Neuroscience
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The manipulation of remote agents such as robotic arms in remote surgery or in BCI-wheelchair control are prone to errors. Some of these are related to user intent misclassification or other interface system errors, which lead to an incorrect movement. Here we focused on errors originating from unpredicted interface movements violating user intent and producing sensory conflicts. ⋯ Incongruence between visual and proprioceptive feedback in interface errors not only elicited distinct EEG signal characteristics, but also produced a marginally significant Stroop effect. Incongruency in visuo-haptic feedback modalities cause a delayed user response. This effect is of major importance for the design of controlling interfaces and can provide designers with crucial information when aiming to control human response time.
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This study investigates the error processing components in the EEG signal of Performers and Observers using an auditory lexical decision task, in which participants heard spoken items and decided for each item if it was a real word or not. Pairs of participants were tested in both the role of the Performer and the Observer. In the literature, an Error Related Negativity (ERN)-Error Positivity (Pe) complex has been identified for performed (ERN-Pe) and observed (oERN-oPe) errors. ⋯ Our hypothesis regarding the ERN was not supported, however a Pe-like effect, as well as a P300 were present. Analyses to disentangle lexical and error processing similarly indicated a P300 for errors, and the results furthermore pointed to differences between responses before and after word offset. The findings are interpreted as marking attention during error processing during auditory word recognition.
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The prediction of the sensory consequences of physical movements is a fundamental feature of the human brain. This function is attributed to a forward model, which generates predictions based on sensory and efferent information. The neural processes underlying such predictions have been studied using the error-related negativity (ERN) as a fronto-central event-related potential in electroencephalogram (EEG) tracings. ⋯ The findings suggest that early in learning, the motor control system relies more on information from external feedback about terminal outcome. With increasing task performance, the forward model is able to generate more accurate outcome predictions, which, as a result, increasingly contributes to error processing. The data also suggests a complementary relationship between the ERN and the FRN over motor learning.