Humans are social animals, and feelings of attachment, connection and empathy are the glue that binds societies together. Before an infant’s immune system is fully operational, before a baby can even use its hands, it recognizes its parents’ voices, responds uniquely to human faces and even, incredibly, smiles back.
Yet, some people, often as the result of traumatic experiences or neglect, don’t experience these fundamental social feelings normally. Could a machine teach them these quintessentially human responses? A thought-provoking Brazilian study recently published in PLoS One suggests it could.
Researchers at the D’Or Institute for Research and Education outside Rio de Janeiro, Brazil, performed functional MRI scans on healthy young adults while asking them to focus on past experience that epitomized feelings of non-sexual affection or pride of accomplishment. They set up a basic form of artificial intelligence to categorize, in real time, the fMRI readings as affection, pride or neither. They then showed the experiment group a graphic form of biofeedback to tell them whether their brain results were fully manifesting that feeling; the control group saw the meaningless graphics.
The results demonstrated that the machine-learning algorithms were able to detect complex emotions that stem from neurons in various parts of the cortex and sub-cortex, and the participants were able to hone their feelings based on the feedback, learning on command to light up all of those brain regions.
Jorge Moll, the lead researcher, told Singularity Hub that the participants weren’t beating the system by faking feelings, because that would lead to its own fMRI pattern. They were learning to feel a particular emotion more completely.
Click below to read the full article: http://www.singularityhub.com/2014/06/16/machines-teach-humans-how-to-feel-using-neurofeedback/
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