Language statistical learning responds to reinforcement learning principles rooted in the striatum.

Statistical learning (SL) is the ability to extract regularities from the environment. In the domain of language, this ability is fundamental in the learning of words and structural rules. In lack of reliable online measures, statistical word and rule learning have been primarily investigated using offline (post-familiarization) tests, which gives limited insights into the dynamics of SL and its neural basis. Here, we capitalize on a novel task that tracks the online SL of simple syntactic structures combined with computational modeling to show that online SL responds to reinforcement learning principles rooted in striatal function. Specifically, we demonstrate-on 2 different cohorts-that a temporal difference model, which relies on prediction errors, accounts for participants' online learning behavior. We then show that the trial-by-trial development of predictions through learning strongly correlates with activity in both ventral and dorsal striatum. Our results thus provide a detailed mechanistic account of language-related SL and an explanation for the oft-cited implication of the striatum in SL tasks. This work, therefore, bridges the long-standing gap between language learning and reinforcement learning phenomena.

Anticipatory and consummatory neural correlates of monetary and music rewarding stimuli.

Most of the literature on the neural bases of human reward and punishment processing has used monetary gains and losses, but less is known about the neurophysiological mechanisms underlying the anticipation and consumption of other types of rewarding stimuli. In the present study, EEG was recorded from 19 participants who completed a modified version of the Monetary Incentive Delay (MID) task. During the task, cues providing information about potential future outcomes were presented to the participants. Then, they had to respond rapidly to a target stimulus to win money or listening to pleasant music, or to avoid losing money or listening to unpleasant music. Results revealed similar responses for monetary and music cues, with increased activity for cues indicating potential gains compared to losses. However, differences emerged in the outcome phase between money and music. Monetary outcomes showed an interaction between the type of the cue and the outcome in the Feedback Related Negativity and Fb-P3 ERPs and increased theta activity increased for negative feedbacks. In contrast, music outcomes showed significant interactions in the Fb-P3 and theta activities. These findings suggest similar neurophysiological mechanisms in processing cues for potential positive or negative outcomes in these two types of stimuli.

Neural predictors of cognitive-behavior therapy outcome in anxiety-related disorders: a meta-analysis of task-based fMRI studies.

BACKGROUND: Cognitive-behavior therapy (CBT) is a well-established first-line intervention for anxiety-related disorders, including specific phobia, social anxiety disorder, panic disorder/agoraphobia, generalized anxiety disorder, obsessive-compulsive disorder, and posttraumatic stress disorder. Several neural predictors of CBT outcome for anxiety-related disorders have been proposed, but previous results are inconsistent. METHODS: We conducted a systematic review and meta-analysis of task-based functional magnetic resonance imaging (fMRI) studies investigating whole-brain predictors of CBT outcome in anxiety-related disorders (17 studies, n = 442). RESULTS: Across different tasks, we observed that brain response in a network of regions involved in salience and interoception processing, encompassing fronto-insular (the right inferior frontal gyrus-anterior insular cortex) and fronto-limbic (the dorsomedial prefrontal cortex-dorsal anterior cingulate cortex) cortices was strongly associated with a positive CBT outcome. CONCLUSIONS: Our results suggest that there are robust neural predictors of CBT outcome in anxiety-related disorders that may eventually lead (probably in combination with other data) to develop personalized approaches for the treatment of these mental disorders.

Dopamine modulates the reward experiences elicited by music.

Understanding how the brain translates a structured sequence of sounds, such as music, into a pleasant and rewarding experience is a fascinating question which may be crucial to better understand the processing of abstract rewards in humans. Previous neuroimaging findings point to a challenging role of the dopaminergic system in music-evoked pleasure. However, there is a lack of direct evidence showing that dopamine function is causally related to the pleasure we experience from music. We addressed this problem through a double blind within-subject pharmacological design in which we directly manipulated dopaminergic synaptic availability while healthy participants (n = 27) were engaged in music listening. We orally administrated to each participant a dopamine precursor (levodopa), a dopamine antagonist (risperidone), and a placebo (lactose) in three different sessions. We demonstrate that levodopa and risperidone led to opposite effects in measures of musical pleasure and motivation: while the dopamine precursor levodopa, compared with placebo, increased the hedonic experience and music-related motivational responses, risperidone led to a reduction of both. This study shows a causal role of dopamine in musical pleasure and indicates that dopaminergic transmission might play different or additive roles than the ones postulated in affective processing so far, particularly in abstract cognitive activities.

