Version française Annuaire du personnel
M. Giovanni De marco
Enseignant-chercheur / Enseignante-chercheuse
Fonction
- Directeur du laboratoire LINP2 (Université Paris Nanterre)
- Directeur du laboratoire CeRSM – EA 2931 (Université Paris Nanterre) 2011-2019
- Directeur équipe « Analyse du Mouvement en Biomécanique, Physiologie et Imagerie» 2010-2019;
- Membre élu au Conseil Académique de la COMUE UPL 2015-2019
- Membre élu au comité d’éthique de la COMUE UPL 2016-2019
- Membre du conseil scientifique de l’ED 566 2010-à ce jour
- Membre du conseil scientifique de l’UFR STAPS Paris Nanterre 2009-à ce jour
- Responsable du parcours (Masters 1 et 2) Psychologie, Neurosciences, physiologie du mouvement et de la performance Paris Nanterre à partir de 2020
- Responsable du Master 2 Psychologie et Neurosciences du Mouvement:Exercice, Performance et Santé - UFR STAPS Paris Nanterre 2014–2019
- Membre élu du conseil scientifique du PRES UPL Paris Lumières 2012-2014
- Directeur du pôle « l’humain en devenir » (Paris Ouest Nanterre) 2012-2014
- Responsable du Master 2 contrôle Moteur - UFR STAPS Nanterre 2010-2013
- Responsable en Licence 3 de l’EC Initiation à la pratique de la Recherche 2014 –à ce jour.
Coordonnées
- Tél
- +33674610165
- giovanni.demarco@parisnanterre.fr
Disciplines enseignées
Mathematics, Statistics, Methodology, Computer Science, Biomechanics, Neurosciences, Neuroimaging, Medical Imaging;
- Development of concepts and methods in imaging associated with the fields of physics, biology, physiology, cognitive psychology and neuroscience;
- Development of concepts and methods in imaging associated with the fields of physics, biology, physiology, cognitive psychology and neuroscience;
- Study of the processes, treatments and complex visuomotor, cognitive-motor, affective and perceptual-action interactions at the cerebral level;
- Coupling and synchronization of electrophysiological devices (EMG, ECG, SCR, Eye-tracking, respiration, force, acceleration) with neuroimaging (fMRI, NIRS, EEG) and stimulation (tDCS, TMS) technics ;
- Modeling of neural circuitry to explore and analyze the integrative and adaptive mechanisms that are organized under the influence of the central, autonomic, peripheral nervous systems, and cerebral plasticity;
- Transfer of experimental paradigms and scientific knowledge in the field of physical activity and health.
- Coupling and synchronization of electrophysiological devices (EMG, ECG, SCR, Eye-tracking, respiration, force, acceleration) with neuroimaging (fMRI, NIRS, EEG) and stimulation (tDCS, TMS) technics ;
- Modeling of neural circuitry to explore and analyze the integrative and adaptive mechanisms that are organized under the influence of the central, autonomic, peripheral nervous systems, and cerebral plasticity;
- Transfer of experimental paradigms and scientific knowledge in the field of physical activity and health.
Thèmes de recherche
Recent advances in molecular and cellular biology, genetics, and computational neuroscience have considerably improved our understanding of the mechanisms governing living systems. Extending these foundations, our research aims to explain how interactions between the body, brain, and environment give rise to perception, action, cognition, and conscious experience across multiple spatial and temporal scales.
The brain is approached as a dynamic, adaptive, and self-organizing system, embedded within a broader physiological architecture that includes the autonomic nervous system. This perspective emphasizes the continuous interaction between central and peripheral processes, structured through hierarchical top-down and bottom-up dynamics that regulate perception, action, and internal states.
Within this framework, our work focuses on the analysis of brain activity as a multiscale system characterized by complex spatiotemporal dynamics, including synchronization/desynchronization processes, variability, and large-scale network interactions. Multimodal neuroimaging (fMRI, EEG, fNIRS), coupled with physiological and behavioral recordings, is used to investigate how neural systems integrate information and adapt to changing environmental and internal constraints.
