Motor imagery (MI) is widely used in sports, in particular for motor learning and anxiety management [1]. Indeed, athletes consistently report using MI for rehearsing technique, maintaining arousal or enhancing self-confidence [2]. However, optimal gains are limited by the fact that they receive no feedback and cannot assess their performance. This can have detrimental effects on their motivation to diligently practice MI. Therefore, using Neurofeedback (NF) appears to be an adapted solution, allowing athletes to know if they are correctly performing the task. This addition also makes it possible to objectify performance and quantify progression throughout the sessions. In fact, three recent meta-analysis testify that NF improves the ability to self-regulate brain activity and sport performance [3, 4, 5]. The number of papers using MI-NF protocols has increased in the past few years. However, their efficiency has been shown to depend on various factors such as expertise in the imagined task [6], personality traits [7], MI ability [8] or NF acceptability [9]. Some of these factors can be assessed using validated questionnaires [10,11,12] but items are generally focused on questioning the current use of MI or thoughts on NF. An issue, as we know that practice can sometimes differ from real needs and expectations. To our knowledge, no previous work has investigated sports field actors’ preferences with the aim of designing specific NF tools, perfectly fitted to their profile, goals and expectations. Therefore, based on pre-existing questionnaires, we will build and broadcast an online questionnaire for athletes where personality, MI use, NF acceptability and NF preferences will be assessed. This method will enable us to personalise MI-NF trainings to fit each athlete’s needs. A longitudinal study will then require that athletes follow a personalised procedure to investigate how it impacts their MI and NF performances as well as their acceptability levels. [1] Guillot, A., & Collet, C. (2008). Construction of the Motor Imagery Integrative Model in Sport : A review and theoretical investigation of motor imagery use. International Review of Sport and Exercise Psychology, 1. [2] Munroe, K. J., Giacobbi Jr., P. R., Hall, C., & Weinberg, R. (2000). The Four Ws of Imagery Use : Where, When, Why, and What. Sport Psychologist, 14(2), 119. [3] Mirifar, A., Beckmann, J., & Ehrlenspiel, F. (2017). Neurofeedback as supplementary training for optimizing athletes’ performance: A systematic review with implications for future research. Neuroscience & Biobehavioral Reviews, 75, 419 432. [4] Xiang, M.-Q., Hou, X.-H., Liao, B.-G., Liao, J.-W., & Hu, M. (2018). The effect of neurofeedback training for sport performance in athletes: A meta-analysis. Psychology of Sport and Exercise, 36, 114 122. [5] Gong, A., Gu, F., Nan, W., Qu, Y., Jiang, C., & Fu, Y. (2021). A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience. Frontiers in Neuroscience, 15. [6] Kraeutner, S. N., McWhinney, S. R., Solomon, J. P., Dithurbide, L., & Boe, S. G. (2018). Experience modulates motor imagery-based brain activity. European Journal of Neuroscience, 47(10), 1221 1229. [7] Jeunet, C., N’Kaoua, B., Subramanian, S., Hachet, M., & Lotte, F. (2015). Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns. PLOS ONE, 10(12), e0143962. [8] Guillot, A., Collet, C., Nguyen, V. A., Malouin, F., Richards, C., & Doyon, J. (2008). Functional neuroanatomical networks associated with expertise in motor imagery. NeuroImage. [9] Morone, G., Pisotta, I., Pichiorri, F., Kleih, S., Paolucci, S., Molinari, M., Cincotti, F., Kübler, A., & Mattia, D. (2015). Proof of principle of a brain-computer interface approach to support poststroke arm rehabilitation in hospitalized patients: Design, acceptability, and usability. Archives of Physical Medicine and Rehabilitation, 96(3 Suppl), S71-78. [10] Hall, C. R., Rodgers, W. M., & Barr, K. A. (1990). The Use of Imagery by Athletes in Selected Sports. The Sport Psychologist, 4(1), 1 10. [11] Plaisant, O., Courtois, R., Réveillère, C., Mendelsohn, G. A., & John, O. P. (2010). Validation par analyse factorielle du Big Five Inventory français (BFI-Fr). Analyse convergente avec le NEO-PI-R. Annales Médico-psychologiques, revue psychiatrique, 168(2), 97 106. [12] Grevet, E., Forge, K., Tadiello, S., Izac, M., Amadieu, F., Brunel, L., Pillette, L., Py, J., Gasq, D., & Jeunet-Kelway, C. (2023). Modeling the acceptability of BCIs for motor rehabilitation after stroke: A large scale study on the general public. Frontiers in Neuroergonomics, 3.