Reactivation-induced motor skill learning.

Learning motor skills commonly requires repeated execution to achieve gains in performance. Motivated by memory reactivation frameworks predominantly originating from fear-conditioning studies in rodents, which have extended to humans, we asked the following: Could motor skill learning be achieved by brief memory reactivations? To address this question, we had participants encode a motor sequence task in an initial test session, followed by brief task reactivations of only 30 s each, conducted on separate days. Learning was evaluated in a final retest session. The results showed that these brief reactivations induced significant motor skill learning gains. Nevertheless, the efficacy of reactivations was not consistent but determined by the number of consecutive correct sequences tapped during memory reactivations. Highly continuous reactivations resulted in higher learning gains, similar to those induced by full extensive practice, while lower continuity reactivations resulted in minimal learning gains. These results were replicated in a new independent sample of subjects, suggesting that the quality of memory reactivation, reflected by its continuity, regulates the magnitude of learning gains. In addition, the change in noninvasive brain stimulation measurements of corticospinal excitability evoked by transcranial magnetic stimulation over primary motor cortex between pre- and postlearning correlated with retest and transfer performance. These results demonstrate a unique form of rapid motor skill learning and may have far-reaching implications, for example, in accelerating motor rehabilitation following neurological injuries.

Neuromodulation of reinforced skill learning reveals the causal function of prefrontal cortex.

Accumulating evidence has suggested functional interactions between prefrontal cortex (PFC) and dissociable large-scale networks. However, how these networks interact in the human brain to enable complex behaviors is not well-understood. Here, using a combination of behavioral, brain stimulation and neuroimaging paradigms, we tested the hypothesis that human PFC is required for successful reinforced skill formation. We additionally tested the extent to which PFC-dependent skill formation is related to intrinsic functional communication with this region. We report that inhibitory noninvasive transcranial magnetic stimulation over lateral PFC, a hub region with a diverse connectivity profile, causally modulated effective reinforcement-based motor skill acquisition. Furthermore, PFC-dependent skill formation was strongly related to the strength of functional connectivity between the PFC and regions in the sensorimotor network. These results point to the involvement of lateral PFC in the neural architecture that underlies the acquisition of complex skills, and suggest that, in relation to skill acquisition, this region may be involved in functional interactions with sensorimotor networks.

Reactivation-induced motor skill modulation does not operate at a rapid micro-timescale level.

Abundant evidence shows that consolidated memories are susceptible to modifications following their reactivation. Processes of memory consolidation and reactivation-induced skill modulation have been commonly documented after hours or days. Motivated by studies showing rapid consolidation in early stages of motor skill acquisition, here we asked whether motor skill memories are susceptible to modifications following brief reactivations, even at initial stages of learning. In a set of experiments, we collected crowdsourced online motor sequence data to test whether post-encoding interference and performance enhancement occur following brief reactivations in early stages of learning. Results indicate that memories forming during early learning are not susceptible to interference nor to enhancement within a rapid reactivation-induced time window, relative to control conditions. This set of evidence suggests that reactivation-induced motor skill memory modulation might be dependent on consolidation at the macro-timescale level, requiring hours or days to occur.

Initial motor skill performance predicts future performance, but not learning.

People show vast variability in skill performance and learning. What determines a person's individual performance and learning ability? In this study we explored the possibility to predict participants' future performance and learning, based on their behavior during initial skill acquisition. We recruited a large online multi-session sample of participants performing a sequential tapping skill learning task. We used machine learning to predict future performance and learning from raw data acquired during initial skill acquisition, and from engineered features calculated from the raw data. Strong correlations were observed between initial and final performance, and individual learning was not predicted. While canonical experimental tasks developed and selected to detect average effects may constrain insights regarding individual variability, development of novel tasks may shed light on the underlying mechanism of individual skill learning, relevant for real-life scenarios.

Inhibition of the supplementary motor area affects distribution of effort over time.

In tasks that extend over time, people tend to exert much effort at the beginning and the end, but not in the middle, exhibiting the stuck-in-the-middle pattern (STIM). To date, little is known about the neural mechanisms underlying this effect. As the supplementary motor area (SMA) was previously implicated in coding prospective task-demands, we tested its role in producing the STIM pattern. Participants first underwent an SMA-localization session in which they tapped their fingers repeatedly while fMRI-scanned. In the next two sessions, before playing a 10-min computer game that measured effort-engagement, participants underwent inhibitory 1-Hz repetitive transcranial magnetic stimulation over the SMA, or over a control precuneus location. Three control experiments and a pretest confirmed that this task yields a STIM, which can be eliminated when the task lacks a salient end-point, or is too short. The results of the main experiment showed a more pronounced STIM following inhibitory SMA stimulation compared to control. A control analysis showed that overall level of effort was similar in both conditions, rendering alternative accounts in terms of motor inhibition unlikely. These findings are consistent with the possibility that the SMA may play a role in moment-to-moment coding of effort value, or in related sub-processes, which can cause effort to be distributed more equally over the course of a task.

