Evaluating the Influence of Musical and Monetary Rewards on Decision Making through Computational Modelling.

A central question in behavioural neuroscience is how different rewards modulate learning. While the role of monetary rewards is well-studied in decision-making research, the influence of abstract rewards like music remains poorly understood. This study investigated the dissociable effects of these two reward types on decision making. Forty participants completed two decision-making tasks, each characterised by probabilistic associations between stimuli and rewards, with probabilities changing over time to reflect environmental volatility. In each task, choices were reinforced either by monetary outcomes (win/lose) or by the endings of musical melodies (consonant/dissonant). We applied the Hierarchical Gaussian Filter, a validated hierarchical Bayesian framework, to model learning under these two conditions. Bayesian statistics provided evidence for similar learning patterns across both reward types, suggesting individuals' similar adaptability. However, within the musical task, individual preferences for consonance over dissonance explained some aspects of learning. Specifically, correlation analyses indicated that participants more tolerant of dissonance behaved more stochastically in their belief-to-response mappings and were less likely to choose the response associated with the current prediction for a consonant ending, driven by higher volatility estimates. By contrast, participants averse to dissonance showed increased tonic volatility, leading to larger updates in reward tendency beliefs.

Anterior cingulate and medial prefrontal cortex oscillations underlie learning alterations in trait anxiety in humans.

Anxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by suppressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.

Modulation of Motor Vigor by Expectation of Reward Probability Trial-by-Trial Is Preserved in Healthy Ageing and Parkinson's Disease Patients.

Motor improvements, such as faster movement times or increased velocity, have been associated with reward magnitude in deterministic contexts. Yet whether individual inferences on reward probability influence motor vigor dynamically remains undetermined. We investigated how dynamically inferring volatile action-reward contingencies modulated motor performance trial-by-trial. We conducted three studies that coupled a reversal learning paradigm with a motor sequence task and used a validated hierarchical Bayesian model to fit trial-by-trial data. In Study 1, we tested healthy younger [HYA; 37 (24 females)] and older adults [HOA; 37 (17 females)], and medicated Parkinson's disease (PD) patients [20 (7 females)]. We showed that stronger predictions about the tendency of the action-reward contingency led to faster performance tempo, commensurate with movement time, on a trial-by-trial basis without robustly modulating reaction time (RT). Using Bayesian linear mixed models, we demonstrated a similar invigoration effect on performance tempo in HYA, HOA, and PD, despite HOA and PD being slower than HYA. In Study 2 [HYA, 39 (29 females)], we additionally showed that retrospective subjective inference about credit assignment did not contribute to differences in motor vigor effects. Last, Study 3 [HYA, 33 (27 females)] revealed that explicit beliefs about the reward tendency (confidence ratings) modulated performance tempo trial-by-trial. Our study is the first to reveal that the dynamic updating of beliefs about volatile action-reward contingencies positively biases motor performance through faster tempo. We also provide robust evidence for a preserved sensitivity of motor vigor to inferences about the action-reward mapping in aging and medicated PD.SIGNIFICANCE STATEMENT Navigating a world rich in uncertainty relies on updating beliefs about the probability that our actions lead to reward. Here, we investigated how inferring the action-reward contingencies in a volatile environment modulated motor vigor trial-by-trial in healthy younger and older adults, and in Parkinson's disease (PD) patients on medication. We found an association between trial-by-trial predictions about the tendency of the action-reward contingency and performance tempo, with stronger expectations speeding the movement. We additionally provided evidence for a similar sensitivity of performance tempo to the strength of these predictions in all groups. Thus, dynamic beliefs about the changing relationship between actions and their outcome enhanced motor vigor. This positive bias was not compromised by age or Parkinson's disease.

Identification of spatial patterns with maximum association between power of resting state neural oscillations and trait anxiety.

