Neural predictors of sensorimotor adaptation rate and savings.
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ABSTRACT:
SUBMITTER: Cassady K
PROVIDER: S-EPMC5847457 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In the present study we evaluated changes in neural activation that occur over the time course of multiple days of sensorimotor adaptation, and identified individual neural predictors of adaptation and savings magnitude. We collected functional MRI data while participants performed a manual adaptation task during four separate test sessions over a three-month period. This allowed us to examine changes in activation and associations with adaptation and savings at subsequent sessions. Participants exhibited reliable savings of adaptation across the four sessions. Brain activity associated with early adaptation increased across the sessions in a variety of frontal, parietal, cingulate, and temporal cortical areas, as well as various subcortical areas. We found that savings was positively associated with activation in several striatal, parietal, and cingulate cortical areas including the putamen, precuneus, angular gyrus, dorsal anterior cingulate cortex (dACC), and cingulate motor area. These findings suggest that participants may learn how to better engage cognitive processes across days, potentially reflecting improvements in action selection. We propose that such improvements may rely on action-value assignments, which previously have been linked to the dACC and striatum. As correct movements are assigned a higher value than incorrect movements, the former are more likely to be performed again.
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Project description:Recent computational and behavioral studies suggest that motor adaptation results from the update of multiple memories with different timescales. Here, we designed a model-based functional magnetic resonance imaging (fMRI) experiment in which subjects adapted to two opposing visuomotor rotations. A computational model of motor adaptation with multiple memories was fitted to the behavioral data to generate time-varying regressors of brain activity. We identified regional specificity to timescales: in particular, the activity in the inferior parietal region and in the anterior-medial cerebellum was associated with memories for intermediate and long timescales, respectively. A sparse singular value decomposition analysis of variability in specificities to timescales over the brain identified four components, two fast, one middle, and one slow, each associated with different brain networks. Finally, a multivariate decoding analysis showed that activity patterns in the anterior-medial cerebellum progressively represented the two rotations. Our results support the existence of brain regions associated with multiple timescales in adaptation and a role of the cerebellum in storing multiple internal models.
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Project description:Altered vestibular signaling and body unloading in microgravity results in sensory reweighting and adaptation. Microgravity effects are well-replicated in head-down tilt bed rest (HDBR). Artificial gravity (AG) is a potential countermeasure to mitigate the effects of microgravity on human physiology and performance. We examined the effectiveness of daily AG for mitigating brain and/or behavioral changes in 60 days of HDBR. One group received AG for 30 minutes daily (AG; n = 16) and a control group spent the same time in HDBR but received no AG (CTRL; n = 8). All participants performed a sensorimotor adaptation task five times during fMRI scanning: twice prior to HDBR, twice during HDBR, and once following HDBR. The AG group showed similar behavioral adaptation effects compared with the CTRLs. We identified decreased brain activation in the AG group from pre to late HDBR in the cerebellum for the task baseline portion and in the thalamus, calcarine, cuneus, premotor cortices, and superior frontal gyrus in the AG group during the early adaptation phase. The two groups also exhibited differential brain-behavior correlations. Together, these results suggest that AG may result in a reduced recruitment of brain activity for basic motor processes and sensorimotor adaptation. These effects may stem from the somatosensory and vestibular stimulation that occur with AG.
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Project description:Humans vary greatly in their motor learning abilities, yet little is known about the neural mechanisms that underlie this variability. Recent neuroimaging and electrophysiological studies demonstrate that large-scale neural dynamics inhabit a low-dimensional subspace or manifold, and that learning is constrained by this intrinsic manifold architecture. Here, we asked, using functional MRI, whether subject-level differences in neural excursion from manifold structure can explain differences in learning across participants. We had subjects perform a sensorimotor adaptation task in the MRI scanner on 2 consecutive days, allowing us to assess their learning performance across days, as well as continuously measure brain activity. We find that the overall neural excursion from manifold activity in both cognitive and sensorimotor brain networks is associated with differences in subjects' patterns of learning and relearning across days. These findings suggest that off-manifold activity provides an index of the relative engagement of different neural systems during learning, and that subject differences in patterns of learning and relearning are related to reconfiguration processes occurring in cognitive and sensorimotor networks.
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Project description:Error detection and correction are essential components of motor skill learning. These processes have been well characterized in cognitive psychology using electroencephalography (EEG) to record an event-related potential (ERP) called error-related negativity (ERN). However, it is unclear whether this ERP component is sensitive to the magnitude of the error made in a sensorimotor adaptation task. In the present study, we tested the function of error-related activity in a visuomotor adaptation task. To examine whether error size is reflected in the ERP, two groups of participants adapted manual aiming movements to either a small (30 degrees) or large (45 degrees) rotation of the visual feedback display. Each participant's trials were sorted into large and small error trials using a median split to examine potential error magnitude waveform differences. We also examined these trial types at the early and late stages of adaptation. There were no group differences for the behavioral or neural measures; however, waveforms from large error trials were significantly different from small error trials. The waveforms also changed as a function of practice as early adaptation waveforms were larger than late adaptation waveforms. The observed ERP component reflected differences in error magnitude with the amount of activity corresponding to the size of the error. Movement monitoring potentials likely affected the frequency and time course of the waveform so that it did not resemble the typical ERN; however, error-related activity was still distinguishable. The present findings are discussed in terms of current theories of the ERN as well as skill acquisition.