Electrophysiological underpinnings of reward processing: Are we exploiting the full potential of EEG?

Understanding how the brain processes reward is an important and complex endeavor, which has involved the use of a range of complementary neuroimaging tools, including electroencephalography (EEG). EEG has been praised for its high temporal resolution but, because the signal recorded at the scalp is a mixture of brain activities, it is often considered to have poor spatial resolution. Besides, EEG data analysis has most often relied on event-related potentials (ERPs) which cancel out non-phase locked oscillatory activity, thus limiting the functional discriminative power of EEG attainable through spectral analyses. Because these three dimensions -temporal, spatial and spectral- have been unequally leveraged in reward studies, we argue that the full potential of EEG has not been exploited. To back up our claim, we first performed a systematic survey of EEG studies assessing reward processing. Specifically, we report on the nature of the cognitive processes investigated (i.e., reward anticipation or reward outcome processing) and the methods used to collect and process the EEG data (i.e., event-related potential, time-frequency or source analyses). A total of 359 studies involving healthy subjects and the delivery of monetary rewards were surveyed. We show that reward anticipation has been overlooked (88% of studies investigated reward outcome processing, while only 24% investigated reward anticipation), and that time-frequency and source analyses (respectively reported by 19% and 12% of the studies) have not been widely adopted by the field yet, with ERPs still being the dominant methodology (92% of the studies). We argue that this focus on feedback-related ERPs provides a biased perspective on reward processing, by ignoring reward anticipation processes as well as a large part of the information contained in the EEG signal. Finally, we illustrate with selected examples how addressing these issues could benefit the field, relying on approaches combining time-frequency analyses, blind source separation and source localization.

White Matter Microstructure Reflects Individual Differences in Music Reward Sensitivity.

People show considerable variability in the degree of pleasure they experience from music. These individual differences in music reward sensitivity are driven by variability in functional connectivity between the nucleus accumbens (NAcc), a key structure of the reward system, and the right superior temporal gyrus (STG). However, it is unknown whether a neuroanatomical basis exists for this variability. We used diffusion tensor imaging and probabilistic tractography to study the relationship between music reward sensitivity and white matter microstructure connecting these two regions via the orbitofrontal cortex (OFC) in 38 healthy human participants (24 females and 14 males). We found that right axial diffusivity (AD) in the STG-OFC connectivity inversely correlated with music reward sensitivity. Additionally, right mean diffusivity and left AD in the NAcc-OFC tract also showed an inverse correlation. Further, AD in this tract also correlated with previously acquired BOLD activity during music listening, but not for a control monetary reward task in the NAcc. Finally, we used mediation analysis to show that AD in the NAcc-OFC tract explains the influence of NAcc activation during a music task on music reward sensitivity. Overall, our results provide further support for the idea that the exchange of information among perceptual, integrative, and reward systems is important for musical pleasure, and that individual differences in the structure of the relevant anatomical connectivity influences the degree to which people are able to derive such pleasure.SIGNIFICANCE STATEMENT Music is one of the most important sources of pleasure for many people, but at the same time there are important individual differences in the sensitivity to musical reward. Previous studies have revealed the critical involvement of the functional connectivity between perceptual and subcortical brain areas in the enjoyment of music. However, it is unknown whether individual differences in music sensitivity might arise from variability in the structural connectivity among these areas. Here we show that structural connectivity between supratemporal and orbitofrontal cortices, and between orbitofrontal and nucleus accumbens, predict individual differences in sensibility to music reward. These results provide evidence for the critical involvement of the interaction between the subcortical reward system and higher-order cortical areas in music-induced pleasure.

Fronto-temporal theta phase-synchronization underlies music-evoked pleasantness.

Listening to pleasant music engages a complex distributed network including pivotal areas for auditory, reward, emotional and memory processing. On the other hand, frontal theta rhythms appear to be relevant in the process of giving value to music. However, it is not clear to which extent this oscillatory mechanism underlies the brain interactions that characterize music-evoked pleasantness and its related processes. The goal of the present experiment was to study brain synchronization in this oscillatory band as a function of music-evoked pleasantness. EEG was recorded from 25 healthy subjects while they were listening to music and rating the experienced degree of induced pleasantness. By using a multilevel Bayesian approach we found that phase synchronization in the theta band between right temporal and frontal signals increased with the degree of pleasure experienced by participants. These results show that slow fronto-temporal loops play a key role in music-evoked pleasantness.

