Task Feedback Processing Differs Between Young and Older Adults in Visuomotor Rotation Learning Despite Similar Initial Adaptation and Savings

Age-Related Topological Organization of Phase-Amplitude Coupling Between Postural Fluctuations and Scalp EEG During Unsteady Stance

Through phase-amplitude analysis, this study investigated how low-frequency postural fluctuations interact with high-frequency scalp electroencephalography (EEG) amplitudes, shedding light on age-related mechanic differences in balance control during uneven surface navigation. Twenty young ( 24.1 ± 1.9 years) and twenty older adults ( 66.2 ± 2.7 years) stood on a training stabilometer with visual guidance, while their scalp EEG and stabilometer plate movements were monitored. In addition to analyzing the dynamics of the postural fluctuation phase, phase-amplitude coupling (PAC) for postural fluctuations below 2 Hz and within EEG sub-bands (theta: 4-7 Hz, alpha: 8-12 Hz, beta: 13-35 Hz) was calculated. The results indicated that older adults exhibited significantly larger postural fluctuation amplitudes(p <0.001) and lower mean frequencies of the postural fluctuation phase ( p = 0.005 ) than young adults. The PAC between postural fluctuation and theta EEG (FCz and bilateral temporal-parietal-occipital area), as well as that between postural fluctuation and alpha EEG oscillation, was lower in older adults than in young adults (p <0.05). In contrast, the PAC between the phase of postural fluctuation and beta EEG oscillation, particularly in C3 ( p=0.006 ), was higher in older adults than in young adults. In summary, the postural fluctuation phase and phase-amplitude coupling between postural fluctuation and EEG are sensitive indicators of the age-related decline in postural adjustments, reflecting less flexible motor state transitions and adaptive changes in error monitoring and visuospatial attention.

Spatio-temporal modulation of cortical activity during motor deadaptation depends on the feedback of task-related error

Motor adaptations are responsible for recalibrating actions and facilitating the achievement of goals in a constantly changing environment. Once consolidated, the decay of motor adaptation is a process affected by available sensory information during deadaptation. However, the cortical response to task error feedback during the deadaptation phase has received little attention. Here, we explored changes in brain cortical responses due to feedback of task-related error during deadaptation. Twelve healthy volunteers were recruited for the study. Right hand movement and EEG were recorded during repetitive trials of a hand reaching movement. A visuomotor rotation of 30° was introduced to induce motor adaptation. Volunteers participated in two experimental sessions organized in baseline, adaptation, and deadaptation blocks. In the deadaptation block, the visuomotor rotation was removed, and visual feedback was only provided in one session. Performance was quantified using angle end-point error, averaged speed, and movement onset time. A non-parametric spatiotemporal cluster-level permutation test was used to analyze the EEG recordings. During deadaptation, participants experienced a greater error reduction when feedback of the cursor was provided. The EEG responses showed larger activity in the left centro-frontal parietal areas during the deadaptation block when participants received feedback, as opposed to when they did not receive feedback. Centrally distributed clusters were found for the adaptation and deadaptation blocks in the absence of visual feedback. The results suggest that visual feedback of the task-related error activates cortical areas related to performance monitoring, depending on the accessible sensory information.

Feedback processing in cognitive and motor tasks: A meta-analysis on the feedback-related negativity

For motor learning, the processing of behavioral outcomes is of high significance. The feedback-related negativity (FRN) is an event-related potential, which is often described as a correlate of the reward prediction error in reinforcement learning. The number of studies examining the FRN in motor tasks is increasing. This meta-analysis summarizes the component in the motor domain and compares it to the cognitive domain. Therefore, a data set of a previous meta-analysis in the cognitive domain that comprised 47 studies  was reanalyzed and compared to additional 25 studies of the motor domain. Further, a moderator analysis for the studies in the motor domain was conducted. The FRN amplitude was higher in the motor domain than in the cognitive domain. This might be related to a higher task complexity and a higher feedback ambiguity of motor tasks. The FRN latency was shorter in the motor domain than in the cognitive domain. Given that sensory information can be used as an external feedback predictor prior to the presentation of the final feedback, reward processing in the motor domain may have been faster and reduced the FRN latency. The moderator variable analysis revealed that the feedback modality influenced the FRN latency, with shorter FRN latencies after bimodal than after visual feedback. Processing of outcome feedback seems to share basic principles in both domains; however, differences exist and should be considered in FRN studies. Future research is motivated to scrutinize the effects of bimodal feedback and other moderators within the motor domain.

Age-related changes to electroencephalographic markers of visuomotor error processing and learning in prism adaptation

Aging is associated with changes in cognitive function, including declines in learning, memory, and executive function. Prism adaptation (PA) is a useful paradigm to measure changes in explicit and implicit mechanisms of visuo-motor learning with age, but the neural correlates are not well understood. In the present study, we used PA to investigate visuo-motor learning and error processing in older adults. Twenty older adults (56-85 yrs) and 20 younger adults (18-33 yrs) underwent a goal-oriented reaching task while wearing prism goggles as continuous EEG was recorded to examine neural correlates of error detection. We examined behavioural measures of PA, as well as ERP components previously found associated with the early and late phases of adaptation to visual distortion caused by the prism goggles. Our results indicate important age-related behavioural and neurophysiological differences. Older adults reached more slowly than younger adults but showed the same accuracy throughout the prism exposure. Older adults also displayed larger aftereffects, indicating preserved visuomotor adaptation. EEG results indicated similar initial error processing in older and younger adults, as measured by the feedback error related negativity (FRN). As seen previously in young adults, the P3a and P3b declined over the prism exposure phase in both groups. Older adults displayed reduced P3a amplitude compared to the younger group in the early phase of adaptation, however, suggesting reduced attentional orienting. Finally, the older group exhibited a greater P3b amplitude compared to the younger group in the later phases of adaptation, potentially a marker of enhanced context updating underlying spatial realignment, leading to their larger aftereffect. Implications for age-related learning differences and clinical applications are discussed.

