Whole-brain dynamics of human sensorimotor adaptation

Abstract

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.

Whole-brain modular dynamics at rest predict sensorimotor learning performance

“…Networks derived at rest differed from those derived during learning. Our derivation of four summary networks from each of the first and second resting scans (Supplementary Materials Figure 2) was conspicuously different from the five networks derived during early learning (26). This difference was especially pronounced in relation to the learning network, which was no more than 20% similar to any network derived from either resting scan (quantified by the Jaccard index).…”

“…Following false discovery rate (FDR) correction over the five networks (see Methods), we found a significant positive correlation between recruitment of the relearning network and PC1 (r = 0.501, p = 0.003, adjusted p = 0.017). This finding was surprising to us, since the relearning network was not associated with participants' behavioural profiles during the task until the second day of the experiment (26). As was the case with Q and modular reconfiguration above, the FF and SS subgroups were significantly different according to this measure (FF recruited the network more strongly than SS) but neither of these subgroups differed statistically from SF (Figure 5A).…”

“…We analysed rs-fMRI data from a study (26) in which participants performed a classic visuomotor rotation (VMR) task (36), controlling a small force sensor with the hand in order to move a cursor to a target that appeared randomly at one of eight locations around an invisible circle. On each of two testing days (separated by 24 hours) participants performed a baseline block, during which motion of the cursor was veridically mapped to motion of the hand, and a learning block, during which the correspondence between hand movement and cursor movement was rotated clockwise by 45 degrees.…”

“…Sensorimotor adaptation (SA) tasks are ideal for investigating individual differences in cognition, since participants show a high degree of variability in their use of cognitive strategies toward these tasks (24)(25)(26). On SA tasks, an established sensorimotor mapping is systematically altered, such as visual feedback of hand motion while reaching, so that participants are required to learn a new mapping for competent task performance.…”

“…We reasoned that if recruitment of these (or other) task-based networks are supportive of task performance [and/or individual differences in performance (26)] then a predisposition toward their composition would be advantageous. Conversely, we reasoned that if their integration is disruptive to task performance (26) then such a predisposition would be disadvantageous. All predictive measures were re-quantified after the task in a second resting scan, enabling us to determine whether participants' intrinsic whole-brain networks were modified by adaptation, as seen with some other tasks and network measures (33)(34)(35).…”