Gossip information increases reward-related oscillatory activity.

Previous research has described the process by which the interaction between the firing in midbrain dopamine neurons and the hippocampus results in promoting memory for high-value motivational and rewarding events, both extrinsically and intrinsically driven (i.e. curiosity). Studies on social cognition and gossip have also revealed the activation of similar areas from the reward network. In this study we wanted to assess the electrophysiological correlates of the anticipation and processing of novel information (as an intrinsic cognitive reward) depending on the degree of elicited curiosity and the content of the information. 24 healthy volunteers participated in this EEG experiment. The task consisted of 150 questions and answers divided into three different conditions: trivia-like questions, personal-gossip information about celebrities and personal-neutral information about the same celebrities. Our main results from the ERPs and time-frequency analysis pinpointed main differences for gossip in comparison with personal-neutral and trivia-like conditions. Specifically, we found an increase in beta oscillatory activity in the outcome phase and a decrease of the same frequency band in the expectation phase. Larger amplitudes in P300 component were also found for gossip condition. Finally, gossip answers were the most remembered in a one-week memory test. The arousing value and saliency of gossip information, its rewarding effect evidenced by the increase of beta oscillatory power and the recruitment of areas from the brain reward network in previous fMRI studies, as well as its potential social value have been argued in order to explain its differential processing, encoding and recall.

Evidence for default mode network dysfunction in borderline personality disorder.

BACKGROUND: Although executive and other cognitive deficits have been found in patients with borderline personality disorder (BPD), whether these have brain functional correlates has been little studied. This study aimed to examine patterns of task-related activation and de-activation during the performance of a working memory task in patients with the disorder. METHODS: Sixty-seven DSM-IV BPD patients and 67 healthy controls underwent fMRI during the performance of the n-back task. Linear models were used to obtain maps of within-group activations and areas of differential activation between the groups. RESULTS: On corrected whole-brain analysis, there were no activation differences between the BPD patients and the healthy controls during the main 2-back v. baseline contrast, but reduced activation was seen in the precentral cortex bilaterally and the left inferior parietal cortex in the 2-back v. 1-back contrast. The patients showed failure of de-activation affecting the medial frontal cortex and the precuneus, plus in other areas. The changes did not appear to be attributable to previous history of depression, which was present in nearly half the sample. CONCLUSIONS: In this study, there was some, though limited, evidence for lateral frontal hypoactivation in BPD during the performance of an executive task. BPD also appears to be associated with failure of de-activation in key regions of the default mode network.

The contribution of striatal pseudo-reward prediction errors to value-based decision-making.

Most studies that have investigated the brain mechanisms underlying learning have focused on the ability to learn simple stimulus-response associations. However, in everyday life, outcomes are often obtained through complex behavioral patterns involving a series of actions. Parallel learning systems might be important to reduce the complexity of the learning problem in such scenarios, as proposed in the framework of hierarchical reinforcement learning (HRL). The key feature of HRL is the decomposition of complex sets of action into subgoals. These subgoals are associated with the computation of pseudo-reward prediction errors (PRPEs), which allow the reinforcement of actions that led to a subgoal before the final goal itself is achieved. Here we wanted to test the hypothesis that, despite not carrying any rewarding value per se, pseudo-rewards might generate a bias in choice behavior in the absence of any advantage. Second, we also hypothesized that this bias might be related to the strength of PRPE striatal representations. In order to test these ideas, we developed a novel decision-making paradigm to assess reward prediction errors (RPEs) and PRPEs in two studies (fMRI study: n = 20; behavioral study: n = 19). Our results show that the participants developed a preference for the most pseudo-rewarding option throughout the task, even though it did not lead to more monetary rewards. fMRI analyses revealed that this preference was predicted by individual differences in the relative striatal sensitivity to PRPEs vs RPEs. Together, our results indicate that pseudo-rewards generate learning signals in the striatum and subsequently bias choice behavior despite their lack of association with actual reward.

Brain oscillatory activity of skill and chance gamblers during a slot machine game.

