Single trial-based prediction of a go/no-go decision in monkey superior colliculus
Neural Networks - 2006 Special issue: Neurobiology of decision making
International Journal of Imaging Systems and Technology - Human Brain Imaging
Editorial: Recent advances in brain-machine interfaces
Neural Networks
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Brain-machine interfaces (BMIs) have the potential to improve the quality of life for individuals with disabilities. We engaged in the development of neural mind-reading techniques for cognitive BMIs to provide a readout of decision processes. We trained 2 monkeys on go/no-go tasks, and monitored the activity of groups of neurons in their mid-brain superior colliculus (SC). We designed a virtual decision function (VDF) reflecting the continuous progress of binary decisions on a single-trial basis, and applied it to the ensemble activity of SC neurons. Post hoc analyses using the VDF predicted the cue location as well as the monkey's motor choice (go or no-go) soon after the presentation of the cue. These results suggest that our neural mind-reading techniques have the potential to provide rapid real-time control of communication support devices.