A central line of research investigates perceptivo-motor control under conditions of uncertainty, with a specific focus on how the brain maintains stable behavior while continuously updating internal models. This is explored through the manipulation of geometric motor primitives (e.g., ellipse, infinity, clover shapes) across different sensory modalities (visual, haptic/proprioceptive, tactile), allowing us to characterize how sensorimotor representations are structured and revised.
This approach is grounded in the theoretical framework of the Free Energy Principle and active inference, where brain function is understood as a process of minimizing uncertainty through prediction and model updating. In this context, motor behavior is conceptualized as the expression of internal dynamic structures governed by geometric and kinematic invariants (e.g., curvature, velocity, acceleration, jerk), rather than as a sequence of discrete commands.
To capture these processes, we combine advanced analytical approaches including Dynamic Causal Modeling (DCM), Multivariate Pattern Analysis (MVPA), and graph theory. This integrative framework allows us to link local neural computations with large-scale network organization, and to investigate how cortical and cerebellar circuits interact to support the emergence, stabilization, and revision of perceptivo-motor representations.
A further objective is to integrate behavioral dynamics—such as speed, accuracy, and jerk—into neuroimaging analyses, providing quantitative markers of prediction error, online correction, and adaptive control. These measures are used to bridge computational modeling, movement kinematics, and brain activity within a unified framework.
In parallel, we develop multimodal EEG–fNIRS approaches to investigate cognitive and perceptual processes, including uncertainty processing, reversal learning, attentional flexibility, and decision-making. By combining the high temporal resolution of EEG with the spatial and hemodynamic sensitivity of fNIRS, this approach enables the characterization of multiscale neural dynamics underlying belief updating and precision modulation.
These research programs are applied to both fundamental and clinical contexts, particularly in the study of neurodegenerative disorders such as Amyotrophic Lateral Sclerosis and multiple sclerosis. A key objective is to better understand mechanisms of functional reorganization, compensatory plasticity, and allostatic regulation, in order to develop targeted interventions based on physical activity, neurostimulation, and cognitive training.
Overall, this work aims to contribute to a unified theoretical, neurobiological, and computational framework of brain function, emphasizing its dynamic, adaptive, and predictive nature, and to translate these insights into practical applications for health, performance, and learning.
The brain is approached as a dynamic, adaptive, and self-organizing system, embedded within a broader physiological architecture that includes the autonomic nervous system. This perspective emphasizes the continuous interaction between central and peripheral processes, structured through hierarchical top-down and bottom-up dynamics that regulate perception, action, and internal states.
Within this framework, our work focuses on the analysis of brain activity as a multiscale system characterized by complex spatiotemporal dynamics, including synchronization/desynchronization processes, variability, and large-scale network interactions. Multimodal neuroimaging (fMRI, EEG, fNIRS), coupled with physiological and behavioral recordings, is used to investigate how neural systems integrate information and adapt to changing environmental and internal constraints.
A central line of research investigates perceptivo-motor control under conditions of uncertainty, with a specific focus on how the brain maintains stable behavior while continuously updating internal models. This is explored through the manipulation of geometric motor primitives (e.g., ellipse, infinity, clover shapes) across different sensory modalities (visual, haptic/proprioceptive, tactile), allowing us to characterize how sensorimotor representations are structured and revised.
This approach is grounded in the theoretical framework of the Free Energy Principle and active inference, where brain function is understood as a process of minimizing uncertainty through prediction and model updating. In this context, motor behavior is conceptualized as the expression of internal dynamic structures governed by geometric and kinematic invariants (e.g., curvature, velocity, acceleration, jerk), rather than as a sequence of discrete commands.
To capture these processes, we combine advanced analytical approaches including Dynamic Causal Modeling (DCM), Multivariate Pattern Analysis (MVPA), and graph theory. This integrative framework allows us to link local neural computations with large-scale network organization, and to investigate how cortical and cerebellar circuits interact to support the emergence, stabilization, and revision of perceptivo-motor representations.