Explaining Individual Differences in Motor Behavior by Intrinsic Functional Connectivity and Corticospinal Excitability.

Motor performance varies substantially between individuals. This variance is rooted in individuals' innate motor abilities, and should thus have a neural signature underlying these differences in behavior. Could these individual differences be detectable with neural measurements acquired at rest? Here, we tested the hypothesis that motor performance can be predicted by resting motor-system functional connectivity and motor-evoked-potentials (MEPs) induced by non-invasive brain stimulation. Twenty healthy right handed subjects performed structural and resting-state fMRI scans. On a separate day, MEPs were measured using transcranial magnetic stimulation (TMS) over the contrateral primary motor cortex (M1). At the end of the session, participants performed a finger-tapping task using their left non-dominant hand. Resting-state functional connectivity between the contralateral M1 and the supplementary motor area (SMA) predicted motor task performance, indicating that individuals with stronger resting M1-SMA functional connectivity exhibit better motor performance. This prediction was neither improved nor reduced by the addition of corticospinal excitability to the model. These results confirm that motor behavior can be predicted from neural measurements acquired prior to task performance, primarily relying on resting functional connectivity rather than corticospinal excitability. The ability to predict motor performance from resting neural markers, provides an opportunity to identify the extent of successful rehabilitation following neurological damage.

Modulation of Learning and Memory: A Shared Framework for Interference and Generalization.

The human brain is known by its ability to modify and update existing memories, mediated by underlying neuronal plasticity. This ability is facilitated by two main phenomena, interference and generalization. Interference occurs when a new memory harms, or is being harmed by, a different memory that was acquired in temporal proximity to it. Generalization on the other hand, refers to the case in which a learned memory is expanded beyond its specific properties. While each of these two phenomena may be well known separately, we review recent evidence primarily in perceptual and motor skill memory, spanning synaptic, neural systems-level, and behavioral research, suggesting that although the outcomes are different, the underlying neural and behavioral processes responsible for their inducements share numerous commonalities. The reviewed literature may imply a common mechanism underlying these two phenomena, and suggests a unified framework of memory and learning in the human brain.

Consolidation of complex motor skill learning: evidence for a delayed offline process.

Following initial acquisition, studies across domains have shown that memories stabilize through consolidation processes, requiring a post-acquisition temporal interval to allow their occurrence. In procedural skill memories, consolidation not only stabilizes the memory, but also simultaneously enhances it by accumulating additional gains in performance. In addition, explicit skill tasks were previously shown to consolidate through sleep, whereas implicit tasks were consolidated following a time interval which did not include a period of sleep. Although previous research has been instrumental in utilizing simple motor tasks designed to model skill learning, whether and how skill consolidation processes operate in complex real-life environments remains to be determined. Here, we tested consolidation in a complex motor skill, used to train execution of fine-motor movements. Since the complex task was explicit, we hypothesized that consolidation will be evident immediately following sleep, as in simple explicit motor skills. However, results show that even though participants were aware of the goal of the complex skill task, consolidation was evident only 24 hr following skill acquisition, and not following a shorter 12 hr interval, even when the latter included sleep. An additional experiment verified that without a temporal interval longer than 12hr, the same skill training does not undergo complete consolidation. These results suggest that task complexity is a crucial characteristic determining the proper terms allowing full consolidation. Due to the enhanced ecological validity of this study, revealing the differences between complex and simple motor skills could enable the facilitation of advanced rehabilitation methods following neurological injuries.

Memory Reactivation Enables Long-Term Prevention of Interference.

The ability of the human brain to successively learn or perform two competing tasks constitutes a major challenge in daily function. Indeed, exposing the brain to two different competing memories within a short temporal offset can induce interference, resulting in deteriorated performance in at least one of the learned memories [1-4]. Although previous studies have investigated online interference and its effects on performance [5-13], whether the human brain can enable long-term prevention of future interference is unknown. To address this question, we utilized the memory reactivation-reconsolidation framework [2, 12] stemming from studies at the synaptic level [14-17], according to which reactivation of a memory enables its update. In a set of experiments, using the motor sequence learning task [18] we report that a unique pairing of reactivating the original memory (right hand) in synchrony with novel memory trials (left hand) prevented future interference between the two memories. Strikingly, these effects were long-term and observed a month following reactivation. Further experiments showed that preventing future interference was not due to practice per se, but rather specifically depended on a limited time window induced by reactivation of the original memory. These results suggest a mechanism according to which memory reactivation enables long-term prevention of interference, possibly by creating an updated memory trace integrating original and novel memories during the reconsolidation time window. The opportunity to induce a long-term preventive effect on memories may enable the utilization of strategies optimizing normal human learning, as well as recovery following neurological insults.