State anxiety biases estimates of uncertainty and impairs reward learning in volatile environments.

Clinical and subclinical (trait) anxiety impairs decision making and interferes with learning. Less understood are the effects of temporary anxious states on learning and decision making in healthy populations, and whether these can serve as a model for clinical anxiety. Here we test whether anxious states in healthy individuals elicit a pattern of aberrant behavioural, neural, and physiological responses comparable with those found in anxiety disorders-particularly when processing uncertainty in unstable environments. In our study, both a state anxious and a control group learned probabilistic stimulus-outcome mappings in a volatile task environment while we recorded their electrophysiological (EEG) signals. By using a hierarchical Bayesian model of inference and learning, we assessed the effect of state anxiety on Bayesian belief updating with a focus on uncertainty estimates. State anxiety was associated with an underestimation of environmental uncertainty, and informational uncertainty about the reward tendency. Anxious individuals' beliefs about reward contingencies were more precise (had smaller uncertainty) and thus more resistant to updating, ultimately leading to impaired reward-based learning. State anxiety was also associated with greater uncertainty about volatility. We interpret this pattern as evidence that state anxious individuals are less tolerant to informational uncertainty about the contingencies governing their environment and more willing to be uncertain about the level of stability of the world itself. Further, we tracked the neural representation of belief update signals in the trial-by-trial EEG amplitudes. In control participants, lower-level precision-weighted prediction errors (pwPEs) about reward tendencies were represented in the ERP signals across central and parietal electrodes peaking at 496 ms, overlapping with the late P300 in classical ERP analysis. The state anxiety group did not exhibit a significant representation of low-level pwPEs, and there were no significant differences between the groups. Smaller variance in low-level pwPE about reward tendencies in state anxiety could partially account for the null results. Expanding previous computational work on trait anxiety, our findings establish that temporary anxious states in healthy individuals impair reward-based learning in volatile environments, primarily through changes in uncertainty estimates, which play a central role in current Bayesian accounts of perceptual inference and learning.

Cardiac afferent activity modulates early neural signature of error detection during skilled performance.

Behavioral adaptations during performance rely on predicting and evaluating the consequences of our actions through action monitoring. Previous studies revealed that proprioceptive and exteroceptive signals contribute to error-monitoring processes, which are implemented in the posterior medial frontal cortex. Interestingly, errors also trigger changes in autonomic nervous system activity such as pupil dilation or heartbeat deceleration. Yet, the contribution of implicit interoceptive signals of bodily states to error-monitoring during ongoing performance has been overlooked. This study investigated whether cardiovascular interoceptive signals influence the neural correlates of error processing during performance, with an emphasis on the early stages of error processing. We recorded musicians' electroencephalography and electrocardiogram signals during the performance of highly-trained music pieces. Previous event-related potential (ERP) studies revealed that pitch errors during skilled musical performance are preceded by an error detection signal, the pre-error-negativity (preERN), and followed by a later error positivity (PE). In this study, by combining ERP, source localization and multivariate pattern classification analysis, we found that the error-minus-correct ERP waveform had an enhanced amplitude within 40-100 ms following errors in the systolic period of the cardiac cycle. This component could be decoded from single-trials, was dissociated from the preERN and PE, and stemmed from the inferior parietal cortex, which is a region implicated in cardiac autonomic regulation. In addition, the phase of the cardiac cycle influenced behavioral alterations resulting from errors, with a smaller post-error slowing and less perturbed velocity in keystrokes following pitch errors in the systole relative to the diastole phase of the cardiac cycle. Lastly, changes in the heart rate anticipated the upcoming occurrence of errors. This study provides the first evidence of preconscious visceral information modulating neural and behavioral responses related to early error monitoring during skilled performance.

Enhanced low-frequency oscillatory activity of the subthalamic nucleus in a patient with dystonia.

