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.

Highlights

  • Neural responses to negative or unexpected action outcomes have been the main target of research seeking to understand neural mechanisms of adaptive behavior in humans (Luft, 2014; Walsh & Anderson, 2012; Weinberg, Dieterich, & Riesel, 2014)

  • 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 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

Read more

Summary

| INTRODUCTION

Neural responses to negative or unexpected action outcomes have been the main target of research seeking to understand neural mechanisms of adaptive behavior in humans (Luft, 2014; Walsh & Anderson, 2012; Weinberg, Dieterich, & Riesel, 2014). Patient studies demonstrate that ERN and FRN may be affected differently in a number of neuropsychiatric conditions including obsessive– compulsive disorder (Gründler et al, 2009), trait anxiety (Gu et al, 2010), major depression (Proudfit, Bress, Foti, Kujawa, & Klein, 2015; Weinberg et al, 2012) and schizophrenia (Morris et al, 2011) These discrepancies led researchers to suggest that, despite the apparent similarities, distinct neuronal populations may be involved in producing motor- and feedback-related error responses (Müller, Möller, Rodriguez-Fornells, & Münte, 2005). The across-condition generalization method allowed us to probe how the processing of valence and expectancy of the feedback contributes to the observed similarities

| Participants
| Experimental procedure
| RESULTS
| DISCUSSION
Findings
| CONCLUSIONS

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.