OHBM 2019 symposium on neurofeedback

We are delighted to announce that our symposium “Multimodal Neurofeedback: The next generation of Neurofeedback for advanced brain self-regulation” has been accepted for OHBM 2019.and will take place on Thursday June 13th, 2019 from 8:00 to 9:15am.

Organizer : Christian Barillot, CNRS, Rennes, France

Co-Organizer : Giulia Lioi, Inria, Rennes France


  1. Christian Barillot, EMPENN U1228 team, Inserm, Inria, Irisa CNRS 6074, Rennes, France
  2. Jerzy Bodurka, Laureate Institute for Brain Research, Tulsa OK, USA
  3. Fabrizio De Vico Fallani, ARAMIS team, Inria, Brain and Spine Institute (ICM), Paris, France
  4. Benjamin Blankertz, TU Berlin, Germany.


There is a growing interest in neurofeedback (NF) and its potential as a clinical tool. While with the majority of NF applications have relied on EEG (which is the only modality used in the clinical practice to date), in the last years a variety of brain imaging techniques have been used to measure the brain activity (EEG, fMRI, fNIRS and MEG) that are used in NF, with a growing body of clinical applications. The aim of this symposium is to introduce a potential new generation of this technology that will combine online multimodal brain sensing to control the production of multidimensional NF. The symposium will be more research oriented than the educational course, and will particularly address the sum of technological, computational challenges and potential clinical applications that can be expected in the future from this emerging technological evolution. Another potential motivation for this symposium is to encourage the emergence of new teams and research community on this very recent field of research.


Neurofeedback (NF) belongs to the field of brain-computer interface (BCI). It provides individuals with real-time biofeedback of their brain activity and teaches them how to regulate their own brain functions by providing real-time sensory feedback of the brain “in action”. Brain activity can be measured using various non-invasive sensors, such as electro-encephalography (EEG) and magneto-encephalography (MEG) for direct neuronal activity, and functional magnetic resonance imaging (fMRI) or near-infrared spectroscopy (NIRS) for measuring related hemodynamics. Although EEG is currently the more common modality used by NF clinical practitioners, it often lacks of specificity due to its low spatial resolution. Research has therefore recently turned to explore the other brain functional modalities that target the activity of different regions of the brain more precisely. Though promising, current NF approaches suffer from the limitations of the technology, by providing either low spatial or temporal resolutions according to the sensor that is used. The future belongs to hybrid answers that combine the best of two different brain sensors. The symposium will address the sum of technological, computational challenges and potential clinical applications that can be expected in the future from this emerging technological evolution.

Learning objectives

  • The symposium will increase the creativity and innovation in the evolution of the clinical research practice
  • The symposium will enhance Skills and knowledge for potential new clinical research program on brain rehabilitation
  • The symposium will be engaged in the planning and delivery of interprofessional continuing education (i.e. between computational sciences and neurosciences)

Target audience

The symposium will address the Neurofeedback and BCI community and all researchers / practitioners interested in Neurorehabilitation, in particular:

  • Students and Researchers (all generations) in neuroscience interested in the development of new technologies to better provide endogenous brain stimulation using brain computer interfaces
  • Clinical researchers involved in brain pathologies interested in learning about the most recent advances in stimulating the brain for rehabilitation issues in various field of medicine (Neurology, Psychiatry, Physical and Rehabilitation Medicine)
  • Computational scientists interested in understanding the technological challenges of online integration of multimodal functional brain sensing with real-time processing of the brain activity

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