M. Giovanni De marco


- 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.


UFR STAPS (bâtiment Alice Milliat) Bureau S307 - 200 Avenue de la République 92001 NANTERRE CEDEX FRANCE
UFR des Sciences et Techniques des Activités Physiques et Sportives (STAPS)
Ecole doctorale Sciences du sport, de la motricité et du mouvement humain

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;
- Study of the processes, treatments and complex visuomotor, cognitive-motor, affective and perceptual-motor 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 of cerebral plasticity;
- Transfer of university knowledge in the field of physical activity and health.

Thèmes de recherche

Spectacular progress in molecular and cellular biology and genetics has made it possible to make great strides in the knowledge of living beings, in particular in the understanding of the microscopic, competitive and homeostatic mechanisms that govern our organic life. In the extension of this fundamental work, cognitive sciences, computational neurosciences, artificial neural networks and other artificial intelligence (AI) techniques come together to try to explain how, on a meso- and macroscopic scale, the human experience and "Body-Brain-Environment" interactions participate in the emergence of our perceptions, intuitions, sensations, actions from which our judgments, our feelings, our beliefs, our moods, our ruminations built our thoughts and cerebral states of consciousness. The human brain has been self-organizing and adapting itself for hundreds of thousands of years (homo sapiens) with its billions of neurons and tens of thousands of connections per neuron which seem limitless and central in the system of living things (including animal). Its evolutionary history depends on hereditary transmission by descent and acquired experiences associated with the personal, social, cultural and technological environment which over time in a chaotic and uninterrupted flow nourishes the activity of circuits and neural networks housing our thoughts and our consciousness. The brain as a central nervous system (CNS) is not isolated. It is supplemented by other systems such as the vegetative nervous system (or ANS) which autonomously participates in the functioning of bodily organs, controls and regulates (via the sympathetic, parasympatic, enteric systems) cardiac, respiratory, vascular activity, glandular; its functional contribution to the CNS and its participation in the brain organization must be deepened, particularly in the top down and bottom up hierarchy of cognitive and mental processes. It is highly probable that the orchestrating power of the CNS associated with the ANS is a determining element in the construction of human and animal thought. The spatial and temporal organization and deployment of brain activity compels us to explore and analyze the brain as an energetic, dynamic, complex and multivariate system capable of establishing bidirectional mono and multisynaptic connections in space-time, discontinuous, transitional with more or less controlled and lasting states. The propagation of neuronal activity or brain waves over different distances (short / wide scales), with intensities (hypo / hyperconnected), powers and frequencies different rhythm and codes the brain information that takes root in these dynamic tangles stable (unstable), synchronized (desynchronized) and stochastic neural states that we try to break down and elucidate in the light of multidisciplinary knowledge and with the help of brain exploration techniques and methods of analyzing the signal extremely sophisticated. The fusion of multimodal information, brain stimulation techniques and algorithmic learning methods associated with the analysis of the activity and the functional and structural interactivity (connectivity) of neural networks provides an inovative framework for deepening the neurophysiological, psychological and cognitive mechanisms that contribute to the mental imagery of the mind, rational / irrational and the development of conscious (intentional / anticipatory) and pseudo-conscious (intuitive / instinctive) thinking. All the research work carried out in neuroimaging at LINP2 makes it possible to highlight the link that exists between the body, behavior and cognition in an interactive and multisensory manner to feed the integrative hypotheses of cerebral functioning. Imaging research is carried out in the field of experimental and cognitive neurosciences and is applied in the health sector, making it possible to elucidate the behavioral consequences of cerebral lesions / infections, the loss of integrity of neural networks and the degradation of brain functions found in certain neurodegenerative disorders such as Charcot's disease (ALS) and multiple sclerosis (MS).
To conclude, we hope to contribute to the development of a theoretical, neurobiological and computational framework of the dynamic, evolutionary and adaptive functioning of the brain and of the cerebral circuits which compose it; apply concretely this research work through the development of learning and therapeutic methods to instruct, train and (re) organize neural networks; set up educational methods (in connection with executive functions and attentional processes), neuropsychological intervention (mindfulness, meditation), electrophysiological (magnetic / electrical stimulation) and physical activity (exercises, training) to modulate / strengthen neural plasticity and improve cognitive and motor functions in healthy and pathological subjects. Finally, we hope that this research will contribute to a significant advance in knowledge on the complex and amazing functioning of the brain and human thought.

