Evidence for a general performance‐monitoring system in the human brain

Abstract

Adaptive behavior relies on the ability of the brain to form predictions and monitor action outcomes. In the human brain, the same system is thought to monitor action outcomes regardless of whether the information originates from internal (e.g., proprioceptive) and external (e.g., visual) sensory channels. Neural signatures of processing motor errors and action outcomes communicated by external feedback have been studied extensively; however, the existence of such a general action‐monitoring system has not been tested directly. Here, we use concurrent EEG‐MEG measurements and a probabilistic learning task to demonstrate that event‐related responses measured by electroencephalography and magnetoencephalography display spatiotemporal patterns that allow an effective transfer of a multivariate statistical model discriminating the outcomes across the following conditions: (a) erroneous versus correct motor output, (b) negative versus positive feedback, (c) high‐ versus low‐surprise negative feedback, and (d) erroneous versus correct brain–computer‐interface output. We further show that these patterns originate from highly‐overlapping neural sources in the medial frontal and the medial parietal cortices. We conclude that information about action outcomes arriving from internal or external sensory channels converges to the same neural system in the human brain, that matches this information to the internal predictions.

Disentangling effects of expectancy, accuracy, and empathy on the processing of observed actions

“…We found that Trial Type (true or false belief) did not account for significantly more variance when included in the model, suggesting that the differences found between the Trial Types in the first analysis was due to differences in expectancy and no other processes were at play. The same was true for Accuracy, which supports findings that it is expectancy, not valence, that influences ERPs that were previously linked to error monitoring (Desmet et al, 2014;Ferdinand et al, 2012;Jessup et al, 2010;Oliveira et al, 2007;Schiffer et al, 2014;Wessel et al, 2012Wessel et al, , 2014Zubarev & Parkkonen, 2018). We also found that a model including trait empathy in addition to expectancy did not explain significantly more variance than a model not including trait empathy.…”

“…However, these study designs make it impossible to disentangle the processing of expectation violations from error processing. Recent evidence has emphasized the role of predictions and prediction errors for ACC activity, indicating that the ACC, and consequently also those ERP components with an ACC origin that were previously associated with error processing, may code for unexpected events rather than errors (Alexander & Brown, 2011;Desmet et al, 2014;Ferdinand et al, 2012;Jessup et al, 2010;Oliveira et al, 2007;Schiffer et al, 2014;Wessel et al, 2012Wessel et al, , 2014Zubarev & Parkkonen, 2018). While watching the actions of others, observers seem to form predictions (Donnarumma et al, 2017;Flanagan & Johansson, 2003;Friston et al, 2012).…”

Meta-analyses of the functional neural alterations in subjects with Internet gaming disorder: Similarities and differences across different paradigms

“…Neurological abnormalities in the DMN, as well as in the precuneus, PCC, and IFG, may contribute to the behavioral inhibition deficits associated with IGD-related cognitive dysfunction(Dong et al 2017a; Wang et al 2017a). The FPN is the key brain network for predicting and monitoring action outcomes(Zubarev and Parkkonen 2018).Some addiction studies reported changes in the FPN(Costumero et al 2017),including studies examining cocaine-dependent people (Barrós-Loscertales et al2011) and smokers(Clewett et al 2014). Consistent with previous studies, the right IFG in the ATN showed abnormalities in IGD(Hong et al 2018).Restingstate fMRI also revealed various internal architectures that support dynamic interactions between the DMN, FPN, and ATN (Avelar-Pereira et al 2017).…”

Midline frontal and occipito-temporal activity during error monitoring in dyadic motor interactions

“…Besides the suggested overlap between the neural systems responding to observed and executed actions and errors (Zubarev et al, 2018) studies have documented a differential contribution of brain areas to the observation of errors performed by others (Shane et al, 2008;Abreu et al, 2012;Somon et al, 2019;Ninomiya, et al, 2018;Somon et al, 2017). In the present study we explored the neural responses associated to coordinating one's own movements with those of a virtual partner who could perform unexpected changes in its motor behaviour.…”