Abstract

The ability to predict action content from neural signals in real time before the ac-tion occurs has been long sought in the neuroscientific study of decision-making,agency and volition. On-line real-time (ORT) prediction is important for under-standing the relation between neural correlates of decision-making and conscious,voluntary action as well as for brain-machine interfaces. Here, epilepsy patients,implanted with intracranial depth microelectrodes or subdural grid electrodes forclinical purposes, participated in a “matching-pennies” game against an opponent.In each trial, subjects were given a 5 s countdown, after which they had to raisetheir left or right hand immediately as the “go” signal appeared on a computerscreen. They won a fixed amount of money if they raised a different hand thantheir opponent and lost that amount otherwise. The question we here studied wasthe extent to which neural precursors of the subjects’ decisions can be detected inintracranial local field potentials (LFP) prior to the onset of the action.We found that combined low-frequency (0.1–5 Hz) LFP signals from 10 electrodeswere predictive of the intended left-/right-hand movements before the onset of thego signal. Our ORT system predicted which hand the patient would raise 0.5 sbefore the go signal with 68±3% accuracy in two patients. Based on these results,we constructed an ORT system that tracked up to 30 electrodes simultaneously,and tested it on retrospective data from 7 patients. On average, we could predictthe correct hand choice in 83% of the trials, which rose to 92% if we let the systemdrop 3/10 of the trials on which it was less confident. Our system demonstrates—for the first time—the feasibility of accurately predicting a binary action on singletrials in real time for patients with intracranial recordings, well before the actionoccurs. 1