Frontal theta reveals further information about neural valence-dependent processing of augmented feedback in extensive motor practice-A secondary analysis

Supplementing an earlier analysis of event-related potentials in extensive motor learning (Margraf et al., 2022a, 2022b), frontal theta-band activity (4-8 Hz) was scrutinized. Thirty-seven participants learned a sequential arm movement with 192 trials in each of five practice sessions. Feedback, based on a performance adaptive bandwidth, was given after every trial. Electroencephalogram (EEG) was recorded in the first and last practice sessions. The degree of motor automatization was tested under dual-task conditions in a pre-test-post-test design. Quantitative error information was transported in both feedback conditions (positive and negative). Frontal theta activity was discussed as a general signal that cognitive control is needed and, therefore, was expected to be higher after negative feedback. Extensive motor practice promotes automatization, and therefore, decreased frontal theta activity was expected in the later practice. Further, it was expected that frontal theta was predictive for subsequent behavioural adaptations and the amount of motor automatization. As the results show, induced frontal theta power was higher after negative feedback and decreased after five sessions of practice. Moreover, induced theta activity was predictive for error correction and, therefore, an indicator of whether the recruited cognitive resources successfully induced behavioural adaptations. It remains to be solved why these effects, which fit well with the theoretical assumptions, were only revealed by the induced part of frontal theta activity. Further, the amount of theta activity during practice was not predictive for the degree of motor automatization. It seems that there might be a dissociation between attentional resources associated with feedback processing and attentional resources associated with motor control.

The Influence of Age on the Intermanual Transfer and Retention of Implicit Visuomotor Adaptation

We examined age-related changes in intermanual transfer and retention of implicit visuomotor adaptation. We further asked if providing augmented somatosensory feedback regarding movement endpoint would enhance visuomotor adaptation. Twenty young adults and twenty older adults were recruited and randomly divided into an Augmented Feedback group and a Control group. All participants reached to five visual targets with visual feedback rotated 30° counter-clockwise relative to their actual hand motion. Augmented somatosensory feedback was provided at the end of the reach via the robotic handle that participants held. Implicit adaptation was assessed in the absence of visual feedback in the right trained hand and in the left untrained hand following rotated training trials to establish implicit adaptation and intermanual transfer of adaptation respectively. Participants then returned 24 hours later to assess retention in the trained and untrained hands. Results revealed that older adults demonstrated a comparable magnitude of implicit adaptation, transfer and retention of visuomotor adaptation as observed in younger adults, regardless of the presence of augmented somatosensory feedback. To conclude, when visuomotor adaptation is driven implicitly, intermanual transfer and retention do not differ significantly between young and older adults, even when the availability of augmented somatosensory feedback is manipulated.

Dissociable use-dependent processes for volitional goal-directed reaching

Repetition of specific movement biases subsequent actions towards the practiced movement, a phenomenon known as use-dependent learning (UDL). Recent experiments that impose strict constraints on planning time have revealed two sources of use-dependent biases, one arising from dynamic changes occurring during motor planning and another reflecting a stable shift in motor execution. Here, we used a distributional analysis to examine the contribution of these biases in reaching. To create the conditions for UDL, the target appeared at a designated 'frequent' location on most trials, and at one of six 'rare' locations on other trials. Strikingly, the heading angles were bimodally distributed, with peaks at both frequent and rare target locations. Despite having no constraints on planning time, participants exhibited a robust bias towards the frequent target when movements were self-initiated quickly, the signature of a planning bias; notably, the peak near the rare target was shifted in the frequently practiced direction, the signature of an execution bias. Furthermore, these execution biases were not only replicated in a delayed-response task but were also insensitive to reward. Taken together, these results extend our understanding of how volitional movements are influenced by recent experience.

Using EEG to study sensorimotor adaptation

Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.

Does proprioceptive acuity influence the extent of implicit sensorimotor adaptation in young and older adults?

The ability to adjust movements to changes in the environment declines with aging. This age-related decline is caused by the decline of explicit adjustments. However, implicit adaptation remains intact and might even be increased with aging. Since proprioceptive information has been linked to implicit adaptation, it might well be that an age-related decline in proprioceptive acuity might be linked to the performance of older adults in implicit adaptation tasks. Indeed, age-related proprioceptive deficits could lead to altered sensory integration with an increased weighting of the visual sensory-prediction error. Another possibility is that reduced proprioceptive acuity results in an increased reliance on predicted sensory consequences of the movement. Both these explanations led to our preregistered hypothesis: we expected a relation between the decline of proprioception and the amount of implicit adaptation across ages. However, we failed to support this hypothesis. Our results question the existence of reliability-based integration of visual and proprioceptive signals during motor adaptation.