Utilizzi del Neurofeedback
– Potenziamento degli atleti a livello agonistico;
– Miglioramento delle peak performance dei top manager
– Maggior ‘lucidità’ nelle reazioni in situazioni di emergenza
– Prevenzione di situazioni negative a fronte di stress prolungati

Apprendimento attraverso il rinforzo
Fornisce al nostro cervello le informazioni necessarie affinché si attivino in sinergia i meccanismi di:
– rinforzo positivo per l’attivazione delle onde mentali funzionali all’obiettivo,
– rinforzo negativo per la disattivazione delle onde mentali disfunzionali all’obiettivo.

Bibliografia
Di seguito si riporta un estratto parziale di articoli e link dove poter trovare maggiori dettagli sul neurofeedback e sulla sua rilevanza scientifica.

https://www.researchgate.net/search.Search.html?type=publication&query=neurofeedback
https://en.wikipedia.org/wiki/Neurofeedback

– Cipresso, P., Gaggioli, A., Serino, S., Raspelli, S., Vigna, C., Pallavicini, F., & Riva, G. (2012). Inter-reality in the evaluation and treatment of psychological stress disorders: The INTERSTRESS project. Studies in Health Technology and Informatics, 181, 8–11.
– Cipresso, P., Soria-Frisch, A., Albajes-Eizagirre, A., Grau, C., Dunne, S., Ruffini, G., (2012). Electro-Physiological Data Fusion for Stress Detection. Annual Review of Cybertherapy and Telemedicine, 228-232.
– Davidson, R.J. (1992). Anterior cerebral asymmetry and the nature of emotion. Brain and Cognition factors. Psychophysiology, 35, 389-404.
– Hammond, D.C. (2007). What is neurofeedback? Journal of Neurotherapy, 10 (4), 25-36.
– Hao, Y., et al. (2014). A visual feedback design based on a Brain-Computer Interface to assist users regulate their emotional state. CHI, Apri 26 – May 01, 2491-2496.
– Wilson V., Moss D., Peper E. (2006) “The Mind Room” in Italian soccer training: The use of biofeedback and neurofeedback for optimum performance, Biofeedback volume 34, Issue 3, pp 79-81
– Harmony, T. (2013). The functional significance of delta oscillations in cognitive processing. Frontiers in Integrative Neuroscience, 7, art 83, 1-10. doi: 10.3389/fnint.2013.00083
– Katie, C., Aidan, S., Ian, P. & Dave, M. (2010). Evaluating a brain-computer interface to categorise human emotional response. Proc. 10th IEEE International Conference on Advanced Learning Technologies, pp. 276-278.
– Knyazev, G. (2012). EEG delta oscillations as a correlate of basic homeostatic and motivational processes. Neurosci. Bio behav. Rev. 36, 677-695. doi:10.1016/j. neubiorev.2011.10.002
– LeDoux J. (1996). The emotional brain. Phoenix, New York.
– Lim, C.A. & Chia, W.C. (2015). Analysis of single-electrode EEG rhythms using MATLAB to elicit correlation with cognitive stress. International Journal of Computer Theory and Engineering, 7, 149-155. doi:10.7763/IJCTE.2015.V7.947.
– Liu, Y., Sourina, O., & Nguyen, M.K. (2011). Real time EEG-based emotion recognition and its applications. In Transactions on computational science XII (pp. 256-277). Springer Berlin Heidelberg.
– Thut, G., Schyns, P.G. & Gross, J. (2011). Entrainment of perceptually relevant brain oscillations by non-invasive rhythmic stimulation of the human brain. Frontiers of Psychology, 2, 170. doi: 10.3389/ fpsyg.2011.00170.
– Zoefel, B., et al., (2010). Neurofeedback training of the upper alpha frequency band in EEG improves cognitive performance. NeuroImage. doi:10.1016/j.neuroimage.2010.08.078.