Age-related differences in practice-dependent resting-state functional connectivity related to motor sequence learning

Abstract

Decreased neural plasticity is observed with healthy ageing in the primary sensorimotor (SM1) cortex thought to participate in motor learning and memory consolidation processes. In the present magnetoencephalography study, the post-training reorganization of resting-state functional connectivity (rsFC) and its relation with motor learning and early consolidation in 14 young (19-30 years) and 14 old (66-70 years) healthy participants were investigated. At the behavioral level, participants were trained on a motor sequence learning task then retested 20-30 min later for transient offline gains in performance. Using a sensorimotor seed-based approach, rsFC relying on beta band power envelope correlation was estimated immediately before and 10 min after the learning episode. Post-training changes in rsFC (from before to after learning) were correlated with motor learning performance and with the offline improvement in performance within the hour after learning. Young and old participants exhibited differential patterns of sensorimotor-related rsFC, bearing specific relationships with motor learning and consolidation. Our findings suggest that rsFC changes following learning reflect the offline processing of the new motor skill and contribute to the early memory consolidation within the hour after learning. Furthermore, differences in post-training changes in rsFC between young and old participants support the hypothesis that ageing modulates the neural circuits underlying the learning of a new motor skill and the early subsequent consolidation stages. Hum Brain Mapp 38:923-937, 2017. © 2016 Wiley Periodicals, Inc.

Somatosensory electrical stimulation improves skill acquisition, consolidation, and transfer by increasing sensorimotor activity and connectivity

“…It is conceivable that increased connectivity could not be manifested within the 20 min of SES, which may explain why activity rather than connectivity correlated with skill acquisition on day 1. In addition, the present data reinforce the importance of the ␤ frequency range in visuomotor learning processes (Mary et al 2017;Veldman et al 2018;Wu et al 2014). Available data suggest that the ␤-frequency range-much more than other frequency ranges-may reflect interactions between sensory and motor cortices, and even with muscle spindle afferents, thereby providing further evidence that SES can be used to target the motor system (Baker 2007).…”

“…We measured activity in sensorimotor areas reflected by the N30 somatosensory evoked potential (SEP) that is sensitive to changes in motor performance following skill learning (Andrew et al 2015;Rossi et al 2003) and also quantified interregional connectivity by the phase slope index (PSI). Previous studies showed that the magnitude of connectivity correlated with motor learning (Mary et al 2017;Mehrkanoon et al 2016;Veldman et al 2018;Wu et al 2014). The PSI estimates not only the magnitude, but also the direction of effective connectivity by quantifying the dependence of phase lag between two signals on frequency.…”

The electrophysiological connectome is maintained in healthy elders: a power envelope correlation MEG study

“…Twenty-five young (12 females and 13 males; age: 23.6 ± 2.9 years (mean ± standard deviation); age range: 19–31 years) and twenty-five elderly (15 females and 10 males; 68.8 ± 2.4 years; age range: 65–74 years) healthy adult subjects were included in this study. Of notice, resting-state MEG data from fifteen of the twenty-five elders were already used in previous studies from our group 63 , 64 . All participants were right-handed according to the Edinburgh handedness questionnaire (laterality scores young: 76.4 ± 15.2; laterality scores old: 89.2 ± 13.4), had no prior history of neurological or psychiatric disorder, and did not report of any subjective sleep or cognitive (e.g., memory impairment) problem.…”

Motor Cortical Network Plasticity in Patients With Recurrent Brain Tumors

“…For clinical factors, tumor location in the right and left, or motordominant and non-dominant hemisphere, could also introduce variability (Volkmann et al, 1998;Jung et al, 2003;Pool et al, 2014), although no influence was observed here and in our previous studies (Nagarajan et al, 2008). Furthermore, aging is associated with changes in motor beta ERD, as well as a decrease in motor cortical plasticity, and might be a source of reorganization itself (Rossiter et al, 2014;Mary et al, 2017;Rueda-Delgado et al, 2019). It is also possible that the biological manifestation of motor cortical network reorganization in our cohorts could arise from a signal to noise difference in network activation, perhaps superimposed upon the effects observed here.…”