Closed-loop adaptation of neurofeedback based on mental effort facilitates reinforcement learning of brain self-regulation

Brain-computer and brain-machine interfaces (BCI/BMI) are utilized in a variety of neurological and neuropsychiatric conditions (Daly and Wolpaw 2008). While assistive interfaces aim to replace lost functions by controlling external devices, the goal of restorative approaches is to reduce disease-specific symptoms. By providing contingent feedback of specific neuronal states, restorative BCI/BMI use operant conditioning to reinforce the targeted brain states or dynamic modulations for achieving behavioral gains (Sherlin et al.

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