Anxiety affects approximately 5-10% of the adult population worldwide, placing a large burden on the health systems. Despite its omnipresence and impact on mental and physical health, most of the individuals affected by anxiety do not receive appropriate treatment. Current research in the field of psychiatry emphasizes the need to identify and validate biological markers relevant to this condition. Neurophysiological preclinical studies are a prominent approach to determine brain rhythms that can be reliable markers of key features of anxiety. However, while neuroimaging research consistently implicated prefrontal cortex and subcortical structures, such as amygdala and hippocampus, in anxiety, there is still a lack of consensus on the underlying neurophysiological processes contributing to this condition. Methods allowing non-invasive recording and assessment of cortical processing may provide an opportunity to help identify anxiety signatures that could be used as intervention targets. In this study, we apply Source-Power Comodulation (SPoC) to electroencephalography (EEG) recordings in a sample of participants with different levels of trait anxiety. SPoC was developed to find spatial filters and patterns whose power comodulates with an external variable in individual participants. The obtained patterns can be interpreted neurophysiologically. Here, we extend the use of SPoC to a multi-subject setting and test its validity using simulated data with a realistic head model. Next, we apply our SPoC framework to resting state EEG of 43 human participants for whom trait anxiety scores were available. SPoC inter-subject analysis of narrow frequency band data reveals neurophysiologically meaningful spatial patterns in the theta band (4-7 Hz) that are negatively correlated with anxiety. The outcome is specific to the theta band and not observed in the alpha (8-12 Hz) or beta (13-30 Hz) frequency range. The theta-band spatial pattern is primarily localised to the superior frontal gyrus. We discuss the relevance of our spatial pattern results for the search of biomarkers for anxiety and their application in neurofeedback studies.

Action Selection and Motor Decision Making: Insights from Transcranial Magnetic Stimulation.

In everyday life, goal-oriented motor behaviour relies on the estimation of the rewards/costs associated with alternative actions and on the appropriate selection of movements. Motor decision making is defined as the process by which a motor plan is chosen among a set of competing actions based on the expected value. In the present literature review we discuss evidence from transcranial magnetic stimulation (TMS) studies of motor control. We focus primarily on studies of action selection for instructed movements and motor decision making. In the first section, we delve into the usefulness of various TMS paradigms to characterise the contribution of motor areas and distributed brain networks to cued action selection. Then, we address the influence of motivational information (e.g., reward and biomechanical cost) in guiding action choices based on TMS findings. Finally, we conclude that TMS represents a powerful tool for elucidating the neurophysiological mechanisms underlying action choices in humans.

Introspection confidence predicts EEG decoding of self-generated thoughts and meta-awareness.

The neurophysiological bases of mind wandering (MW)-an experiential state wherein attention is disengaged from the external environment in favour of internal thoughts-and state meta-awareness are poorly understood. In parallel, the relationship between introspection confidence in experiential state judgements and neural representations remains unclear. Here, we recorded EEG while participants completed a listening task within which they made experiential state judgements and rated their confidence. Alpha power was reliably greater during MW episodes, with unaware MW further associated with greater delta and theta power. Multivariate pattern classification analysis revealed that MW and meta-awareness can be decoded from the distribution of power in these three frequency bands. Critically, we show that individual decoding accuracies positively correlate with introspection confidence. Our results reaffirm the role of alpha oscillations in MW, implicate lower frequencies in meta-awareness, and are consistent with the proposal that introspection confidence indexes neurophysiological discriminability of representational states.

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning.

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance) encoded in gamma oscillations (>30 Hz) and associated with the suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.

Multivariate patterns and long-range temporal correlations of alpha oscillations are associated with flexible manipulation of visual working memory representations.

The ability to flexibly manipulate memory representations is embedded in visual working memory (VWM) and can be tested using paradigms with retrospective cues. Although valid retrospective cues often facilitate memory recall, invalid ones may or may not result in performance costs. We investigated individual differences in utilising retrospective cues and evaluated how these individual differences are associated with brain oscillatory activity at rest. At the behavioural level, we operationalised flexibility as the ability to make effective use of retrospective cues or disregard them if required. At the neural level, we tested whether individual differences in such flexibility were associated with properties of resting-state alpha oscillatory activity (8-12 Hz). To capture distinct aspects of these brain oscillations, we evaluated their power spectral density and temporal dynamics using long-range temporal correlations (LRTCs). In addition, we performed multivariate patterns analysis (MVPA) to classify individuals' level of behavioural flexibility based on these neural measures. We observed that alpha power alone (magnitude) at rest was not associated with flexibility. However, we found that the participants' ability to manipulate VWM representations was correlated with alpha LRTC and could be decoded using MVPA on patterns of alpha power. Our findings suggest that alpha LRTC and multivariate patterns of alpha power at rest may underlie some of the individual differences in using retrospective cues in working memory tasks.

Resting-State Theta Oscillations and Reward Sensitivity in Risk Taking.

