Detection of Error Related Neuronal Responses Recorded by Electrocorticography in Humans during Continuous Movements

Abstract

BackgroundBrain-machine interfaces (BMIs) can translate the neuronal activity underlying a user’s movement intention into movements of an artificial effector. In spite of continuous improvements, errors in movement decoding are still a major problem of current BMI systems. If the difference between the decoded and intended movements becomes noticeable, it may lead to an execution error. Outcome errors, where subjects fail to reach a certain movement goal, are also present during online BMI operation. Detecting such errors can be beneficial for BMI operation: (i) errors can be corrected online after being detected and (ii) adaptive BMI decoding algorithm can be updated to make fewer errors in the future.Methodology/Principal FindingsHere, we show that error events can be detected from human electrocorticography (ECoG) during a continuous task with high precision, given a temporal tolerance of 300–400 milliseconds. We quantified the error detection accuracy and showed that, using only a small subset of 2×2 ECoG electrodes, 82% of detection information for outcome error and 74% of detection information for execution error available from all ECoG electrodes could be retained.Conclusions/SignificanceThe error detection method presented here could be used to correct errors made during BMI operation or to adapt a BMI algorithm to make fewer errors in the future. Furthermore, our results indicate that smaller ECoG implant could be used for error detection. Reducing the size of an ECoG electrode implant used for BMI decoding and error detection could significantly reduce the medical risk of implantation.

Augmenting intracortical brain-machine interface with neurally driven error detectors

“…Thus, the key scientific contribution of this study is that, to our knowledge, this is the first report of task outcome-related spiking neural activity in M1 and PMd. These results using intracortical recordings significantly expand a recent ECoG study [19,71] which suggested the presence of error signals in motor cortex. First, we showed that error signals are present in both PMd and M1, and that they appear earlier in PMd compared to M1.…”

“…This open question is an important area for future investigation; recent encouraging ECoG results indeed showed evidence for such activity in motor cortex [71]. We predict that one source of differences that may be encountered during translation stems from human BMI movements being self-initiated by the user, in contrast to experimenter-paced monkey tasks.…”

Brain Responses to Errors During 3D Motion in a Hapto-Visual VR

“…ACC takes part in action monitoring and detection of errors [26]. On the other hand in line with our results, non-haptic Electrocorticography (ECoG) invasive studies on execution errors during continuous 1D motion [6,7], did not show significant error related activation in the ACC. Using fMRI, random target jumps and visuo-motor rotations were found to activate the posterior or anterior aspects of the parietal cortex, respectively; but not the ACC [33].…”

“…Interface errors can occur in any type of controlled motion, and are defined as execution errors. Execution errors occur when an unexpected movement was performed instead of the intended one [6][7][8]. Error Related Potentials (ErrPs) evoked by errors and embedded in the ongoing Electroencephalography (EEG) (non-invasive brain signal recording) [8] are used to decrease the misclassification rate [4].…”

“…Previous work on ErrP used non-haptic interfaces in a one dimensional (1D) [11] or two dimensional (2D) environments [8]. Execution errors in all of these experiments were artificially induced by random inversion of the motion direction, opposite to the intended [6][7][8]11]. A stereoscopic 3D world, highly resembling the physical world was designed for improved immersion in the experiment, and for enhanced validity of transfer to real-life situations, such as required in rehabilitation or telesurgery.…”