Invariability of EEG error-related potentials during continuous feedback protocols elicited by erroneous actions at predicted or unpredicted states

Abstract

Objective. When humans perceive an erroneous action, an EEG error-related potential (ErrP) is elicited as a neural response. ErrPs have been largely investigated in discrete feedback protocols, where actions are executed at discrete steps, to enable seamless brain-computer interaction. However, there are only a few studies that investigate ErrPs in continuous feedback protocols. The objective of the present study is to better understand the differences between two types of ErrPs elicited during continuous feedback protocols, where errors may occur either at predicted or unpredicted states. We hypothesize that ErrPs of the unpredicted state is associated with longer latency as it requires higher cognitive workload to evaluate actions compared to the predicted states. Approach. Participants monitored the trajectory of an autonomous cursor that occasionally made erroneous actions on its way to the target in two conditions, namely, predicted or unpredicted states. After characterizing the ErrP waveform elicited by erroneous actions in the two conditions, we performed single-trial decoding of ErrPs in both synchronous (i.e. time-locked to the onset of the erroneous action) and asynchronous manner. Furthermore, we explored the possibility to transfer decoders built with data of one of the conditions to the other condition. Main results. As hypothesized, erroneous actions at unpredicted states gave rise to ErrPs with higher latency than erroneous actions at predicted states, a correlate of higher cognitive effort in the former condition. Moreover, ErrP decoders trained in a given condition successfully transferred to the other condition with a slight loss of classification performance. This was the case for synchronous as well as asynchronous ErrP decoding, showing the invariability of ErrPs across conditions. Significance. These results advance the characterization of ErrPs during continuous feedback protocols, enlarging the potential use of ErrPs during natural operation of brain-controlled devices as it is not necessary to have different decoders for each kind of erroneous conditions.

EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

“…2c). Although we have further analyzed datasets collected during our previous studies (27,29), we did not observe such gamma band activity nor theta-gamma phase-amplitude coupling. A distinction between those previous studies and the present study is that in the latter subjects performed corrective actions upon perception of an error.…”

“…We observed band specific power modulation for theta [4, 8] Hz (26, 27), beta [18, 30] Hz (31, 32) and gamma [60, 90] Hz rhythms (17) (Fig. 2a and b).…”

“…Nevertheless, in these studies actions were executed at discrete steps, not continuously as required here. Some BCIs have succeeded in decoding the presence of an ErrP during a continuous task (24)(25)(26)(27). However, these studies used experimental protocols where erroneous actions are abrupt stops of the device (24,25), errors happen at the same moment during the interaction (26,28), or the device fails to reach a target (27)-all extreme conditions that do not capture erroneous actions during a continuous interaction, but see Batzianoulis et al (29).…”

“…Some BCIs have succeeded in decoding the presence of an ErrP during a continuous task (24)(25)(26)(27). However, these studies used experimental protocols where erroneous actions are abrupt stops of the device (24,25), errors happen at the same moment during the interaction (26,28), or the device fails to reach a target (27)-all extreme conditions that do not capture erroneous actions during a continuous interaction, but see Batzianoulis et al (29). Furthermore, none of these previous studies characterized the ErrP signals as a function of the severity of the erroneous action.…”

EEG Peak Detection in Cognitive Conflict Processing Using Summit Navigator and Clustering-Based Ranking

“…This trait is also essential for the development of promising applications EEG signal processing, where the intra-and inter-subject variability is not avoidable. As error-related potentials can be exploited to improve the performance of BCIs [10], [40], the dissimilarity between conflict and non-conflict peaks will be investigated in our future work for the enhancement of a communication assistance system.…”