Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these "micro-offline" gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments = 951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N = 389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N = 118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N = 373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N = 71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning

Prefrontal-Premotor Pathways and Motor Output in Well-Recovered Stroke Patients

Structural brain imaging has continuously furthered our knowledge how different pathways of the human motor system contribute to residual motor output in stroke patients. Tract-related microstructure of pathways between primary and premotor areas has been found to critically influence motor output. The motor network is not restricted in connectivity to motor and premotor areas but these brain regions are densely interconnected with prefrontal regions such as the dorsolateral (DLPFC) and ventrolateral (VLPFC) prefrontal cortex. So far, the available data about the topography of such direct pathways and their microstructural properties in humans are sparse. To what extent prefrontal-premotor connections might also relate to residual motor outcome after stroke is still an open question. The present study was designed to address this issue of structural connectivity of prefrontal-premotor pathways in 26 healthy, older participants (66 ± 10 years old, 15 male) and 30 well-recovered chronic stroke patients (64 ± 10 years old, 21 males). Probabilistic tractography was used to reconstruct direct fiber tracts between DLPFC and VLPFC and three premotor areas (dorsal and ventral premotor cortex and the supplementary motor area). Direct connections between DLPFC/VLPFC and the primary motor cortex were also tested. Tract-related microstructure was estimated for each specific tract by means of fractional anisotropy and alternative diffusion metrics. These measures were compared between the groups and related to residual motor outcome in the stroke patients. Direct prefrontal-premotor trajectories were successfully traceable in both groups. Similar in gross anatomic topography, stroke patients presented only marginal microstructural alterations of these tracts, predominantly of the affected hemisphere. However, there was no clear evidence for a significant association between tract-related microstructure of prefrontal-premotor connections and residual motor functions in the present group of well-recovered stroke patients. Direct prefrontal-motor connections between DLPFC/VLPFC and the primary motor cortex could not be reconstructed in the present healthy participants and stroke patients

Generalization of procedural motor sequence learning after a single practice trial

When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge acquired during this early skill learning period generalizes to new, related skills. Here, we addressed this question by investigating factors influencing generalization of early learning from a skill A to a different, but related skill B. Early skill generalization was tested over four experiments (N = 2095). Subjects successively learned two related motor sequence skills (skills A and B) over different practice schedules. Skill A and B sequences shared ordinal (i.e., matching keypress locations), transitional (i.e., ordered keypress pairs), parsing rule (i.e., distinct sequence events like repeated keypresses that can be used as a breakpoint for segmenting the sequence into smaller units) structures, or possessed no structure similarities. Results showed generalization for shared parsing rule structure between skills A and B after only a single 10-second practice trial of skill A. Manipulating the initial practice exposure to skill A (1 to 12 trials) and inter-practice rest interval (0–30 s) between skills A and B had no impact on parsing rule structure generalization. Furthermore, this generalization was not explained by stronger sensorimotor mapping between individual keypress actions and their symbolic representations. In contrast, learning from skill A did not generalize to skill B during early learning when the sequences shared only ordinal or transitional structure features. These results document sequence structure that can be very rapidly generalized during initial learning to facilitate generalization of skill

Sub-millimeter fMRI reveals multiple topographical digit representations that form action maps in human motor cortex

The human brain coordinates a wide variety of motor activities. On a large scale, the cortical motor system is topographically organized such that neighboring body parts are represented by neighboring brain areas. This homunculus-like somatotopic organization along the central sulcus has been observed using neuroimaging for large body parts such as the face, hands and feet. However, on a finer scale, invasive electrical stimulation studies show deviations from this somatotopic organization that suggest an organizing principle based on motor actions rather than body part moved. It has not been clear how the action-map organization principle of the motor cortex in the mesoscopic (sub-millimeter) regime integrates into a body map organization principle on a macroscopic scale (cm). Here we developed and applied advanced mesoscopic (sub-millimeter) fMRI and analysis methodology to non-invasively investigate the functional organization topography across columnar and laminar structures in humans. Compared to previous methods, in this study, we could capture locally specific blood volume changes across entire brain regions along the cortical curvature. We find that individual fingers have multiple mirrored representations in the primary motor cortex depending on the movements they are involved in. We find that individual digits have cortical representations up to 3 ​mm apart from each other arranged in a column-like fashion. These representations are differentially engaged depending on whether the digits’ muscles are used for different motor actions such as flexion movements, like grasping a ball or retraction movements like releasing a ball. This research provides a starting point for non-invasive investigation of mesoscale topography across layers and columns of the human cortex and bridges the gap between invasive electrophysiological investigations and large coverage non-invasive neuroimaging

