Individual differences in error-related frontal midline theta activity during visuomotor adaptation

Frontal midline theta power accounts for inter-individual differences in motor learning ability

Recent neurophysiological studies have demonstrated that frontal midline theta (FMT) activity plays a significant role in motor learning. One of the key challenges in motor learning is to understand the interindividual variability in learning proficiency rates, yet the underlying neural mechanisms remain unclear. To address this open question, this study recorded electroencephalogram activity from twenty-one healthy participants during a visuomotor tracking task to investigate whether modulation of FMT power and the theta phase synchronization across trials (theta phase consistency) during motor preparation could explain individual differences in learning proficiency. We found a significant positive correlation between increased FMT power during motor preparation and learning proficiency rates. Specifically, individuals with greater FMT power exhibited faster learning rates. In contrast, no significant correlation was observed between the consistency of the theta phase during motor preparation and learning proficiency. Together, these findings highlight that the FMT power, rather than phase synchrony, is closely associated with motor learning efficiency. This study provides a novel perspective for understanding the causes of individual differences in motor learning and further corroborates the previous evidence showing FMT power contributes to motor learning processes.

Dorsomedial frontal cortex damage impairs error-based, but not reinforcement-based motor learning in humans

We adapt our movements to new and changing environments through multiple processes. Sensory error-based learning counteracts environmental perturbations that affect the sensory consequences of movements. Sensory errors also cause the upregulation of reflexes and muscle co-contraction. Reinforcement-based learning enhances the selection of movements that produce rewarding outcomes. Although some findings have identified dissociable neural substrates of sensory error- and reinforcement-based learning, correlative methods have implicated dorsomedial frontal cortex in both. Here, we tested the causal contributions of dorsomedial frontal to adaptive motor control, studying people with chronic damage to this region. Seven human participants with focal brain lesions affecting the dorsomedial frontal and 20 controls performed a battery of arm movement tasks. Three experiments tested: (i) the upregulation of visuomotor reflexes and muscle co-contraction in response to unpredictable mechanical perturbations, (ii) sensory error-based learning in which participants learned to compensate predictively for mechanical force-field perturbations, and (iii) reinforcement-based motor learning based on binary feedback in the absence of sensory error feedback. Participants with dorsomedial frontal damage were impaired in the early stages of force field adaptation, but performed similarly to controls in all other measures. These results provide evidence for a specific and selective causal role for the dorsomedial frontal in sensory error-based learning.

Using EEG to study sensorimotor adaptation

Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.