Motor and non-motor error and the influence of error magnitude on brain activity

MEG signatures of long-term effects of agreement and disagreement with the majority

People often change their beliefs by succumbing to an opinion of others. Such changes are often referred to as effects of social influence. While some previous studies have focused on the reinforcement learning mechanisms of social influence or on its internalization, others have reported evidence of changes in sensory processing evoked by social influence of peer groups. In this study, we used magnetoencephalographic (MEG) source imaging to further investigate the long-term effects of agreement and disagreement with the peer group. The study was composed of two sessions. During the first session, participants rated the trustworthiness of faces and subsequently learned group rating of each face. In the first session, a neural marker of an immediate mismatch between individual and group opinions was found in the posterior cingulate cortex, an area involved in conflict-monitoring and reinforcement learning. To identify the neural correlates of the long-lasting effect of the group opinion, we analysed MEG activity while participants rated faces during the second session. We found MEG traces of past disagreement or agreement with the peers at the parietal cortices 230 ms after the face onset. The neural activity of the superior parietal lobule, intraparietal sulcus, and precuneus was significantly stronger when the participant’s rating had previously differed from the ratings of the peers. The early MEG correlates of disagreement with the majority were followed by activity in the orbitofrontal cortex 320 ms after the face onset. Altogether, the results reveal the temporal dynamics of the neural mechanism of long-term effects of disagreement with the peer group: early signatures of modified face processing were followed by later markers of long-term social influence on the valuation process at the ventromedial prefrontal cortex.

Momentary lapses of attention in multisensory environment

Momentary lapses in attention disrupt goal-directed behaviors, and have been associated with increased pre-stimulus activity in the default mode network (DMN). The human brain often encounters multisensory inputs. It remains unknown, however, whether the neural mechanisms underlying attentional lapses are supra-modal or modality-dependent. To answer this question in the present functional magnetic resonance imaging (fMRI) study, we asked participants to respond to either visual or auditory targets in a multisensory paradigm, and focused on the pre-stimulus neural signals underlying attentional lapses, which resulted in impaired task performance, in terms of both delayed RTs and behavioral errors, in different sensory modalities. Behaviorally, mean reaction times (RTs) were equivalent between the visual and auditory modality. At the neural level, increased pre-stimulus neural activity in the majority of the core DMN regions, including medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and left angular gyrus (AG), predicted delayed RTs more effectively in the visual than auditory modality. Especially, increased pre-stimulus activity in the mPFC predicted not only delayed RTs but also errors, more effectively in the visual than auditory modality. On the other hand, increased pre-stimulus activity in the anterior precuneus predicted both prolonged RTs and errors more effectively in the auditory than visual modality. Moreover, a supra-modal mechanism was revealed in the left middle temporal gyrus (MTG), which belongs to the posterior DMN. Increased pre-stimulus neural activity in the left MTG predicted impaired task performance in both the visual and auditory modality. Taken together, the core DMN regions manifest vision-dependent mechanisms of attentional lapses while a novel region in the anterior precuneus shows audition-dependent mechanisms of attentional lapses. Moreover, left MTG in the posterior DMN manifests a supra-modal mechanism of attentional lapses, independent of the modality of sensory inputs.

Neural circuits activated by error amplification and haptic guidance training techniques during performance of a timing-based motor task by healthy individuals

To promote motor learning, robotic devices have been used to improve subjects' performance by guiding desired movements (haptic guidance-HG) or by artificially increasing movement errors to foster a more rapid learning (error amplification-EA). To better understand the neurophysiological basis of motor learning, a few studies have evaluated brain regions activated during EA/HG, but none has compared both approaches. The goal of this study was to investigate using fMRI which brain networks were activated during a single training session of HG/EA in healthy adults learning to play a computerized pinball-like timing task. Subjects had to trigger a robotic device by flexing their wrist at the correct timing to activate a virtual flipper and hit a falling ball towards randomly positioned targets. During training with HG/EA, subjects' timing errors were decreased/increased, respectively, by the robotic device to delay or accelerate their wrist movement. The results showed that at the beginning of the training period with HG/EA, an error-detection network, including cerebellum and angular gyrus, was activated, consistent with subjects recognizing discrepancies between their intended actions and the actual movement timing. At the end of the training period, an error-detection network was still present for EA, while a memory consolidation/automatization network (caudate head and parahippocampal gyrus) was activated for HG. The results indicate that training movement with various kinds of robotic input relies on different brain networks. Better understanding the neurophysiological underpinnings of brain processes during HG/EA could prove useful for optimizing rehabilitative movement training for people with different patterns of brain damage.

To err is (perfectly) human: behavioural and neural correlates of error processing and perfectionism

The attitude towards one’s own imperfection strongly varies between individuals. Here, we investigated variations in error-related activity depending on two sub-traits of perfectionism, Personal Standard Perfectionism (PSP) and Evaluative Concern Perfectionism (ECP) in a large scale functional magnetic resonance imaging study (N = 75) using a digit-flanker task. Participants with higher PSP scores showed both more post-error slowing and more neural activity in the medial-frontal gyrus including anterior cingulate cortex after errors. Interestingly, high-EC perfectionists with low PSP showed no post-error slowing and the highest activity in the middle frontal gyrus, whereas high-EC perfectionists with high PSP showed the lowest activity in this brain area and more post-error slowing. Our findings are in line with the hypothesis that perfectionists with high concerns but low standards avoid performance monitoring to avoid the worry-inducing nature of detecting personal failure and the anticipation of poor evaluation by others. However, the stronger goal-oriented performance motivation of perfectionists with high concerns and high standards may have led to less avoidance of error processing and a more intense involvement with the imperfect behaviour, which is essential for improving future performance.

