Decoded neurofeedback: Difference between revisions
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'''Decoded Neurofeedback''' (DecNef) is the process of inducing [[knowledge]] in a subject by increasing [[neuron|neural]] activation in predetermined regions in the [[brain]], such as the [[visual cortex]]. This is achieved by measuring neural activity in these regions via [[functional magnetic resonance imaging]] (FMRI), comparing this to the ideal pattern of neural activation in these [[List of regions in the human brain|regions]] (for the intended purpose), and giving subjects [[feedback]] on how close their current pattern of neural activity is to the ideal pattern. Without explicit knowledge of what they are supposed to be doing or thinking about, over time participants learn to induce this ideal pattern of neural activation. Corresponding to this, their 'knowledge' or way of thinking has been found to change accordingly. |
'''Decoded Neurofeedback''' (DecNef) is the process of inducing [[knowledge]] in a subject by increasing [[neuron|neural]] activation in predetermined regions in the [[brain]], such as the [[visual cortex]]. This is achieved by measuring neural activity in these regions via [[functional magnetic resonance imaging]] (FMRI), comparing this to the ideal pattern of neural activation in these [[List of regions in the human brain|regions]] (for the intended purpose), and giving subjects [[feedback]] on how close their current pattern of neural activity is to the ideal pattern. Without explicit knowledge of what they are supposed to be doing or thinking about, over time participants learn to induce this ideal pattern of neural activation. Corresponding to this, their 'knowledge' or way of thinking has been found to change accordingly. |
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Revision as of 11:32, 31 May 2020
 | This article includes a list of references, related reading, or external links, but its sources remain unclear because it lacks inline citations. (January 2012) |
Decoded Neurofeedback (DecNef) is the process of inducing knowledge in a subject by increasing neural activation in predetermined regions in the brain, such as the visual cortex. This is achieved by measuring neural activity in these regions via functional magnetic resonance imaging (FMRI), comparing this to the ideal pattern of neural activation in these regions (for the intended purpose), and giving subjects feedback on how close their current pattern of neural activity is to the ideal pattern. Without explicit knowledge of what they are supposed to be doing or thinking about, over time participants learn to induce this ideal pattern of neural activation. Corresponding to this, their 'knowledge' or way of thinking has been found to change accordingly.
Experiments conducted in 2011 at Boston University (BU) and ATR Computational Neuroscience Laboratories in Kyoto, Japan demonstrated that volunteers were able to quickly solve complex visual puzzles they had not previously had exposure to. They did so by receiving the brain patterns of other volunteers who had already learned to solve the puzzles through trial and error methods.
The research has far-reaching implications for treating patients with various learning disabilities, mental illness, memory problems, and motor functionality impairments.