P. J. Allen, O. Josephs, and R. Turner, A method for removing imaging artifact from continuous EEG recorded during functional MRI, NeuroImage, vol.12, pp.230-239, 2000.

E. Bagarinao, A. Yoshida, M. Ueno, K. Terabe, S. Kato et al., Improved volitional recall of motor-imagery-related brain activation patterns using real-time functional MRI-based neurofeedback, Front. Hum. Neurosci, vol.12, p.158, 2018.

B. D. Berman, S. G. Horovitz, G. Venkataraman, and M. Hallett, Selfmodulation of primary motor cortex activity with motor and motor imagery tasks using real-time fMRI-based neurofeedback, NeuroImage, vol.59, pp.917-925, 2012.

N. Birbaumer, S. Ruiz, and R. Sitaram, Learned regulation of brain metabolism, Trends Cogn. Sci, vol.17, pp.295-302, 2013.

M. L. Blefari, J. Sulzer, M. C. Hepp-reymond, S. Kollias, and R. Gassert, Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery, Front. Behav. Neurosci, vol.9, p.18, 2015.

L. V. Bradnam, C. M. Stinear, and W. D. Byblow, Ipsilateral motor pathways after stroke: implications for non-invasive brain stimulation, Front. Hum. Neurosci, vol.7, p.184, 2013.

M. A. Cervera, S. R. Soekadar, J. Ushiba, J. R. Del-millán, M. Liu et al., Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis, Ann. Clin. Transl. Neurol, vol.5, pp.651-663, 2018.

M. Chiew, S. M. Laconte, and S. J. Graham, Investigation of fMRI neurofeedback of differential primary motor cortex activity using kinesthetic motor imagery, NeuroImage, vol.61, pp.21-31, 2012.

D. Pino, G. Pellegrino, G. Assenza, G. Capone, F. Ferreri et al., Modulation of brain plasticity in stroke: a novel model for neurorehabilitation, Nat. Rev. Neurol, vol.10, pp.597-608, 2014.

I. Favre, T. A. Zeffiro, O. Detante, A. Krainik, M. Hommel et al., Upper limb recovery after stroke is associated with ipsilesional primary motor cortical activity: a meta-analysis, Stroke, vol.45, pp.1077-1083, 2014.

W. Förstner and B. Moonen, A metric for covariance matrices, pp.113-128, 1999.

A. R. Fugl-meyer, L. Jaasko, I. Leyman, S. Olsson, and S. Steglind, The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand, J. Rehabil. Med, vol.7, pp.13-31, 1975.

M. Grosse-wentrup, D. Mattia, and K. Oweiss, Using brain-computer interfaces to induce neural plasticity and restore fuction, J. Neural. Eng, vol.8, p.25004, 2011.

S. Hétu, M. Grégoire, A. Saimpont, M. P. Coll, F. Eugène et al., The neural network of motor imagery: an ALE meta-analysis, Neurosci. Biobehav. Rev, vol.37, pp.930-949, 2013.

A. Jaillard, C. D. Martin, K. Garambois, and J. Franc, Vicarious function within the human primary motor cortex? A longitudinal fmri stroke study, Brain, vol.128, pp.1122-1138, 2005.
URL : https://hal.archives-ouvertes.fr/inserm-00391162

S. L. Jong, M. K. Han, H. K. Sung, O. K. Kwon, J. et al., Fiber tracking by diffusion tensor imaging in corticospinal tract stroke: topographical correlation with clinical symptoms, NeuroImage, vol.26, pp.771-776, 2005.

S. Liew, M. Rana, S. Cornelsen, M. F. De-barros-filho, N. Birbaumer et al., Improving motor corticothalamic communication after stroke using real-time fMRI connectivity-based neurofeedback, Neurorehabil. Neural Repair, vol.30, pp.671-675, 2016.

R. Likert, A technique for the measurement of attitudes, Arch. Psychol, vol.140, pp.5-55, 1932.

G. Lioi, M. Fleury, S. Butet, A. Lécuyer, C. Barillot et al., , 2018.

, Bimodal EEG-fMRI neurofeedback for stroke rehabilitation: a case report, Ann. Phys. Rehabil. Med, vol.61, pp.482-483

M. Mano, A. Lécuyer, E. Bannier, L. Perronnet, S. Noorzadeh et al., How to build a hybrid neurofeedback platform combining EEG and fMRI, Front. Neurosci, vol.11, p.140, 2017.
URL : https://hal.archives-ouvertes.fr/inserm-01576500

D. M. Mehler, A. N. Williams, F. Krause, M. Lührs, R. G. Wise et al., The BOLD response in primary motor cortex and supplementary motor area during kinesthetic motor imagery based graded fMRI neurofeedback, NeuroImage, vol.184, pp.36-44, 2019.

M. Mihara, N. Hattori, M. Hatakenaka, H. Yagura, T. Kawano et al., Near-infrared spectroscopy-mediated neurofeedback enhances efficacy of motor imagery-based training in poststroke victims A pilot study, Stroke, vol.44, pp.1091-1098, 2013.