EEG Theta Dynamics within Frontal and Parietal Cortices for Error Processing during Reaching Movements in a Prism Adaptation Study Altering Visuo-Motor Predictive Planning

Modulation of frontal midline theta (fmθ) is observed during error commission, but little is known about the role of theta oscillations in correcting motor behaviours. We investigate EEG activity of healthy partipants executing a reaching task under variable degrees of prism-induced visuo-motor distortion and visual occlusion of the initial arm trajectory. This task introduces directional errors of different magnitudes. The discrepancy between predicted and actual movement directions (i.e. the error), at the time when visual feedback (hand appearance) became available, elicits a signal that triggers on-line movement correction. Analysis were performed on 25 EEG channels. For each participant, the median value of the angular error of all reaching trials was used to partition the EEG epochs into high- and low-error conditions. We computed event-related spectral perturbations (ERSP) time-locked either to visual feedback or to the onset of movement correction. ERSP time-locked to the onset of visual feedback showed that fmθ increased in the high- but not in the low-error condition with an approximate time lag of 200 ms. Moreover, when single epochs were sorted by the degree of motor error, fmθ started to increase when a certain level of error was exceeded and, then, scaled with error magnitude. When ERSP were time-locked to the onset of movement correction, the fmθ increase anticipated this event with an approximate time lead of 50 ms. During successive trials, an error reduction was observed which was associated with indices of adaptations (i.e., aftereffects) suggesting the need to explore if theta oscillations may facilitate learning. To our knowledge this is the first study where the EEG signal recorded during reaching movements was time-locked to the onset of the error visual feedback. This allowed us to conclude that theta oscillations putatively generated by anterior cingulate cortex activation are implicated in error processing in semi-naturalistic motor behaviours.

Development of ERN together with an internal model of audio-motor associations

The brain's reactions to error are manifested in several event related potentials (ERP) components, derived from electroencephalographic (EEG) signals. Although these components have been known for decades, their interpretation is still controversial. A current hypothesis (first indicator hypothesis) claims that the first indication of an action being erroneous leads to a negative deflection of the EEG signal over frontal midline areas. In some cases this requires sensory feedback in the form of knowledge of results (KR). If KR is given, then the first negative deflection can be found around 250 ms after feedback presentation (feedback-related negativity, FRN). When KR is not required, a negative deflection is found already around 100 ms after action onset (ERN). This deflection may be evoked when a mismatch between required and actually executed actions is detected. To detect such a mismatch, however, necessitates knowledge about which action is required. To test this assumption, the current study monitored EEG error components during acquisition of an internal model, i.e., acquisition of the knowledge of which actions are needed to reach certain goals. Actions consisted of finger presses on a piano keyboard and goals were tones of a certain pitch to be generated, thus the internal model represented audio-motor mapping. Results show that with increasing proficiency in mapping goals to appropriate actions, the amplitude of the ERN increased, whereas the amplitude of the FRN remained unchanged. Thus, when knowledge is present about which action is required, this supports generation of an ERN around 100 ms, likely by detecting a mismatch between required and performed actions. This is in accordance with the first indicator hypothesis. The present study furthermore lends support to the notion that FRN mainly relies on comparison of sensory targets with sensory feedback.

The cerebellum and cognition: evidence from functional imaging studies

Evidence for a role of the human cerebellum in cognitive functions comes from anatomical, clinical and neuroimaging data. Functional neuroimaging reveals cerebellar activation during a variety of cognitive tasks, including language, visual-spatial, executive, and working memory processes. It is important to note that overt movement is not a prerequisite for cerebellar activation: the cerebellum is engaged during conditions which either control for motor output or do not involve motor responses. Resting-state functional connectivity data reveal that, in addition to networks underlying motor control, the cerebellum is part of "cognitive" networks with prefrontal and parietal association cortices. Consistent with these findings, regional differences in activation patterns within the cerebellum are evident depending on the task demands, suggesting that the cerebellum can be broadly divided into functional regions based on the patterns of anatomical connectivity between different regions of the cerebellum and sensorimotor and association areas of the cerebral cortex. However, the distinct contribution of the cerebellum to cognitive tasks is not clear. Here, the functional neuroimaging evidence for cerebellar involvement in cognitive functions is reviewed and related to hypotheses as to why the cerebellum is active during such tasks. Identifying the precise role of the cerebellum in cognition-as well as the mechanism by which the cerebellum modulates performance during a wide range of tasks-remains a challenge for future investigations.

Interregional synchrony of visuomotor tracking: perturbation effects and individual differences

The present study evaluated the neural and behavioural correlates associated with a visuomotor tracking task during which a sensory perturbation was introduced that created a directional bias between moving hand and cursor position. The results revealed that trajectory error increased as a result of the perturbation in conjunction with a dynamic neural reorganization of cluster patterns that reflected distinct processing. In particular, a negatively activated cluster, characterizing the degraded information processing due to the perturbation, involved both hemispheres as well as midline area. Conversely, a positively activated cluster, indicative of compensatory processing was strongly confined to the left (dominant) hemisphere. In addition, a brain-behavioural association of good vs. poor performing participants enabled to localize a neural circuit within the left hemisphere and midline area that linked with successful performance. Overall, these data reinforce the functional significance of interregional synchrony in defining response output and behavioural success.