BACKGROUND: Local field potentials were recorded from the subthalamic nucleus (STN) in a patient with dystonia to further elucidate disease-specific aspects of basal ganglia oscillatory activity. METHODS: STN local field potentials and electromyograms (EMGs) from dystonic muscles were recorded to provide an estimate of the power spectra and coherence between the STN activity and EMG. RESULTS: STN power spectra revealed a distinct peak at approximately 7 Hz in our patient. This finding is similar to the pallidal activity seen in dystonic patients but clearly different from the subthalamic beta activity of patients with Parkinson's disease. Significant coherence between STN activity and EMG was present in the 4- to 12-Hz band in this patient. CONCLUSIONS: Dystonia is associated with pathological activity in the theta range present throughout the cortical-basal ganglia network. This activity differs from that in Parkinson's disease, suggesting that different movement disorders may involve distinct oscillatory circuit disturbances. © 2012 Movement Disorder Society.

EEG oscillatory patterns are associated with error prediction during music performance and are altered in musician's dystonia.

Skilled performance requires the ability to monitor ongoing behavior, detect errors in advance and modify the performance accordingly. The acquisition of fast predictive mechanisms might be possible due to the extensive training characterizing expertise performance. Recent EEG studies on piano performance reported a negative event-related potential (ERP) triggered in the ACC 70 ms before performance errors (pitch errors due to incorrect keypress). This ERP component, termed pre-error related negativity (pre-ERN), was assumed to reflect processes of error detection in advance. However, some questions remained to be addressed: (i) Does the electrophysiological marker prior to errors reflect an error signal itself or is it related instead to the implementation of control mechanisms? (ii) Does the posterior frontomedial cortex (pFMC, including ACC) interact with other brain regions to implement control adjustments following motor prediction of an upcoming error? (iii) Can we gain insight into the electrophysiological correlates of error prediction and control by assessing the local neuronal synchronization and phase interaction among neuronal populations? (iv) Finally, are error detection and control mechanisms defective in pianists with musician's dystonia (MD), a focal task-specific dystonia resulting from dysfunction of the basal ganglia-thalamic-frontal circuits? Consequently, we investigated the EEG oscillatory and phase synchronization correlates of error detection and control during piano performances in healthy pianists and in a group of pianists with MD. In healthy pianists, the main outcomes were increased pre-error theta and beta band oscillations over the pFMC and 13-15 Hz phase synchronization, between the pFMC and the right lateral prefrontal cortex, which predicted corrective mechanisms. In MD patients, the pattern of phase synchronization appeared in a different frequency band (6-8 Hz) and correlated with the severity of the disorder. The present findings shed new light on the neural mechanisms, which might implement motor prediction by means of forward control processes, as they function in healthy pianists and in their altered form in patients with MD.

Unsupervised statistical learning underpins computational, behavioural, and neural manifestations of musical expectation.

The ability to anticipate forthcoming events has clear evolutionary advantages, and predictive successes or failures often entail significant psychological and physiological consequences. In music perception, the confirmation and violation of expectations are critical to the communication of emotion and aesthetic effects of a composition. Neuroscientific research on musical expectations has focused on harmony. Although harmony is important in Western tonal styles, other musical traditions, emphasizing pitch and melody, have been rather neglected. In this study, we investigated melodic pitch expectations elicited by ecologically valid musical stimuli by drawing together computational, behavioural, and electrophysiological evidence. Unlike rule-based models, our computational model acquires knowledge through unsupervised statistical learning of sequential structure in music and uses this knowledge to estimate the conditional probability (and information content) of musical notes. Unlike previous behavioural paradigms that interrupt a stimulus, we devised a new paradigm for studying auditory expectation without compromising ecological validity. A strong negative correlation was found between the probability of notes predicted by our model and the subjectively perceived degree of expectedness. Our electrophysiological results showed that low-probability notes, as compared to high-probability notes, elicited a larger (i) negative ERP component at a late time period (400-450 ms), (ii) beta band (14-30 Hz) oscillation over the parietal lobe, and (iii) long-range phase synchronization between multiple brain regions. Altogether, the study demonstrated that statistical learning produces information-theoretic descriptions of musical notes that are proportional to their perceived expectedness and are associated with characteristic patterns of neural activity.