Females demonstrate greater risk aversion than males on a variety of tasks, but the underlying neurobiological basis is still unclear. We studied how theta (4-7 Hz) oscillations at rest related to three different measures of risk taking. Thirty-five participants (15 females) completed the Bomb Risk Elicitation Task (BRET), which allowed us to measure risk taking during an economic game. The Domain-Specific Risk-Taking Scale (DOSPERT) was used to measure self-assessed risk attitudes as well as reward and punishment sensitivities. In addition, the Barratt Impulsiveness Scale (BIS11) was included to quantify impulsiveness. To obtain measures of frontal theta asymmetry and frontal theta power, we used magnetoencephalography (MEG) acquired prior to task completion, while participants were at rest. Frontal theta asymmetry correlated with average risk taking during the game but only in the female sample. By contrast, frontal theta power correlated with risk taking as well as with measures of reward and punishment sensitivity in the joint sample. Importantly, we showed that reward sensitivity mediated a correlation between risk taking and the power of theta oscillations localized to the anterior cingulate cortex. In addition, we observed significant sex differences in source- and sensor-space theta power, risk taking during the game, and reward sensitivity. Our findings suggest that sensitivity to rewards, associated with resting-state theta oscillations in the anterior cingulate cortex, is a trait that potentially contributes to sex differences in risk taking.

Alterations in the amplitude and burst rate of beta oscillations impair reward-dependent motor learning in anxiety.

Anxiety results in sub-optimal motor learning, but the precise mechanisms through which this effect occurs remain unknown. Using a motor sequence learning paradigm with separate phases for initial exploration and reward-based learning, we show that anxiety states in humans impair learning by attenuating the update of reward estimates. Further, when such estimates are perceived as unstable over time (volatility), anxiety constrains adaptive behavioral changes. Neurally, anxiety during initial exploration increased the amplitude and the rate of long bursts of sensorimotor and prefrontal beta oscillations (13-30 Hz). These changes extended to the subsequent learning phase, where phasic increases in beta power and burst rate following reward feedback were linked to smaller updates in reward estimates, with a higher anxiety-related increase explaining the attenuated belief updating. These data suggest that state anxiety alters the dynamics of beta oscillations during reward processing, thereby impairing proper updating of motor predictions when learning in unstable environments.

Feeling anxious can hinder how well someone performs a task, a phenomenon that is sometimes called "choking under pressure". Anxiety may also impair a person's ability to learn a new manual task, like juggling or playing the piano; however, it remains unclear exactly how this happens. People learn manual tasks more quickly if they can practice first, and the more someone varies their movements during these trial runs, the faster they learn afterwards. Yet, anxiety can affect movement; for example, anxious people often make repetitive motions like hand-wringing or fidgeting. There is also evidence that very anxious people may learn less from the outcomes of their actions. To understand how anxiety may affect the learning of manual tasks, Sporn et al designed experiments where people learned to play a short sequence of notes on a piano. The main experiment involved 60 participants and was split over two phases. In the first 'exploration' phase, participants had to play the piano sequence using any timing they liked and were encouraged to explore different rhythms. In the second 'learning' phase, participants were rewarded with a higher score the closer they got to playing the notes with a certain rhythm, without being told that this was their specific goal. To see how anxiety affected performance, the participants were split into three groups. One group were told in the initial exploration phase that they would give a public talk after they completed the piano task, which reliably made them more anxious. A second group were told about the anxiety-inducing public speaking only during the learning phase; while a third group ­ the controls ­ were not aware of any public speaking task. People in the second group could learn the rhythm as well as the controls. Participants who were made anxious during the exploration phase, however, scored fewer points and were less likely to learn the piano sequence in the second phase. They also varied their movements less in the first phase. As a follow-up, Sporn et al. repeated the experiment with 26 people but without the initial exploration phase. This time the anxious participants were less able to learn the piano sequence and scored fewer points. This suggests that the initial exploration in the previous experiment had enabled later anxious participants to succeed in the learning phase despite being anxious. Finally, Sporn et al. also used a technique called electroencephalography (or EEG for short) to record brain activity and observed differences in participants with and without anxiety, particularly when they received their scores. The EEG signals showed that anxiety altered rhythmic patterns of brain activity called "sensorimotor beta oscillations", which are known to be involved in both movement and learning.

Beta Oscillations in Working Memory, Executive Control of Movement and Thought, and Sensorimotor Function.