Gambling behavior presents a broad variety of individual differences, with a continuum ranging from nongamblers to pathological gamblers. The reward network has been proposed to be critical in gambling behavior, but little is known about the behavioral and neural mechanisms underlying individual differences that depend on gambling preference. The main goals of the present study were to explore brain oscillatory responses to gambling outcomes in regular gamblers and to assess differences between strategic gamblers, nonstrategic gamblers, and nongamblers. In all, 54 healthy volunteers participated in the study. Electroencephalography was recorded while participants were playing a slot machine task that delivered win, near-miss, and full-miss outcomes. Behaviorally, regular gamblers selected a larger percentage of risky bets, especially when they could select the image to play. The time-frequency results showed larger oscillatory theta power increases to near-misses and increased beta power to win outcomes for regular gamblers, as compared to nongamblers. Moreover, theta oscillatory activity after wins was only increased in nonstrategic gamblers, revealing differences between the two groups of gamblers. The present results reveal differences between regular gamblers and nongamblers in both their behavioral and neural responses to gambling outcomes. Moreover, the results suggest that different brain oscillatory mechanisms might underlie the studied gambling profiles, which might have implications for both basic and clinical studies.

Neural correlates of specific musical anhedonia.

Although music is ubiquitous in human societies, there are some people for whom music holds no reward value despite normal perceptual ability and preserved reward-related responses in other domains. The study of these individuals with specific musical anhedonia may be crucial to understand better the neural correlates underlying musical reward. Previous neuroimaging studies have shown that musically induced pleasure may arise from the interaction between auditory cortical networks and mesolimbic reward networks. If such interaction is critical for music-induced pleasure to emerge, then those individuals who do not experience it should show alterations in the cortical-mesolimbic response. In the current study, we addressed this question using fMRI in three groups of 15 participants, each with different sensitivity to music reward. We demonstrate that the music anhedonic participants showed selective reduction of activity for music in the nucleus accumbens (NAcc), but normal activation levels for a monetary gambling task. Furthermore, this group also exhibited decreased functional connectivity between the right auditory cortex and ventral striatum (including the NAcc). In contrast, individuals with greater than average response to music showed enhanced connectivity between these structures. Thus, our results suggest that specific musical anhedonia may be associated with a reduction in the interplay between the auditory cortex and the subcortical reward network, indicating a pivotal role of this interaction for the enjoyment of music.

Strength of Temporal White Matter Pathways Predicts Semantic Learning.

Learning the associations between words and meanings is a fundamental human ability. Although the language network is cortically well defined, the role of the white matter pathways supporting novel word-to-meaning mappings remains unclear. Here, by using contextual and cross-situational word learning, we tested whether learning the meaning of a new word is related to the integrity of the language-related white matter pathways in 40 adults (18 women). The arcuate, uncinate, inferior-fronto-occipital and inferior-longitudinal fasciculi were virtually dissected using manual and automatic deterministic fiber tracking. Critically, the automatic method allowed assessing the white matter microstructure along the tract. Results demonstrate that the microstructural properties of the left inferior-longitudinal fasciculus predict contextual learning, whereas the left uncinate was associated with cross-situational learning. In addition, we identified regions of special importance within these pathways: the posterior middle temporal gyrus, thought to serve as a lexical interface and specifically related to contextual learning; the anterior temporal lobe, known to be an amodal hub for semantic processing and related to cross-situational learning; and the white matter near the hippocampus, a structure fundamental for the initial stages of new-word learning and, remarkably, related to both types of word learning. No significant associations were found for the inferior-fronto-occipital fasciculus or the arcuate. While previous results suggest that learning new phonological word forms is mediated by the arcuate fasciculus, these findings show that the temporal pathways are the crucial neural substrate supporting one of the most striking human abilities: our capacity to identify correct associations between words and meanings under referential indeterminacy.SIGNIFICANCE STATEMENT The language-processing network is cortically (i.e., gray matter) well defined. However, the role of the white matter pathways that support novel word learning within this network remains unclear. In this work, we dissected language-related (arcuate, uncinate, inferior-fronto-occipital, and inferior-longitudinal) fasciculi using manual and automatic tracking. We found the left inferior-longitudinal fasciculus to be predictive of word-learning success in two word-to-meaning tasks: contextual and cross-situational learning paradigms. The left uncinate was predictive of cross-situational word learning. No significant correlations were found for the arcuate or the inferior-fronto-occipital fasciculus. While previous results showed that learning new phonological word forms is supported by the arcuate fasciculus, these findings demonstrate that learning new word-to-meaning associations is mainly dependent on temporal white matter pathways.

Unraveling the Role of the Hippocampus in Reversal Learning.