A further objective is to integrate behavioral dynamics—such as speed, accuracy, and jerk—into neuroimaging analyses, providing quantitative markers of prediction error, online correction, and adaptive control. These measures are used to bridge computational modeling, movement kinematics, and brain activity within a unified framework.
In parallel, we develop multimodal EEG–fNIRS approaches to investigate cognitive and perceptual processes, including uncertainty processing, reversal learning, attentional flexibility, and decision-making. By combining the high temporal resolution of EEG with the spatial and hemodynamic sensitivity of fNIRS, this approach enables the characterization of multiscale neural dynamics underlying belief updating and precision modulation.
These research programs are applied to both fundamental and clinical contexts, particularly in the study of neurodegenerative disorders such as Amyotrophic Lateral Sclerosis and multiple sclerosis. A key objective is to better understand mechanisms of functional reorganization, compensatory plasticity, and allostatic regulation, in order to develop targeted interventions based on physical activity, neurostimulation, and cognitive training.
Overall, this work aims to contribute to a unified theoretical, neurobiological, and computational framework of brain function, emphasizing its dynamic, adaptive, and predictive nature, and to translate these insights into practical applications for health, performance, and learning.
Curriculum Vitae
Jallouli S., Jallouli D., Damak M., Sakka S., Ghroubi S., Mhiri C., Driss T., de Marco G., Ayadi F., Hammouda O. 12-week melatonin intake attenuates cardiac autonomic dysfunction and oxidative stress in multiple sclerosis patients: a randomized controlled trial. Metabolic Brain Disease. 2025;40(1):52. ePub 2024-12.
Jallouli S., Ghroubi S., Bouattour N., Maaloul R., Elleuch M.H., Yahia A., de Marco G., Driss T., Hammouda O. Effects of Melatonin Supplementation on Muscle Strength, Manual Dexterity, and Postural Balance in Patients Living with Multiple Sclerosis – A Randomized Controlled Trial. Journal of Dietary Supplements. 2025;22(2):236-261. doi:10.1080/19390211.2024.2449030.
Mouazen B., Benali A., Chebchoub N.T., de Marco G. Enhancing EEG-Based Emotion Detection with Hybrid Models: Insights from DEAP Dataset Applications. ResearchGate preprint. Mars 2025.
Ezzedini S., Abidi M., de Marco G. Enhancing cognitive and motor performance through mental training: The interplay between temporal preparation, inhibition and autonomic arousal. Cognitive, Affective, & Behavioral Neuroscience. 2025;25(5):1359-1377.
Mouazen B., Bendaouia A., Abdelwahed E.H., de Marco G. Machine learning and clinical EEG data for multiple sclerosis: A systematic review. Artificial Intelligence in Medicine. 2025;166:103116.
Jallouli S., Jallouli D., Damak M., Kallel C., Sakka S., Jaafar B., Mhiri C., de Marco G., Ayadi F., Hammouda O. Self-paced combined training alleviated oxidative stress, inflammatory responses and hyperlipidaemia in people living with multiple sclerosis: a randomized controlled trial. Archives of Physiology and Biochemistry. 2025;131(3):432-444. ePub 2024-12.
Souabni M., Souabni M.J., Salem A., Hammouda O., Ammar A., Saidi O., Zmijewski P., Jahrami H., de Marco G., Trabelsi K., Driss T. Napping and memory consolidation in early childhood: A systematic review and meta-analysis. Sleep Medicine. 2025;133:106649.
Mouazen B., Bendaouia A., Bellakhdar O., Laghdaf K., Abdelwahed E.H., de Marco G. Transparent EEG analysis: leveraging autoencoders, Bi-LSTMs and SHAP for improved neurodegenerative disease detection. Sensors. 2025;25(18):5690.
