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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.

Using an individual differences approach, we evaluated whether manual and locomotor adaptation are associated in terms of adaptation and savings across days, and whether they rely on shared underlying mechanisms involving visuospatial working memory or visual field dependence. Participants performed a manual and a locomotor adaptation task during 4 separate test sessions over a 3-month period. Reliable adaptation and savings were observed for both tasks. It was further found that higher visuospatial working memory performance and lower visual field dependence scores were associated with faster learning in the manual and locomotor tasks, respectively. Moreover, adaptation rates were correlated between the 2 tasks in the final test session, suggesting that people may gradually be learning something generalizable about the adaptation process.

In this study, we investigate whether individual variability in the rate of visuomotor adaptation and multiday savings is associated with differences in regional gray matter volume and resting-state functional connectivity. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. Functional connectivity strength between sensorimotor, dorsal cingulate, and temporoparietal regions of the brain was found to predict the rate of learning during the early phase of the adaptation task. In contrast, default mode network connectivity strength was found to predict both the rate of learning during the late adaptation phase and savings. As for structural predictors, greater gray matter volume in temporoparietal and occipital regions predicted faster early learning, whereas greater gray matter volume in superior posterior regions of the cerebellum predicted faster late learning. These findings suggest that the offline neural predictors of early adaptation may facilitate the cognitive aspects of sensorimotor adaptation, supported by the involvement of temporoparietal and cingulate networks. The offline neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations., (© 2017 Wiley Periodicals, Inc.)

Brain activity typically increases with increasing working memory (WM) load, regardless of age, before reaching an apparent ceiling. However, older adults exhibit greater brain activity and reach ceiling at lower loads than younger adults, possibly reflecting compensation at lower loads and dysfunction at higher loads. We hypothesized that WM training would bolster neural efficiency, such that the activation peak would shift towards higher memory loads after training. Pre-training, older adults showed greater recruitment of the WM network than younger adults across all loads, with decline at the highest load. Ten days of adaptive training on a verbal WM task improved performance and led to greater brain responsiveness at higher loads for both groups. For older adults the activation peak shifted rightward towards higher loads. Finally, training increased task-related functional connectivity in older adults, both within the WM network and between this task-positive network and the task-negative/default-mode network. These results provide new evidence for functional plasticity with training in older adults and identify a potential signature of improvement at the neural level.

OBJECTIVE: The majority of the population will experience some cognitive decline with age. Therefore, the development of effective interventions to mitigate age-related decline is critical for older adults cognitive functioning and their quality of life. METHODS: In our randomized controlled multisite trial, we target participants working memory (WM) skills, and in addition, we focus on the interventions optimal scheduling in order to test whether and how the distribution of training sessions might affect task learning, and ultimately, transfer. Healthy older adults completed an intervention targeting either WM or general knowledge twice per day, once per day, or once every-other-day. Before and after the intervention and 3 months after training completion, participants were tested in a variety of cognitive domains, including those representing functioning in everyday life. RESULTS: In contrast to our hypotheses, spacing seems to affect learning only minimally. We did observe some transfer effects, especially within the targeted cognitive domain (WM and inhibition/interference), which remained stable at the 3-month follow-up. DISCUSSION: Our findings have practical implications by showing that the variation in training schedule, at least within the range used here, does not seem to be a crucial element for training benefits.