Beta oscillations (∼13 to 30 Hz) have been observed during many perceptual, cognitive, and motor processes in a plethora of brain recording studies. Although the function of beta oscillations (hereafter "beta" for short) is unlikely to be explained by any single monolithic description, we here discuss several convergent findings. In prefrontal cortex (PFC), increased beta appears at the end of a trial when working memory information needs to be erased. A similar "clear-out" function might apply during the stopping of action and the stopping of long-term memory retrieval (stopping thoughts), where increased prefrontal beta is also observed. A different apparent role for beta in PFC occurs during the delay period of working memory tasks: it might serve to maintain the current contents and/or to prevent interference from distraction. We confront the challenge of relating these observations to the large literature on beta recorded from sensorimotor cortex. Potentially, the clear-out of working memory in PFC has its counterpart in the postmovement clear-out of the motor plan in sensorimotor cortex. However, recent studies support alternative interpretations. In addition, we flag emerging research on different frequencies of beta and the relationship between beta and single-neuron spiking. We also discuss where beta might be generated: basal ganglia, cortex, or both. We end by considering the clinical implications for adaptive deep-brain stimulation.

Disruption of Boundary Encoding During Sensorimotor Sequence Learning: An MEG Study.

Music performance relies on the ability to learn and execute actions and their associated sounds. The process of learning these auditory-motor contingencies depends on the proper encoding of the serial order of the actions and sounds. Among the different serial positions of a behavioral sequence, the first and last (boundary) elements are particularly relevant. Animal and patient studies have demonstrated a specific neural representation for boundary elements in prefrontal cortical regions and in the basal ganglia, highlighting the relevance of their proper encoding. The neural mechanisms underlying the encoding of sequence boundaries in the general human population remain, however, largely unknown. In this study, we examined how alterations of auditory feedback, introduced at different ordinal positions (boundary or within-sequence element), affect the neural and behavioral responses during sensorimotor sequence learning. Analysing the neuromagnetic signals from 20 participants while they performed short piano sequences under the occasional effect of altered feedback (AF), we found that at around 150-200 ms post-keystroke, the neural activities in the dorsolateral prefrontal cortex (DLPFC) and supplementary motor area (SMA) were dissociated for boundary and within-sequence elements. Furthermore, the behavioral data demonstrated that feedback alterations on boundaries led to greater performance costs, such as more errors in the subsequent keystrokes. These findings jointly support the idea that the proper encoding of boundaries is critical in acquiring sensorimotor sequences. They also provide evidence for the involvement of a distinct neural circuitry in humans including prefrontal and higher-order motor areas during the encoding of the different classes of serial order.

Cingulate and cerebellar beta oscillations are engaged in the acquisition of auditory-motor sequences.

Singing, music performance, and speech rely on the retrieval of complex sounds, which are generated by the corresponding actions and are organized into sequences. It is crucial in these forms of behavior that the serial organization (i.e., order) of both the actions and associated sounds be monitored and learned. To investigate the neural processes involved in the monitoring of serial order during the initial learning of sensorimotor sequences, we performed magnetoencephalographic recordings while participants explicitly learned short piano sequences under the effect of occasional alterations of auditory feedback (AAF). The main result was a prominent and selective modulation of beta (13-30 Hz) oscillations in cingulate and cerebellar regions during the processing of AAF that simulated serial order errors. Furthermore, the AAF-induced modulation of beta oscillations was associated with higher error rates, reflecting compensatory changes in sequence planning. This suggests that cingulate and cerebellar beta oscillations play a role in tracking serial order during initial sensorimotor learning and in updating the mapping of the sensorimotor representations. The findings support the notion that the modulation of beta oscillations is a candidate mechanism for the integration of sequential motor and auditory information during an early stage of skill acquisition in music performance. This has potential implications for singing and speech. Hum Brain Mapp 38:5161-5179, 2017. © 2017 Wiley Periodicals, Inc.

Brain networks modulated by subthalamic nucleus deep brain stimulation.

Deep brain stimulation of the subthalamic nucleus is an established treatment for the motor symptoms of Parkinson's disease. Given the frequent occurrence of stimulation-induced affective and cognitive adverse effects, a better understanding about the role of the subthalamic nucleus in non-motor functions is needed. The main goal of this study is to characterize anatomical circuits modulated by subthalamic deep brain stimulation, and infer about the inner organization of the nucleus in terms of motor and non-motor areas. Given its small size and anatomical intersubject variability, functional organization of the subthalamic nucleus is difficult to investigate in vivo with current methods. Here, we used local field potential recordings obtained from 10 patients with Parkinson's disease to identify a subthalamic area with an analogous electrophysiological signature, namely a predominant beta oscillatory activity. The spatial accuracy was improved by identifying a single contact per macroelectrode for its vicinity to the electrophysiological source of the beta oscillation. We then conducted whole brain probabilistic tractography seeding from the previously identified contacts, and further described connectivity modifications along the macroelectrode's main axis. The designated subthalamic 'beta' area projected predominantly to motor and premotor cortical regions additional to connections to limbic and associative areas. More ventral subthalamic areas showed predominant connectivity to medial temporal regions including amygdala and hippocampus. We interpret our findings as evidence for the convergence of different functional circuits within subthalamic nucleus' portions deemed to be appropriate as deep brain stimulation target to treat motor symptoms in Parkinson's disease. Potential clinical implications of our study are illustrated by an index case where deep brain stimulation of estimated predominant non-motor subthalamic nucleus induced hypomanic behaviour.