Curriculum Vitae

- 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. (Q1, IF :3.9).
- M Abidi, G de Marco, F Grami, N Termoz, A Couillandre, G Querin, P Bede, PF Pradat. Neural Correlates of Motor Imagery of Gait in Amyotrophic Lateral Sclerosis. J Magn Reson Imaging 2021.doi: 10.1002/jmri.27335(IF : 3.954)
- 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, 7. (Q2, IF :1.1).
- Saidane Y, Parry R, Belkhiria C, Ben Jebara S, Driss T, de Marco G. Effects of mental effort on premotor muscle activity and maximal grip. Journal of Motor Behavior. 2021 May (IF 1.31)
- 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 : 4.387).
- 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 (IF: 2.67)
- de Marco G. Aspects neurophysiologiques de la prise de risque. Rev Neurol (Paris) (IF :1.91). 2020. https://doi.org/10.1016/j.neurol.2020.01.027
- 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 (IF 4.387)
- Gao-Galibert S, Dematte E, Slawinski J, Fournier J, Ruffault A, Gay MC, Bensmaïl D, Heinzlef O, de Marco G. État des connaissances sur l’apport de l’activité physique dans la SEP et méthodes d’interventions psychologiques : passé, présent, futur. Neurologies, 2020 : vol 23, Num 224, 152-161. D
- 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. (IF: 3.41).
- Feron M, Couillandre A, Mseddi E, Termoz N, Abidi M, Bede P, Pradat PF, de Marco G. Extrapyramidal deficits in ALS: a combined biomechanical and neuroimaging study. J Neurol. 2018 Sep;265(9):2125-2136. (IF: 4.20)
- 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. (IF: 3.002)
- Belkhiria C, Driss T, Habas C, Guillevin R, de Marco G. Exploration and identification of cortico-cerebellar-brainstem closed loop during a cognitive-motor task: an fMRI study. The Cerebellum, 2017. (IF: 3.9).
- Bodranghien F, Mahé H, Baude B, Manto MU, Busegnies Y, Camut S, Habas C, Marien P, de Marco G, van Dun K. The Click Test: A Novel Tool to Quantify the Age-Related Decline of Fast Motor Sequencing of the Thumb. Curr Aging Sci. 2017 May 10. doi: 10.2174/1874609810666170511100318. (IF 1.33)
- Belkhiria C, de Marco G, Driss T. Effects of verbal encouragement on force and electromyographic activations during handgrip exercise. J Sports Med Phys Fitness. 2017 May 9. doi: 10.23736/S0022-4707.17.07282-6. (IF 1.3)
- Thompson S, Daly S, Le Blanche A, Abidi M, Belkhiria C, Driss T, de Marco G. fMRI Randomized Study of Mental and Motor Task Performance and Cortisol: Levels to Potentiate Cortisol as a New Diagnostic Biomarker. Journal of Neurology and Neuroscience (Open Access). 2016. Vol. 7 No. 2: 92. (IF 1.45)
- Costalat R, Francoise JP, Menuel C, Lahutte M, Vallée JN, de Marco G, Chiras J, Guillevin R. Mathematical Modeling of Metabolism and Hemodynamics. Acta Biotheor. Acta Biotheor. 2012 Jun;60(1-2):99-107. Impact Factor = 1.707.
- Liacu D, Idy-Peretti I, Ducreux D, Bouilleret V, de Marco G. Quantitative fiber tracking findings in cingulum fibers of patients with temporal lobe epilepsy. J Magn Reson Imaging, Impact factor = 2.747. J Magn Reson Imaging. 2012 Sep;36(3):561-8. (IF 3.95)
