https://www.biorxiv.org/content/biorxiv/early/2019/10/16/787101.full.pdf Here we hypothesize that observing the visual stimuli of different categories trigger distinct brain states that can be decoded from noninvasive EEG recordings. We introduce an effective closed-loop BCI system that reconstructs the observed or imagined stimuli images from the co-occurring brain wave parameters. The reconstructed images are presented to the subject as a visual feedback. The developed system is applicable to training BCI-naïve subjects because of the user-friendly and intuitive way the visual patterns are employed to modify the brain states. [...] Our stimulation protocol can be considered as a cognitive test that aims to extract subject-specific stable EEG patterns. Each person has specific reactions to different kinds of visual stimuli, thus, for an effective BCI paradigm a preliminary step of individual stimuli set selection from some excessive basic set could be of a great value. Another benefit of this approach is that no additional cognitive task for attention or memory is required, and the subject can remain completely passive throughout the session. This makes it possible to implement this protocol for the patients with cognitive disorders. Basing on the results achieved through the developed experimental protocol, we proposed a novel closed-loop BCI system, which is capable of real-time image reconstruction from the subject’s EEG features. We developed a deep learning model which consists oftwo separately trained deep learning networks, one of which is used for decoding of different categories of images, and the second one transforms the EEG features into the image decoder spatial domain. We demonstrated that the proposed technique can potentially be used for training BCI-naïve subjects by replacing the original stimuli with the subject’s mind-driven image reconstruction model. We suggest that using native feedback could produce a strong self-regulating effect and help a BCI operator to master the imagery commands more effectively. ____ Fortuna che per il momento questi pattern stabili sono "subject specific". Giacomo