Long-range correlation properties in timing of skilled piano performance: the influence of auditory feedback and deep brain stimulation.

Unintentional timing deviations during musical performance can be conceived of as timing errors. However, recent research on humanizing computer-generated music has demonstrated that timing fluctuations that exhibit long-range temporal correlations (LRTC) are preferred by human listeners. This preference can be accounted for by the ubiquitous presence of LRTC in human tapping and rhythmic performances. Interestingly, the manifestation of LRTC in tapping behavior seems to be driven in a subject-specific manner by the LRTC properties of resting-state background cortical oscillatory activity. In this framework, the current study aimed to investigate whether propagation of timing deviations during the skilled, memorized piano performance (without metronome) of 17 professional pianists exhibits LRTC and whether the structure of the correlations is influenced by the presence or absence of auditory feedback. As an additional goal, we set out to investigate the influence of altering the dynamics along the cortico-basal-ganglia-thalamo-cortical network via deep brain stimulation (DBS) on the LRTC properties of musical performance. Specifically, we investigated temporal deviations during the skilled piano performance of a non-professional pianist who was treated with subthalamic-deep brain stimulation (STN-DBS) due to severe Parkinson's disease, with predominant tremor affecting his right upper extremity. In the tremor-affected right hand, the timing fluctuations of the performance exhibited random correlations with DBS OFF. By contrast, DBS restored long-range dependency in the temporal fluctuations, corresponding with the general motor improvement on DBS. Overall, the present investigations demonstrate the presence of LRTC in skilled piano performances, indicating that unintentional temporal deviations are correlated over a wide range of time scales. This phenomenon is stable after removal of the auditory feedback, but is altered by STN-DBS, which suggests that cortico-basal ganglia-thalamocortical circuits play a role in the modulation of the serial correlations of timing fluctuations exhibited in skilled musical performance.

Encoding of sequence boundaries in the subthalamic nucleus of patients with Parkinson's disease.

Sequential behaviour is widespread not only in humans but also in animals, ranging in different degrees of complexity from locomotion to birdsong or music performance. The capacity to learn new motor sequences relies on the integrity of basal ganglia-cortical loops. In Parkinson's disease the execution of habitual action sequences as well as the acquisition of novel sequences is impaired partly due to a deficiency in being able to generate internal cues to trigger movement sequences. In addition, patients suffering from Parkinson's disease have difficulty initiating or terminating a self-paced sequence of actions. Direct recordings from the basal ganglia in these patients show an increased level of beta (14-30 Hz) band oscillatory activity associated with impairment in movement initiation. In this framework, the current study aims to evaluate in patients with Parkinson's disease the neuronal activity in the subthalamic nucleus related to the encoding of sequence boundaries during the explicit learning of sensorimotor sequences. We recorded local field potential activity from the subthalamic nucleus of 12 patients who underwent deep brain stimulation for the treatment of advanced Parkinson's disease, while the patients in their usual medicated state practiced sequences of finger movements on a digital piano with corresponding auditory feedback. Our results demonstrate that variability in performance during an early phase of sequence acquisition correlates across patients with changes in the pattern of subthalamic beta-band oscillations; specifically, an anticipatory suppression of beta-band activity at sequence boundaries is linked to better performance. By contrast, a more compromised performance is related to attenuation of beta-band activity before within-sequence elements. Moreover, multivariate pattern classification analysis reveals that differential information about boundaries and within-sequence elements can be decoded at least 100 ms before the keystroke from the amplitude of oscillations of subthalamic nucleus activity across different frequency bands, not just from the beta-band. Additional analysis was performed to assess the strength of how much the putative signal encoding class of ordinal position (boundaries, within-sequence elements) is reflected in each frequency band. This analysis demonstrates that suppression of power in the beta-band contains the most class-related information, whereas enhancement of gamma band (31-100 Hz) activity is the second main contributor to the encoding. Our findings support the hypothesis that subthalamic nucleus-mediated gating of salient boundary elements during sequence encoding may be a prerequisite for the adequate acquisition of action sequences and the transition to habitual behaviour.

