Abstract
The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes. Axiomatic to these computations are salience and valence prediction error signals, which alert the brain to the occurrence and value of unexpected events. Despite the theoretical assertion of these prediction error signals, it is unknown whether and how brain mechanisms underlying their computations support error processing during skilled motor behavior. Here we demonstrate, with functional magnetic resonance imaging, that internal detection, i.e., without externally-provided feedback, of self-generated movement errors evokes instantaneous activity increases within the salience network and delayed lingering decreases within the nucleus accumbens – a key structure in the reward valuation pathway. A widespread suppression within the sensorimotor network was also observed. Our findings suggest that neural computations of salience and valence prediction errors during skilled motor behaviors operate on different time-scales and, therefore, may contribute differentially to immediate and longer-term adaptive processes.
Highlights
The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes
We aimed to elucidate (1) whether error processing during skilled motor performance is associated with changes in brain regions implemented in computations of salience and valence prediction error signals (PES), and if so, (2) how these changes evolve throughout different phases of error processing
In real-life situations, errors during ongoing skilled motor performance are generally detected immediately and corrected without any externally introduced feedback. Such ability is presumably mediated via highly efficient brain mechanisms dedicated to performance monitoring and prediction error signaling
Summary
The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes. An action error is known to occur when the internal prediction about the consequences of an intended action do not match the actual outcome of that action[1] Such prediction error signals (PES) provide detailed information about the motor command that caused the error, and induce more generic estimations indicating the degree of salience and/or valence of the mismatch. They are thought to initiate a cascade of automatic processes[2] that aim at rapid interruption of ongoing behavior, and/or shift of attention to the source of the unpredicted outcome[3] As such, these alerting signals are derived promptly with minimal neural computations and are typically deemed to be both nonspecific and unsigned, i.e., without indicating whether the actual outcome is better or worse than predicted[4]. The neural correlates of salience PES have been previously studied building on a seminal finding of error-related negativity—
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