bioRxiv Science⌕ Search

bioRxiv · 10.64898/2025.12.11.693740

EEG Dynamics of Movement Preparation and Error Processing Distinguish Motor Adaptation From De Novo Learning

Abstract

Previous research has distinguished behavioral mechanisms between motor adaptation and de novo learning. However, electroencephalography (EEG) markers dissociating them remain unclear. Here, participants (N = 32, 13 female) performed center-out reaching under a 30{degrees} fixed rotation (adaptation), mirror reversal (de novo learning), or random rotation (errors without learning), while we recorded EEG during movement preparation and post-movement feedback. We explored how perturbation type, training phase, and error magnitude shaped neural dynamics in both temporal and frequency domains. During preparation, the readiness potential (RP) showed opposite training-related modulation in the fixed and random rotations, suggesting increased reliance on updated internal models for adaptation. Mirror reversal training showed no RP change, likely reflecting reliance on effortful, explicit learning. Interestingly, we found that Lateralized Readiness Potentials (LRPs) reflected planned movement direction rather than effector-specific preparation. In the frequency domain, beta attenuation for large errors and alpha synchronization for small errors were more pronounced in the fixed rotation than in the mirror reversal, suggesting greater error-sensitivity during adaptation. During post-movement feedback, P3 amplitude decreased from early to late learning in the fixed and random rotations but remained stable in the mirror reversal, highlighting differences in cognitive demands across perturbations. A sustained late positivity emerged following small errors across perturbations, potentially indexing implicit learning. Random rotations also elicited distinct frontal and central beta modulation, likely reflecting disengagement due to task unpredictability. Together, we show that preparatory and feedback-related EEG signatures differ across perturbation types, revealing distinct neural mechanisms underlying motor adaptation and de novo learning. Significance statementUnderstanding how the brain supports skill acquisition and adaptation is critical for advancing theories and applications of motor learning. Although behavioral differences between motor adaptation and de novo learning are well established, the neural processes that distinguish them remain unclear. By comparing EEG activity during movement preparation and feedback-error processing across multiple perturbation types, we uncover distinct temporal and frequency domain signatures that uniquely characterize each learning process. Our findings show that adaptation engages neural dynamics consistent with updating internal models and error-processing, whereas de novo learning relies on explicit, cognitively demanding strategies that likely unfold over extended practice. These results provide a clear neural framework for distinguishing motor learning mechanisms.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gastrock, R. Q., Henriques, D. Y. P., 't Hart, B. M.. 2025-12-15. EEG Dynamics of Movement Preparation and Error Processing Distinguish Motor Adaptation From De Novo Learning. https://doi.org/10.64898/2025.12.11.693740

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A Mechanistic Account of Dedifferentiation in the Aging Visual System

To uncover the mechanisms of age-related dedifferentiation, we simulated neural degradation in a computational model of the ventral visual stream. Severing connections or adding noise, whether in inferotemporal cortex (IT) or upstream, reduced IT differentiation, indicating that dedifferentiation need not originate locally. Degrading peripheral V1, which preferentially drove place-selective IT neurons, selectively reduced place differentiation, a candidate mechanism for the stronger place dedifferentiation reported in aging.

neuroscience↗

Reusing pipettes in Patch-seq: a foundation for automated multimodal profiling

Patch-seq is a technique for single-cell multimodal characterization. It combines whole-cell electrophysiology, single-cell transcriptomics, and morphological reconstruction in single neurons. Patch-seq morphologies are a critical bridge among cell types, genes, physiology, and large-scale connectivity platforms such as EM connectomes and single-cell-resolution projectomes. However, patch-seq experimental complexity and operator dependence limit throughput. Automation could enable scalable Patch-seq but requires procedural adaptations, including detergent-based pipette cleaning, robotic nucleus extraction and collection. The impact of these automations on Patch-seq quality has not been systematically evaluated. Here, we show that each of these modifications preserves or improves key Patch-seq outcomes. Automated nucleus extraction performs comparably to, or better than, expert manual operation, preserving key RNA and morphological metrics. Detergent-cleaned, reused pipettes supported a viable sealing success rate across multiple cleaning cycles and preserved electrophysiological quality and transcriptomic yield without introducing excess contamination. Sonication effectively allows collection of nuclear material without damaging RNA and supports subsequent pipette cleaning and reuse. Enhanced automated sealing and break-in procedures increased throughput regardless of brain region, cell type or species. Together, these results validate the core procedural adaptations required for automated Patch-seq and establish a foundation for high-throughput, standardized multimodal single-cell characterization.

neuroscience↗

Development of direction selectivity in the Xenopus tadpole optic tectum and midbrain tegmentum

Detecting motion direction is a fundamental function performed by direction selective (DS) neurons. DS neurons in the optic tectum (superior colliculus in mammals) enable the tracking of moving objects. DS neurons of the accessory optic system support reflexive eye / head movements that stabilize gaze during self-motion. By developmental stage 48 (10 days postfertilization), Xenopus tadpoles display visually guided behaviors that require both types of DS neurons. Our previous work has shown that these two regions are not only functionally distinct but also follow different developmental programs. Here we characterized and compared how direction selectivity develops in both visual processing centers. Using in vivo electrophysiological recordings during moving bar visual stimulation, we measured DS synaptic inputs and spiking outputs in both regions across three key developmental stages of the retinotectal projection. Tegmental neurons were direction selective ab initio, and both input and output tuning remained stable across development. Tectal neurons were observed to receive DS inputs early, and their input selectivity also remained stable across development. However, their spiking output grew substantially more DS at the later developmental stage. This was due at least in part to a naturally occurring decrease in intrinsic excitability which preferentially dampened overall spike rates, but especially in response to the non-preferred direction of motion, thereby increasing direction selectivity. These results reveal distinct developmental trajectories in parallel visual pathways. Tegmental direction selectivity is established early and stays stable, whereas tectal output tuning sharpens during development through a decrease in intrinsic excitability.

neuroscience↗