Research in reversal learning has mainly focused on the functional role of dopamine and striatal structures in driving behavior on the basis of classic reinforcement learning mechanisms. However, recent evidence indicates that, beyond classic reinforcement learning adaptations, individuals may also learn the inherent task structure and anticipate the occurrence of reversals. A candidate structure to support such task representation is the hippocampus, which might create a flexible representation of the environment that can be adaptively applied to goal-directed behavior. To investigate the functional role of the hippocampus in the implementation of anticipatory strategies in reversal learning, we first studied, in 20 healthy individuals (11 women), whether the gray matter anatomy and volume of the hippocampus were related to anticipatory strategies in a reversal learning task. Second, we tested 20 refractory temporal lobe epileptic patients (11 women) with unilateral hippocampal sclerosis, who served as a hippocampal lesion model. Our results indicate that healthy participants were able to learn the task structure and use it to guide their behavior and optimize their performance. Participants' ability to adopt anticipatory strategies correlated with the gray matter volume of the hippocampus. In contrast, hippocampal patients were unable to grasp the higher-order structure of the task with the same success than controls. Present results indicate that the hippocampus is necessary to respond in an appropriately flexible manner to high-order environments, and disruptions in this structure can render behavior habitual and inflexible.SIGNIFICANCE STATEMENT Understanding the neural substrates involved in reversal learning has provoked a great deal of interest in the last years. Studies with nonhuman primates have shown that, through repetition, individuals are able to anticipate the occurrence of reversals and, thus, adjust their behavior accordingly. The present investigation is devoted to know the role of the hippocampus in such strategies. Importantly, our findings evidence that the hippocampus is necessary to anticipate the occurrence of reversals, and disruptions in this structure can render behavior habitual and inflexible.

Theta oscillations integrate functionally segregated sub-regions of the medial prefrontal cortex.

Reinforcement learning requires the dynamic interplay of several specialized networks distributed across the brain. A potential mechanism to establish accurate temporal coordination among these paths is through the synchronization of neuronal activity to a common rhythm of neuronal firing. Previous EEG studies have suggested that theta oscillatory activity might be crucial in the integration of information from motivational and attentional paths that converge into the medial Prefrontal Cortex (mPFC) during reward-guided learning. However, due to the low spatial resolution of EEG, this hypothesis has not been directly tested. Here, by combining EEG and fMRI, we show that theta oscillations serve as common substrate for the engagement of separated sub-regions within the mPFC (the pre-Supplementary Motor Area and the dorsomedial Prefrontal Cortex), underlying different cognitive operations (encoding of outcome valence and unsigned prediction errors) through separate functional paths (the Salience and the Central Executive Networks).

Beta oscillations and reward processing: Coupling oscillatory activity and hemodynamic responses.

Diverse cortical and subcortical regions are synergically engaged during reward processing. Previous studies using time-frequency decomposition of Electroencephalography (EEG) data have revealed an increase of mid-frontal beta oscillatory activity (BOA) after reward delivery, which could be a potential mechanism in the coordination of the different areas engaged during reward processing. In order to evaluate this hypothesis, twenty subjects performed a monetary gambling paradigm in two separate sessions (EEG and fMRI). Time-frequency oscillatory EEG data and fMRI activity were fused using Joint Independent Component Analysis (ICA). The present results showed that mid-frontal BOA elicited by monetary gains is associated with the engagement of a fronto-striatal-hippocampal network previously involved in reward-related memory enhancement, supporting the role of this activity during reward processing.

Multiple brain networks underpinning word learning from fluent speech revealed by independent component analysis.

Although neuroimaging studies using standard subtraction-based analysis from functional magnetic resonance imaging (fMRI) have suggested that frontal and temporal regions are involved in word learning from fluent speech, the possible contribution of different brain networks during this type of learning is still largely unknown. Indeed, univariate fMRI analyses cannot identify the full extent of distributed networks that are engaged by a complex task such as word learning. Here we used Independent Component Analysis (ICA) to characterize the different brain networks subserving word learning from an artificial language speech stream. Results were replicated in a second cohort of participants with a different linguistic background. Four spatially independent networks were associated with the task in both cohorts: (i) a dorsal Auditory-Premotor network; (ii) a dorsal Sensory-Motor network; (iii) a dorsal Fronto-Parietal network; and (iv) a ventral Fronto-Temporal network. The level of engagement of these networks varied through the learning period with only the dorsal Auditory-Premotor network being engaged across all blocks. In addition, the connectivity strength of this network in the second block of the learning phase correlated with the individual variability in word learning performance. These findings suggest that: (i) word learning relies on segregated connectivity patterns involving dorsal and ventral networks; and (ii) specifically, the dorsal auditory-premotor network connectivity strength is directly correlated with word learning performance.