Arcangeli D., Arnold G., Roby-Brami A., de Marco G., Jarrassé N., Parry R. Perception of Paired Vibrotactile Stimulus on the Upper Limb: Implications for the Design of Wearable Technology. In: Haptics: Science, Technology, Applications (EuroHaptics 2024), Lecture Notes in Computer Science, vol. 15080. Springer, Cham, 2024:419-427.
Langley C, de Marco G, Daly S, Masuda N, Davies Smith A, Jones R, Bruce J, Thai NJ. Neural substrates of alerting dysfunction in females with Multiple Sclerosis. December 2024. Multiple Sclerosis and Related Disorders 93, 106208.
Rekik W, Le Hégarat-Mascle S, Ezzedini S, de Marco G. Detection of atypical attentional behaviors in young subjects. Journal of Neuroscience Methods. July 2024. Volume 407, 110141. (Q2, IF 2.7)
Jallouli S, Ghroubi S, Damak M, Sakka S, Elleuch M, Mhiri C, Yahia A, Driss T, de Marco G, Hammouda O. 12-week melatonin supplementation improved dynamic postural stability and walking performance in persons living with multiple sclerosis: A randomized controlled trial. Behavioural Brain Research. 2024-08, p.115191. (Q2, IF 2.6)
Torkhani E, Bennequin D, de Marco G. Role of the Cerebellum in the construction of functional and geometrical spaces. Cerebellum, 2024, Apr 16, P 1-26 (Q1, IF 3.5).
Jallouli S, Maalou R, Ghroubi S, Kammoun R, Damak M Sakka S, Driss T, de Marco G, Mhiri C, Habib Elleuch M, Feki W, Hammouda O. Benefits of self-paced concurrent training on lung function, cardiopulmonary fitness and fatigue perception in patients with multiple sclerosis. Neurodegenerative Disease Management, 2024. Volume 14, N°5, P 173-187 (Q1, IF 2.3)
Ezzedini S, Ben Jebara S, Abidi M, de Marco G. Influence of Mental Training of Attentional Control on Autonomic Arousal Within the Framework of the Temporal Preparation of a Force Task. 2023. Cognitive Science 47, 1-20.(Q1, IF 2.5)
Langley† C, Masuda N, Godwin S, de Marco G, Smith AD, Jones R, Bruce J and Thai NJ. Dysfunction of basal ganglia functional connectivity associated with subjective and cognitive fatigue in multiple sclerosis. Front. Neuroscience 2023. 17:1194859. doi: 10.3389/fnins.2023.1194859 (Q1, IF : 4.3)
Arcangeli, D.; Dubois, O.; Roby-Brami, A.; Famié, S.; de Marco, G.; Arnold, G.; Jarrassé, N.; Parry, R. Human Exteroception during Object Handling with an Upper Limb Exoskeleton. Sensors 2023, 23, 5158. https://doi.org/10.3390/s23115158.(Q1, IF : 3.9)
Abidi M, Pradat PF, Termoz N, Couillandre A, Bede P, de Marco G. Motor Imagery in ALS: an fMRI study of postural control. Neuroimage Clinical, 2022 (Q1, IF : 4.891).
Vallée R†, Vallée A, Vallée JN, Abidi M, Couillandre A, Termoz N, Pradat PF, de Marco G. Theoretical discrimination index of postural instability in amyotrophic lateral sclerosis. Sci Rep. 2022; 12: 2430 (IF : 4.997)
Torkhani E, Dematte E, Slawinski J, Csillik A, Gay MC, Bensmaïl D, Heinzlef O, de Marco G. Improving Health of People With Multiple Sclerosis From a Multicenter Randomized Controlled Study in Parallel Groups: Preliminary Results on the Efficacy of a Mindfulness Intervention and Intention Implementation Associated With a Physical Activity Program. Front Psychol. 2021 Dec 24;12:767784. (IF : 4.232)
Grami F; de Marco G; Bodranghien F, Manto M; Habas C. Cerebellar transcranial direct current stimulation reconfigurates brain networks involved in motor and mental imagery. The Cerebellum. August, 2021, P2-12 (Q1, IF : 3.5).