- Lehmann P, Saliou G, de Marco G, Monet P, Souraya SE, Bruniau A, Vallée JN, Ducreux D. Cerebral peritumoral oedema study: Does a single dynamic MR sequence assessing perfusion and permeability can help to differentiate glioblastoma from metastasis? Eur J Radiol. 2012 Mar;81(3):522-7. Impact Factor = 2.941, 5-Year Impact Factor: 2.673
- Guillevin R, Menuel C, Taillibert S, Capelle L, Costalat R, Abud L, Habas C, de Marco G, Hoang-Xuan K, Chiras J, Vallée JN. Predicting the outcome of grade II glioma treated with temozolomide using proton magnetic resonance spectroscopy. Br J Cancer. 2011 Jun 7;104(12):1854-61. Impact factor = 4.346
- Liacu D, de Marco G, Ducreux D, Bouilleret V, Masnou P, Idy-Peretti, I. Diffusion tensor changes in epileptogenic hippocampus of TLE patients with and without hippocampal sclerosis. Neurophysiol Clin. 2010 Jun;40(3). Impact factor = 1.693
- Perin B, Godefroy O, Fall S, de Marco G. Alertness in young healthy subjects: An fMRI study of brain region interactivity enhanced by a warning signal. Brain Cogn. 2010 Mar;72(2):271-81. Impact factor = 2.84, 5-Year Impact Factor: 3.05.
- de Marco G, Devauchelle B, Berquin P. Brain functional modeling, what do we measure with fMRI data? Neurosci Res. 2009 May;64(1):12-9. Impact factor = 2.096, 5-Year Impact Factor: 2.339.
- de Marco G, Vrignaud P, Destrieux C, de Marco D, Devauchelle B, Berquin P. Principle of Structural Equation Modeling for Exploring Functional Interactivity within a Putative Network of Interconnected Brain Areas. Magn Reson Imaging 2009 Jan; 27(1):1-12. Impact Factor: 2.042, 5-Year Impact Factor: 2.144.
- Querne L, Berquin P, Vernier MP, Fall S, Deltour L, de Marco G. Dysfunction of the attentional brain network in children with Developmental Coordination Disorder: a fMRI study. Brain Research, 2008, 1244, 89-102. Impact Factor: 2.623, 5-Year Impact Factor: 2.665.
- Quaglino V, Bourdin B, Czternasty G, Vrignaud P, Fall S, Meyer ME, Berquin P, Devauchelle B, de Marco G. Differences in effective connectivity between dyslexic children and normal readers during a pseudoword reading task: An fMRI study. Neurophysiol Clin. 2008 Apr;38(2):73-82. Impact factor =1.693
- Fall S., de Marco G. Assessment of brain interactivity in the motor cortex from the concept of functional connectivity and spectral analysis of fMRI data. Biol Cybern. 2008 Feb; 98(2):101-114. Impact factor =1.7
- Fall S., de Marco G. On multivariate spectral analysis of fMRI signals theoretical approach. Neurophysiol Clin. 2007 Aug-Sep; 37(4):229-37. Impact factor =2.55
- de Marco G, de Bonis M, Vrignaud P, Henry-Feugeas MC, Idy-Peretti I. Changes in effective connectivity during incidental and intentional perception of fearful faces. NeuroImage, 2006, 30(3):1030-1037. Impact factor = 5.93, 5-Year Impact Factor: 6.817.
- de Marco G, Idy-Peretti I, Didon-Poncelet A, Baledent O, Onen F, Henry Feugeas MC. Intracranial fluid dynamics in normal and hydrocephalic states: systems analysis with phase contrast MR imaging. J Comput Assist Tomogr, 2004, Vol 28, 2, 247-254. Impact Factor = 1.383
- de Marco G, Bogdanov A, Marecos E, Moore A, Simonova M, Weissleder. MR Imaging of Gene Delivery to the Central Nervous System Using an Artificial Vector. Radiology, 1998, 208:65-71. Impact Factor = 6.066.




• 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 25 mars 2023