​Launched in 2013 as a flagship project on Emerging Technologies of the Future (EU-FET), the Human Brain Project (HBP) is the largest brain science project in Europe. Now entering its final phase (Specific Grant Agreement 3, SGA3), HBP's activities will focus on three themes: i) neural networks, studied at different spatial and temporal scales; ii) their significance for consciousness and consciousness disorders; iii) the development of artificial neural networks and neurorobotics. For this final phase, 7 new projects have been selected for funding from October 2020 to March 2023. One of them is the collaborative project Brain Inspired Consciousness (BRICON), led by Fanis Panagiotaropoulos, INSERM researcher at UNICOG laboratory in NeuroSpin, directed by Stanislas Dehaene.

BRICON, a project of the neuroscience activities of HBP (WP2: Networks underlying Cognition and Consciousness), is an international collaboration of experimenters and computational neuroscientists, including Gustavo Deco (Pompeu Fabra University), Alain Destexhe (NeuroPSI/CNRS), Lucia Melloni (Max Planck Institute), Pieter Roelfsema (Netherlands Institute of Neurosciences) and Stanislas Dehaene (NeuroSpin/Collège de France). The objective of this consortium is to combine neurophysiological data with computational models and neuromorphic simulations to improve our understanding of consciousness, one of the greatest enigmas of science. The main question is how does the electrochemical activity of our brain give rise to conscious perception and subjective experience? This explanatory gap in our understanding, the so-called "hard problem of consciousness", is often seen as an insurmountable obstacle to scientific research. However, it is likely that this problem seems "hard" simply because we do not understand in detail the complex brain processes that underlie it. To this end, the BRICON project : i) will provide measures of brain activity during conscious perception at multiple scales, from single neurons to mesoscopic networks and whole brain activity; ii) validate and limit computational models using neurophysiological data; iii) implement the models in neuromorphic hardware for real-time biological simulations.