S. J. Page, G. D. Fulk, and P. Boyne, Clinically important differences for the upper-extremity fugl-meyer scale in people with minimal to moderate impairment due to chronic stroke, Phys. Ther, vol.92, pp.791-798, 2012.

L. Perronnet, L. Anatole, M. Mano, E. Bannier, M. Clerc et al., Unimodal versus bimodal EEG-fMRI neurofeedback of a motor imagery task, Front. Hum. Neurosci, vol.11, p.193, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01519755

L. Perronnet, L. Anatole, M. Mano, M. Clerc, F. Lotte et al., Learning 2-in-1: towards integrated EEG-fMRI-neurofeedback, BioRxiv, vol.397729, 2018.

G. Pfurtscheller and F. H. Lopes-da-silva, Event-related EEG/MEG synchronization and desynchronization: basic principles, Clin. Neurophysiol, vol.110, pp.1842-1857, 1999.

F. Pichiorri, G. Morone, M. Petti, J. Toppi, I. Pisotta et al., Brain-computer interface boosts motor imagery practice during stroke recovery, Ann. Neurol, vol.77, pp.851-865, 2015.

E. Plow, D. Dunningham, N. Varnerin, and A. G. Machado, Rethinking stimulation of the brain in stroke rehabilitation: why higher motor areas might be better alternatives for patients with greater impairments, Neuroscientist, vol.21, pp.225-240, 2015.

H. Ramoser, J. Müller-gerking, and G. Pfurtscheller, Optimal spatial filtering of single trial EEG during imagined hand movement, IEEE Trans. Rehabil. Eng, vol.8, pp.441-446, 2000.

N. Sharma, P. S. Jones, T. A. Carpenter, and J. C. Baron, Mapping the involvement of BA 4a and 4p during motor imagery, NeuroImage, vol.41, pp.92-99, 2008.

N. Sharma, M. Uk, V. M. Pomeroy, and J. Baron, Motor imagery: a backdoor to the motor system after stroke, Stroke, vol.37, pp.1941-1952, 2006.

R. Sitaram, T. Ros, L. Stoeckel, S. Haller, F. Scharnowski et al., Closed-loop brain training: the science of neurofeedback, Nat. Rev. Neurosci, vol.18, pp.86-100, 2017.

R. Sitaram, R. Veit, B. Stevens, A. Caria, C. Gerloff et al., Acquired control of ventral premotor cortex activity by feedback training: an exploratory real-time fMRI and TMS study, Neurorehabil. Neural Repair, vol.26, pp.256-265, 2012.

A. Solodkin, P. Hlustik, E. E. Chen, and S. L. Small, Fine modulation in network activation during motor execution and motor imagery, Cereb. Cortex, vol.14, pp.1246-1255, 2004.

B. Sorger, T. Kamp, N. Weiskopf, J. C. Peters, and R. Goebel, When the brain takes 'BOLD' steps: real-time fmri neurofeedback can further enhance the ability to gradually self-regulate regional brain activation, Neuroscience, vol.378, pp.71-88, 2018.

C. M. Stinear, P. A. Barber, M. Petoe, S. Anwar, and W. D. Byblow, The PREP algorithm predicts potential for upper limb recovery after stroke, Brain, vol.135, pp.2527-2535, 2012.

C. M. Stinear, P. A. Barber, P. R. Smale, J. P. Coxon, M. K. Fleming et al., Functional potential in chronic stroke patients depends on corticospinal tract integrity, Brain, vol.130, pp.170-180, 2007.

R. T. Thibault, A. Macpherson, M. Lifshitz, R. R. Roth, and A. Raz, Neurofeedback with fMRI: a critical systematic review, NeuroImage, vol.172, pp.786-807, 2018.

T. Wang, D. Mantini, and C. R. Gillebert, The potential of real-time fMRI neurofeedback for stroke rehabilitation, Cortex, vol.107, pp.148-165, 2017.

M. L. Woodbury, C. A. Velozo, L. G. Richards, and P. W. Duncan, Rasch analysis staging methodology to classify upper extremity movement impairment after stroke, Arch. Phys. Med. Rehabil, vol.94, pp.1527-1533, 2013.

X. Wu, T. Wu, Z. Zhan, L. Yao, W. et al., A real-time method to reduce ballistocardiogram artifacts from eeg during fmri based on optimal basis sets (OBS), Comput. Methods Programs Biomed, vol.127, pp.114-125, 2016.

C. Zich, S. Debener, C. Kranczioch, M. G. Bleichner, I. Gutberlet et al., Real-time EEG feedback during simultaneous EEG-fMRI identifies the cortical signature of motor imagery, NeuroImage, vol.114, pp.438-447, 2015.

C. Zich, S. Debener, C. Schweinitz, A. Sterr, J. Meekes et al., High intensity chronic stroke motor imagery neurofeedback training at home: three case reports, Clin. EEG Neurosci, vol.48, pp.403-412, 2017.

V. Zotev, R. Phillips, H. Yuan, M. Misaki, and J. Bodurka, Selfregulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback, NeuroImage, vol.85, pp.985-995, 2014.