Detecting wrong notes in advance: neuronal correlates of error monitoring in pianists.

Music performance is an extremely rapid process with low incidence of errors even at the fast rates of production required. This is possible only due to the fast functioning of the self-monitoring system. Surprisingly, no specific data about error monitoring have been published in the music domain. Consequently, the present study investigated the electrophysiological correlates of executive control mechanisms, in particular error detection, during piano performance. Our target was to extend the previous research efforts on understanding of the human action-monitoring system by selecting a highly skilled multimodal task. Pianists had to retrieve memorized music pieces at a fast tempo in the presence or absence of auditory feedback. Our main interest was to study the interplay between auditory and sensorimotor information in the processes triggered by an erroneous action, considering only wrong pitches as errors. We found that around 70 ms prior to errors a negative component is elicited in the event-related potentials and is generated by the anterior cingulate cortex. Interestingly, this component was independent of the auditory feedback. However, the auditory information did modulate the processing of the errors after their execution, as reflected in a larger error positivity (Pe). Our data are interpreted within the context of feedforward models and the auditory-motor coupling.

Defective inhibition and inter-regional phase synchronization in pianists with musician's dystonia: an EEG study.

Recent neurophysiological studies have associated focal-task specific dystonia (FTSD) with impaired inhibitory function. However, it remains unknown whether FTSD also affects the inhibition (INH) of long-term overlearned motor programs. Consequently, we investigated in a Go/NoGo paradigm the neural correlates associated with the activation (ACT) and inhibition of long-term overlearned motor memory traces in pianists with musician's dystonia (MD), a form of FTSD, during a relevant motor task under constraint timing conditions with multichannel EEG. In NoGo trials, the movement related cortical potentials showed a positive shift after the NoGo signal related to inhibition and was significantly smaller over sensorimotor areas in musicians with MD. Further, we observed an increase at 850-900 ms in the power of beta oscillations which was significantly weaker for the patient group. The role of the inter-electrode phase coupling in the sensorimotor integration of inhibitory processes turned out to be the most relevant physiological marker: the global phase synchronization during INH exhibited an increase between 230 and 330 ms and 7-8 Hz, increase which was significantly smaller for pianists with MD. This effect was due to a weaker phase synchronization between the supplementary motor cortex and left premotor and sensorimotor electrodes in patients. Thus, our findings support the hypothesis of a deficient phase coupling between the neuronal assemblies required to inhibit motor memory traces in patients with MD. EMG recorded from the right flexor pollicis longus muscle confirmed that patients with MD had a disrupted INH in NoGo trials.

Decrease in early right alpha band phase synchronization and late gamma band oscillations in processing syntax in music.

The present study investigated the neural correlates associated with the processing of music-syntactical irregularities as compared with regular syntactic structures in music. Previous studies reported an early ( approximately 200 ms) right anterior negative component (ERAN) by traditional event-related-potential analysis during music-syntactical irregularities, yet little is known about the underlying oscillatory and synchronization properties of brain responses which are supposed to play a crucial role in general cognition including music perception. First we showed that the ERAN was primarily represented by low frequency (<8 Hz) brain oscillations. Further, we found that music-syntactical irregularities as compared with music-syntactical regularities, were associated with (i) an early decrease in the alpha band (9-10 Hz) phase synchronization between right fronto-central and left temporal brain regions, and (ii) a late ( approximately 500 ms) decrease in gamma band (38-50 Hz) oscillations over fronto-central brain regions. These results indicate a weaker degree of long-range integration when the musical expectancy is violated. In summary, our results reveal neural mechanisms of music-syntactic processing that operate at different levels of cortical integration, ranging from early decrease in long-range alpha phase synchronization to late local gamma oscillations.