Frontal theta oscillatory activity is a common mechanism for the computation of unexpected outcomes and learning rate.

In decision-making processes, the relevance of the information yielded by outcomes varies across time and situations. It increases when previous predictions are not accurate and in contexts with high environmental uncertainty. Previous fMRI studies have shown an important role of medial pFC in coding both reward prediction errors and the impact of this information to guide future decisions. However, it is unclear whether these two processes are dissociated in time or occur simultaneously, suggesting that a common mechanism is engaged. In the present work, we studied the modulation of two electrophysiological responses associated to outcome processing-the feedback-related negativity ERP and frontocentral theta oscillatory activity-with the reward prediction error and the learning rate. Twenty-six participants performed two learning tasks differing in the degree of predictability of the outcomes: a reversal learning task and a probabilistic learning task with multiple blocks of novel cue-outcome associations. We implemented a reinforcement learning model to obtain the single-trial reward prediction error and the learning rate for each participant and task. Our results indicated that midfrontal theta activity and feedback-related negativity increased linearly with the unsigned prediction error. In addition, variations of frontal theta oscillatory activity predicted the learning rate across tasks and participants. These results support the existence of a common brain mechanism for the computation of unsigned prediction error and learning rate.

ERP evidence of adaptive changes in error processing and attentional control during rhythm synchronization learning.

The ability to detect and use information from errors is essential during the acquisition of new skills. There is now a wealth of evidence about the brain mechanisms involved in error processing. However, the extent to which those mechanisms are engaged during the acquisition of new motor skills remains elusive. Here we examined rhythm synchronization learning across 12 blocks of practice in musically naïve individuals and tracked changes in ERP signals associated with error-monitoring and error-awareness across distinct learning stages. Synchronization performance improved with practice, and performance improvements were accompanied by dynamic changes in ERP components related to error-monitoring and error-awareness. Early in learning, when performance was poor and the internal representations of the rhythms were weaker we observed a larger error-related negativity (ERN) following errors compared to later learning. The larger ERN during early learning likely results from greater conflict between competing motor responses, leading to greater engagement of medial-frontal conflict monitoring processes and attentional control. Later in learning, when performance had improved, we observed a smaller ERN accompanied by an enhancement of a centroparietal positive component resembling the P3. This centroparietal positive component was predictive of participant's performance accuracy, suggesting a relation between error saliency, error awareness and the consolidation of internal templates of the practiced rhythms. Moreover, we showed that during rhythm learning errors led to larger auditory evoked responses related to attention orientation which were triggered automatically and which were independent of the learning stage. The present study provides crucial new information about how the electrophysiological signatures related to error-monitoring and error-awareness change during the acquisition of new skills, extending previous work on error processing and cognitive control mechanisms to a more ecologically valid context.

Overactivation of the supplementary motor area in chronic stroke patients.

Stroke induces a loss of neural function, but it triggers a complex amount of mechanisms to compensate the associated functional impairment. The present study aims to increase our understanding of the functional reshape of the motor system observed in chronic stroke patients during the preparation and the execution of movements. A cohort of 14 chronic stroke patients with a mild-to-moderate hemiparesis and 14 matched healthy controls were included in this study. Participants were asked to perform a bimanual reaction time task synchronizing alternated responses to the presentation of a visual cue. We used Laplacian-transformed EEG activity (LT-EEG) recorded at the locations Cz and C3/C4 to study the response-locked components associated with the motor system activity during the performance of this task. Behaviorally, patients showed larger variable errors than controls in synchronizing the frequency of execution of responses to the interstimulus interval, as well as slower responses compared with controls. LT-EEG analysis showed that whereas control participants increased their supplementary motor area (SMA) activity during the preparation of all responses, patients only showed an increment of activity over this area during their first response of the sequence. More interestingly, patients showed a clear increment of the LT-EEG activity associated with SMA shortly after motor responses as compared to the control participants. Finally, patients showed a hand-dependent inhibitory activity over motor areas ipsilateral to the response hand. Overall, our findings reveal drastic differences in the temporal dynamics of the LT-EEG components associated with the activity over motor and premotor cortices in chronic stroke patients compared with matched control participants during alternated hand responses.