Prefrontal-Premotor Pathways and Motor Output in Well-Recovered Stroke Patients

Structural brain imaging has continuously furthered our knowledge how different pathways of the human motor system contribute to residual motor output in stroke patients. Tract-related microstructure of pathways between primary and premotor areas has been found to critically influence motor output. The motor network is not restricted in connectivity to motor and premotor areas but these brain regions are densely interconnected with prefrontal regions such as the dorsolateral (DLPFC) and ventrolateral (VLPFC) prefrontal cortex. So far, the available data about the topography of such direct pathways and their microstructural properties in humans are sparse. To what extent prefrontal-premotor connections might also relate to residual motor outcome after stroke is still an open question. The present study was designed to address this issue of structural connectivity of prefrontal-premotor pathways in 26 healthy, older participants (66 ± 10 years old, 15 male) and 30 well-recovered chronic stroke patients (64 ± 10 years old, 21 males). Probabilistic tractography was used to reconstruct direct fiber tracts between DLPFC and VLPFC and three premotor areas (dorsal and ventral premotor cortex and the supplementary motor area). Direct connections between DLPFC/VLPFC and the primary motor cortex were also tested. Tract-related microstructure was estimated for each specific tract by means of fractional anisotropy and alternative diffusion metrics. These measures were compared between the groups and related to residual motor outcome in the stroke patients. Direct prefrontal-premotor trajectories were successfully traceable in both groups. Similar in gross anatomic topography, stroke patients presented only marginal microstructural alterations of these tracts, predominantly of the affected hemisphere. However, there was no clear evidence for a significant association between tract-related microstructure of prefrontal-premotor connections and residual motor functions in the present group of well-recovered stroke patients. Direct prefrontal-motor connections between DLPFC/VLPFC and the primary motor cortex could not be reconstructed in the present healthy participants and stroke patients

Dynamic causal modelling of EEG and fMRI to characterize network architectures in a simple motor task

Dynamic causal modelling (DCM) has extended the understanding of brain network dynamics in a variety of functional systems. In the motor system, DCM studies based on functional magnetic resonance imaging (fMRI) or on magneto-/electroencephalography (M/EEG) have demonstrated movement-related causal information flow from secondary to primary motor areas and have provided evidence for nonlinear cross-frequency interactions among motor areas. The present study sought to investigate to what extent fMRI- and EEG-based DCM might provide complementary and synergistic insights into neuronal network dynamics. Both modalities share principal similarities in the formulation of the DCM. Thus, we hypothesized that DCM based on induced EEG responses (DCM-IR) and on fMRI would reveal congruent task-dependent network dynamics. Brain electrical (63-channel surface EEG) and Blood Oxygenation Level Dependent (BOLD) signals were recorded in separate sessions from 14 healthy participants performing simple isometric right and left hand grips. DCM-IR and DCM-fMRI were used to estimate coupling parameters modulated by right and left hand grips within a core motor network of six regions comprising bilateral primary motor cortex (M1), ventral premotor cortex (PMv) and supplementary motor area (SMA). We found that DCM-fMRI and DCM-IR similarly revealed significant grip-related increases in facilitatory coupling between SMA and M1 contralateral to the active hand. A grip-dependent interhemispheric reciprocal inhibition between M1 bilaterally was only revealed by DCM-fMRI but not by DCM-IR. Frequency-resolved coupling analysis showed that the information flow from contralateral SMA to M1 was predominantly a linear alpha-to-alpha (9-13Hz) interaction. We also detected some cross-frequency coupling from SMA to contralateral M1, i.e., between lower beta (14-21Hz) at the SMA and higher beta (22-30Hz) at M1 during right hand grip and between alpha (9-13Hz) at SMA and lower beta (14-21Hz) at M1 during left hand grip. In conclusion, the strategy of informing EEG source-space configurations with fMRI-derived coordinates, cross-validating basic connectivity maps and analysing frequency coding allows for deeper insight into the motor network architecture of the human brain. The present results provide evidence for the robustness of non-invasively measured causal information flow from secondary motor areas such as SMA towards M1 and further contribute to the validation of the methodological approach of multimodal DCM to explore human network dynamics

Consolidation of human skill linked to waking hippocampo-neocortical replay

International audienceHighlights d Waking replay bursts occur during short rest periods interspersed with practice d Replay is temporally compressed by approximately 20-fold relative to the practiced skill d Replay activity is distributed across the hippocampus and neocortex d Replay rates correlate with rapid wakeful skill consolidation in individual

Parietofrontal network upregulation after motor stroke

Objective: Motor recovery after stroke shows a high inter-subject variability. The brain's potential to form new connections determines individual levels of recovery of motor function. Most of our daily activities require visuomotor integration, which engages parietal areas. Compared to the frontal motor system, less is known about the parietal motor system's reconfiguration related to stroke recovery. Here, we tested if functional connectivity among parietal and frontal motor areas undergoes plastic changes after stroke and assessed the behavioral relevance for motor function after stroke. Methods: We investigated stroke lesion-induced changes in functional connectivity by measuring high-density electroencephalography (EEG) and assessing task-related changes in coherence during a visually guided grip task with the paretic hand in 30 chronic stroke patients with variable motor deficits and 19 healthy control subjects. Quantitative changes in task-related coherence in sensorimotor rhythms were compared to the residual motor deficit. Results: Parietofrontal coupling was significantly stronger in patients compared to controls. Whereas motor network coupling generally increased during the task in both groups, the task-related coherence between the parietal and primary motor cortex in the stroke lesioned hemisphere showed increased connectivity across a broad range of sensorimotor rhythms. Particularly the parietofrontal task-induced coupling pattern was significantly and positively related to residual impairment in the Nine-Hole Peg Test performance and grip force. Interpretation: These results demonstrate that parietofrontal motor system integration during visually guided movements is stronger in the stroke-lesioned brain. The correlation with the residual motor deficit could either indicate an unspecific marker of motor network damage or it might indicate that upregulated parietofrontal connectivity has some impact on post-stroke motor function. Keywords: EEG, Coherence, Motor recovery, Stroke, Parietal lob