Medial frontal negativities predict performance improvements during motor sequence but not motor adaptation learning

Neural markers of error processing relate to task performance, but not to substance-related risks and problems and externalizing problems in adolescence and emerging adulthood

Detecting errors and adapting behavior accordingly constitutes an integral aspect of cognition. Previous studies have linked neural correlates of error processing (e.g., error-related negativity (ERN) and error-related positivity (Pe)) to task performance and broader behavioral constructs, but few studies examined how these associations manifest in adolescence. In this study, we examined neural error processing markers and their behavioral associations in an adolescent/emerging adult sample (N = 143, Mage = 18.0 years, range 11-25 years), employing a stop-signal task. Linear regressions were conducted using bootstrap resampling to explore associations between ERN/Pe peak amplitudes and latencies, stop accuracy, stop-signal reaction time (SSRT), and post-error slowing, as well as self-reported substance-related risks and problems and externalizing problems. After adjusting for age and sex, smaller frontocentral Pe amplitude and later Pe latency were associated with longer SSRT, and later Pe latency was associated with lower stop accuracy. This might indicate that the Pe, which is thought to reflect conscious error processing, reflects task performance on a response inhibition task better than the ERN, which reflects subconscious error processing. After correcting for multiple testing, there were no associations between ERN/Pe parameters and substance-related or externalizing problems, and no age interactions for these associations were detected.

Response monitoring in math-anxious individuals in an arithmetic task

We examine whether math anxiety is related to altered response monitoring in an arithmetic task. Response-locked event-related brain potentials (ERPs) were evaluated in 23 highly (HMA) and 23 low math-anxious (LMA) individuals while they performed an arithmetic verification task. We focused on two widely studied ERPs elicited during error processing: error-related negativity (ERN) and error positivity (Pe). Correct-related negativity (CRN), an ERP elicited after a correct response, was also studied. The expected ERN following errors was found, but groups did not differ in its amplitude. Importantly, LMA individuals showed less negative CRN and more positive Pe amplitudes than their more anxious peers, suggesting more certainty regarding response accuracy and better adaptive behavioral adjustment after committing errors in an arithmetic task in the LMA group. The worse control over response performance and less awareness of correct responses in the HMA group might reduce their ability to 'learn from errors'.

Bridging event-related potentials with behavioral studies in motor learning

Behavioral approaches and electrophysiology in understanding human sensorimotor systems have both yielded substantial advancements in past decades. In fact, behavioral neuroscientists have found that motor learning involves the two distinct processes of the implicit and the explicit. Separately, they have also distinguished two kinds of errors that drive motor learning: sensory prediction error and task error. Scientists in electrophysiology, in addition, have discovered two motor-related, event-related potentials (ERPs): error-related negativity (ERN), and feedback-related negativity (FRN). However, there has been a lack of interchange between the two lines of research. This article, therefore, will survey through the literature in both directions, attempting to establish a bridge between these two fruitful lines of research.

Behavioral Analysis of EEG Signals in Loss-Gain Decision-Making Experiments

Extraction and analysis of the EEG (electroencephalograph) information features generated during behavioral decision-making can provide a better understanding of the state of mind. Previous studies have focused more on the brainwave features after behavioral decision-making. In fact, the EEG before decision-making is more worthy of our attention. In this study, we introduce a new index based on the reaction time of subjects before decision-making, called the Prestimulus Time (PT), which have important reference value for the study of cognitive function, neurological diseases, and other fields. In our experiments, we use a wearable EEG feature signal acquisition device and a systematic reward and punishment experiment to obtain the EEG features before and after behavioral decision-making. The experimental results show that the EEG generated after behavioral decision due to loss is more intense than that generated by gain in the medial frontal cortex (MFC). In addition, different characteristics of EEG signals are generated prior to behavioral decisions because people have different expectations of the outcome. It will produce more significant negative-polarity event-related potential (ERP) in the forebrain area when the humans are optimistic about the outcomes.

Correct response negativity may reflect subjective value of reaction time under regulatory fit in a speed-rewarded task

Error-related negativity (ERN), an electroencephalogram (EEG) component following an erroneous response, has been associated with the subjective motivational relevance of error commission. A smaller EEG event, the correct response negativity (CRN), occurs after a correct response. It is unclear why correct behavior evokes a neural response similar to error commission. CRN might reflect suboptimal performance: in tasks where speed is motivationally relevant (i.e., incentivized), a correct but slow response may be experienced as a minor error. The literature is mixed on the relationship between CRN and response time (RT), possibly due to different motivational structures, tasks, or individual traits. We examined ERN and CRN in a go/no-go task where correctness and speed were encouraged using a points-based feedback system. A key individual trait, regulatory focus, describes a person's tendency to seek gains (promotion focus) and avoid losses (prevention focus). Trait regulatory focus was measured, and participants were randomly assigned to one of three conditions: points gain, points loss, and informative-only feedback. Participants committed too few errors to reliably model ERN effects. CRN amplitude related to RT in all feedback conditions, with slower responses having larger CRN. Participants with stronger promotion focus had a more exaggerated RT/CRN relationship in the point gain condition, suggesting that regulatory fit influences the motivational relevance of speed and thus the negative subjective experience and CRN for slower responses. These findings are consistent with the claim that CRN reflects RT when RT is motivationally relevant and that the CRN/RT relationship reflects the degree of subjective motivational relevance.

Medial frontal negativities predict performance improvements during motor sequence but not motor adaptation learning

Alterations in our environment require us to learn or alter motor skills to remain efficient. Also, damage or injury may require the relearning of motor skills. Two types have been identified: movement adaptation and motor sequence learning. Doyonet al. (2003, Distinct contribution of the cortico-striatal and cortico-cerebellar systems to motor skill learning. Neuropsychologia, 41(3), 252-262) proposed a model to explain the neural mechanisms related to adaptation (cortico-cerebellar) and motor sequence learning (cortico-striatum) tasks. We hypothesized that medial frontal negativities (MFNs), event-related electrocortical responses including the error-related negativity (ERN) and correct-response-related negativity (CRN), would be trait biomarkers for skill in motor sequence learning due to their relationship with striatal neural generators in a network involving the anterior cingulate and possibly the supplementary motor area. We examined 36 participants' improvement in a motor adaptation and a motor sequence learning task and measured MFNs elicited in a separate Spatial Stroop (conflict) task. We found both ERN and CRN strongly predicted performance improvement in the sequential motor task but not in the adaptation task, supporting this aspect of the Doyon model. Interestingly, the CRN accounted for additional unique variance over the variance shared with the ERN suggesting an expansion of the model.