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Project description:Humans vary greatly in their motor learning abilities, yet little is known about the neural processes that underlie this variability. We identified distinct profiles of human sensorimotor adaptation that emerged across 2 days of learning, linking these profiles to the dynamics of whole-brain functional networks early on the first day when cognitive strategies toward sensorimotor adaptation are believed to be most prominent. During early learning, greater recruitment of a network of higher-order brain regions, involving prefrontal and anterior temporal cortex, was associated with faster learning. At the same time, greater integration of this "cognitive network" with a sensorimotor network was associated with slower learning, consistent with the notion that cognitive strategies toward adaptation operate in parallel with implicit learning processes of the sensorimotor system. On the second day, greater recruitment of a network that included the hippocampus was associated with faster learning, consistent with the notion that declarative memory systems are involved with fast relearning of sensorimotor mappings. Together, these findings provide novel evidence for the role of higher-order brain systems in driving variability in adaptation.
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Project description:Personal saving is an important indicator of future economic prosperity. Despite the growth in gross domestic product per capita (GDPPC) from 2012 to 2022 in the Kingdom of Saudi Arabia (KSA), the personal savings rate remains low. Only a few studies have explored savings in KSA, but no study that used time savings deposits (TSD) to measure personal savings exists. Thus, this study aims to investigate the determinants of personal savings employing TSD. Using data from the Saudi Central Bank from 2012 to 2022, this study empirically examines the determinants of TSD. The autoregressive distributed lag cointegration technique determines the long-run relationship between the study's variables. The study finds that GDPPC, deposit interest rates (DIR), consumer loans (CLs), and real estate loans (RELs) significantly impact personal savings. Only GDPPC and RELs have a significant negative impact on personal savings. The study is among the few to examine savings in KSA but, unlike other studies, used TSD as a measure of personal savings. In conclusion, several implications and recommendations for policymakers and financial institutions were presented.
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Project description:This study investigates the impact of gravity on lower limb muscle coordination during pedaling. It explores how pedaling behaviors, kinematics, and muscle activation patterns dynamically adapts to changes in gravity and resistance levels. The experiment was conducted in parabolic flights, simulating microgravity, hypergravity (1.8 g), and normogravity conditions. Participants pedaled on an ergometer with varying resistances. The goal was to identify potential changes in muscle synergies and activation strategies under different gravitational contexts. Results indicate that pedaling cadence adjusted naturally in response to both gravity and resistance changes. Cadence increased with higher gravity and decreased with higher resistance levels. Muscular activities were characterized by two synergies representing pull and push phases of pedaling. The timing of synergy activation was influenced by gravity, with a delay in activation observed in microgravity compared to other conditions. Despite these changes, the velocity profile of pedaling remained stable across gravity conditions. The findings strongly suggest that the CNS dynamically manages the shift in body weight by finely tuning muscular coordination, thereby ensuring the maintenance of a stable motor output. Furthermore, electromyography analysis suggest that neuromuscular discharge frequencies were not affected by gravity changes. This implies that the types of muscle fibers recruited during exercise in modified gravity are similar to those used in normogravity. This research has contributed to a better understanding of how the human locomotor system responds to varying gravitational conditions, shedding light on the potential mechanisms underlying astronauts' gait changes upon returning from space missions.
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Project description:Our ability to enact successful goal-directed actions involves multiple learning processes. Among these processes, implicit motor adaptation ensures that the sensorimotor system remains finely tuned in response to changes in the body and environment. Whether Parkinson's disease impacts implicit motor adaptation remains a contentious area of research: whereas multiple reports show impaired performance in this population, many others show intact performance. While there is a range of methodological differences across studies, one critical issue is that performance in many of the studies may reflect a combination of implicit adaptation and strategic re-aiming. Here, we revisited this controversy using a visuomotor task designed to isolate implicit adaptation. In two experiments, we found that adaptation in response to a wide range of visual perturbations was similar in Parkinson's disease and matched control participants. Moreover, in a meta-analysis of previously published and unpublished work, we found that the mean effect size contrasting Parkinson's disease and controls across 16 experiments involving over 200 participants was not significant. Together, these analyses indicate that implicit adaptation is preserved in Parkinson's disease, offering a fresh perspective on the role of the basal ganglia in sensorimotor learning.
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