Grami F; de Marco G; Bodranghien F, Manto M; Habas C. Cerebellar transcranial direct current stimulation reconfigurates static and dynamic functional connectivity of the resting-state networks. Cerebellum & Ataxias. 2021. 8, Article number: 7. (Q2, IF : 1.5).
Abidi M, de Marco G, Grami* F, Termoz N, Couillandre A, Querin G, Bede P, Pradat PF. J Magn Reson Imaging. 2021 Jan ;53(1):223-233. doi: 10.1002/jmri.27335. Epub 2020 Sep 7. (Q1, IF : 5.119)
Abidi M, de Marco G, Couillandre A, Feron M, Mseddi E, Termoz N, Querin G, Pradat PF, Bede P. Adaptive functional reorganization in amyotrophic lateral sclerosis: coexisting degenerative and compensatory changes. Eur J Neurol. 2020 Jan;27(1):121-128 (Q1, IF : 6.288).
Daly S, Thai J, Belkhiria C, Langley† C, Le Blanche A, de Marco G. Temporal deployment of attention by mental training: an fMRI study. Cognitive, affective and behavioral neuroscience. 2020 May (Q1, IF: 3.526)
Belkhiria C, Mssedi E, Habas C, Driss T, de Marco G. Collaboration of Cerebello-Rubral and Cerebello-Striatal Loops in a Motor Preparation Task. Cerebellum. 2019 Apr;18(2):203-211. (Q1, IF: 3.5)
Feron M, Couillandre A, Mseddi E, Termoz N, Abidi M, Pradat PF, de Marco G. Extrapyramidal deficits in ALS: a combined biomechanical and neuroimaging study. J Neurol. 2018 Sep;265(9):2125-2136. (Q1, IF: 6.682)
Abidi M, Bruce J, Le Blanche A, Bruce A, Jarmolowicz DP, Csillik A, Thai NJ, Lim SL, Heinzlef O, de Marco G. Neural mechanisms associated with treatment decision making: an fMRI study. Behav Brain Res. 2018 april 20, 349, 54-62. (Q1, IF: 2.77)
Belkhiria C, Driss T, Habas C, Jaafar H, Guillevin R, de Marco G. Exploration and identification of cortico-cerebellar-brainstem closed loop during a motivational-motor task: an fMRI study. The Cerebellum, 2017. (Q1, IF: 3.20)
Corps
PROFESSEUR DES UNIVERSITES
COLLABORATIONS DE RECHERCHE
• Clinical Research and Imaging Center de Bristol (UK)
• University of Missouri-Kansas City (US)
• Institut Cerveau Moelle (ICM) Pitié-Salpêtrière (Paris)
• Hôpitaux parisiens Pitié-Salpêtrière, Quinze-Vingts et Lariboisière
• Hôpitaux périphériques de Garches, Cergy, Poissy
• Hôpitaux de province : Poitiers, Tours
COLLABORATIONS DE RECHERCHE
• Clinical Research and Imaging Center de Bristol (UK)
• University of Missouri-Kansas City (US)
• Institut Cerveau Moelle (ICM) Pitié-Salpêtrière (Paris)
• Hôpitaux parisiens Pitié-Salpêtrière, Quinze-Vingts et Lariboisière
• Hôpitaux périphériques de Garches, Cergy, Poissy
• Hôpitaux de province : Poitiers, Tours
Informations complémentaires
Mis à jour le 29 mars 2026
Directeur du laboratoire LINP2 (UPN)
UFR STAPS
200 Avenue de la République
92001 NANTERRE CEDEX, France
gdemarco@parisnanterre.fr
Tel: 0033 +1 40 97 57 55
UFR STAPS
200 Avenue de la République
92001 NANTERRE CEDEX, France
gdemarco@parisnanterre.fr
Tel: 0033 +1 40 97 57 55