Error signals in the subthalamic nucleus are related to post-error slowing in patients with Parkinson's disease.

Error monitoring is essential for optimizing motor behavior. It has been linked to the medial frontal cortex, in particular to the anterior midcingulate cortex (aMCC). The aMCC subserves its performance-monitoring function in interaction with the basal ganglia (BG) circuits, as has been demonstrated in patients suffering from BG lesions or from Parkinson's disease (PD). The subthalamic nucleus (STN) has been assumed an integrative structure for emotional, cognitive and motor processing. Error-related behavioral adaptation such as post-error slowing has been linked to motor inhibition involving activation of an inhibitory network including the STN. However, direct involvement of the STN in error monitoring and post-error behavioral adjustment has not yet been demonstrated. Here, we used simultaneous scalp electroencephalogram (EEG) and local field potential (LFP) recordings from the BG in 17 patients undergoing deep brain stimulation (DBS) for PD to investigate error-related evoked activity in the human STN, its relation to post-error behavioral adjustment and the influence of dopamine during the performance of a speeded flanker task. We found an error-related positive deflection (STN-Pe) in the STN-LFP 260-450 msec after error commission. Importantly, the STN-Pe amplitude was larger in trials with post-error slowing compared to trials with post-error speeding. There was no overall effect of dopamine on error processing. Subgroup analysis revealed a higher error rate (ER) in younger patients with earlier disease onset ON medication compared to OFF medication (and vice versa in the older patient group), which was associated with modulatory effects of the early cortical error-related negativity (ERN) and late STN-Pe. The late error-related STN-Pe that is associated with post-error reaction time (RT) adjustments supports the notion that post-error slowing is implemented by motor inhibition involving the STN. Further, the modulation of behavioral performance by dopaminergic therapy depending on patients' age may suggest a dopamine overdose effect in patients with earlier onset of PD.

Involvement of human internal globus pallidus in the early modulation of cortical error-related activity.

The detection and assessment of errors are a prerequisite to adapt behavior and improve future performance. Error monitoring is afforded by the interplay between cortical and subcortical neural systems. Ample evidence has pointed to a specific cortical error-related evoked potential, the error-related negativity (ERN), during the detection and evaluation of response errors. Recent models of reinforcement learning implicate the basal ganglia (BG) in early error detection following the learning of stimulus-response associations and in the modulation of the cortical ERN. To investigate the influence of the human BG motor output activity on the cortical ERN during response errors, we recorded local field potentials from the sensorimotor area of the internal globus pallidus and scalp electroencephalogram representing activity from the posterior medial frontal cortex in patients with idiopathic dystonia (hands not affected) during a flanker task. In error trials, a specific pallidal error-related potential arose 60 ms prior to the cortical ERN. The error-related changes in pallidal activity-characterized by theta oscillations-were predictive of the cortical error-related activity as assessed by Granger causality analysis. Our findings show an early modulation of error-related activity in the human pallidum, suggesting that pallidal output influences the cortex at an early stage of error detection.

Beta-band amplitude oscillations in the human internal globus pallidus support the encoding of sequence boundaries during initial sensorimotor sequence learning.

Sequential behavior characterizes both simple everyday tasks, such as getting dressed, and complex skills, such as music performance. The basal ganglia (BG) play an important role in the learning of motor sequences. To study the contribution of the human BG to the initial encoding of sequence boundaries, we recorded local field potentials in the sensorimotor area of the internal globus pallidus (GPi) during the early acquisition of sensorimotor sequences in patients undergoing deep brain stimulation for dystonia. We demonstrated an anticipatory modulation of pallidal beta-band neuronal oscillations that was specific to sequence boundaries, as compared to within-sequence elements, and independent of both the movement parameters and the initiation/termination of ongoing movement. The modulation at sequence boundaries emerged with training, in parallel with skill learning, and correlated with the degree of long-range temporal correlations (LRTC) in the dynamics of ongoing beta-band amplitude oscillations. The implication is that LRTC of beta-band oscillations in the sensorimotor GPi might facilitate the emergence of beta power modulations by the sequence boundaries in parallel with sequence learning. Taken together, the results reveal the oscillatory mechanisms in the human BG that contribute at an initial learning phase to the hierarchical organization of sequential behavior as reflected in the formation of boundary-delimited representations of action sequences.