucial for understanding neuroplasticity in stroke rehabilitation. Neuro-feedback (NF) training has shown promise in facilitating recovery, but its whole-brain effects remain poorly understood due to limitations in traditional FC analysis methods. Many studies rely on region-of-interest (ROI)-based …

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Neurofeedback-Induced Network Plasticity in Motor and Default Mode Networks Correlates with Motor Recovery After Stroke

Alix Lamouroux, Julie Coloigner, Pierre Maurel, Nicolas Farrugia et autres

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Evaluating lesion-specific preprocessing pipelines for rs-fMRI in stroke patients: Impact on functional connectivity and behavioral prediction

Alix Lamouroux, Julie Coloigner, Pierre Maurel, Nicolas Farrugia et autres

Functional magnetic resonance imaging (fMRI) is essential for studying brain function and connectivity. Resting-state fMRI, which captures spontaneous brain activity without task requirements, is particularly suited for individuals with post-stroke impairments. However, the inherent noise and artifacts in fMRI signals can compromise …

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fMRIStroke: A preprocessing pipeline for fMRI Data from Stroke patients

Alix Lamouroux, Giulia Lioi, Julie Coloigner, Pierre Maurel et autres

Functional Magnetic Resonance Imaging (fMRI) is a widely used neuroimaging technique for the analysis of neural activity and functional connectivity.However, the fMRI signal is inherently noisy and susceptible to various artifacts, compromising the accuracy and reliability of derived analyses.This becomes particularly critical …

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Explicit and automatic ejection fraction assessment on 2D cardiac ultrasound with a deep learning-based approach

Olivier Moal, Émilie Roger, Alix Lamouroux, Chloe Younes et autres

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Beta and Theta Oscillations Correlate With Subjective Time During Musical Improvisation in Ecological and Controlled Settings: A Single Subject Study

Nicolas Farrugia, Alix Lamouroux, Christophe Rocher, Jules Bouvet et autres

In this paper, we describe the results of a single subject study attempting at a better understanding of the subjective mental state during musical improvisation. In a first experiment, we setup an ecological paradigm measuring EEG on a musician in free improvised …

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Beta and theta oscillations correlate with subjective time during musical improvisation in ecological and controlled settings: a single subject study

Nicolas Farrugia, Alix Lamouroux, Christophe Rocher, Jules Bouvet et autres

Abstract In this paper, we describe the results of a single subject study attempting at a better understanding of the subjective state during musical improvisation. In a first experiment, we setup an ecological paradigm measuring EEG on a musician in free improvised …

fr (code pays fourni par la source)