Motor Control and Adaptation

The paper shows that granule cell signaling is essential for motor learning but not for many cerebellar-dependent behaviors, while Purkinje cell signaling affects both motor learning and other behaviors.

The paper investigates how task goals influence the relationship between decision and movement speed, finding that coregulation occurs as a default but is replaced by a tradeoff when detrimental to reward rate.

This paper models locomotor adaptation as interactions between a stabilizing controller and a reinforcement learner, predicting adaptation in various scenarios and capturing learning phenomena.

The paper investigates visuomotor adaptation in rhesus monkeys using a BCI, finding that frontal and parietal cortices adapt to movement-contingent visual feedback, with stronger transfer of planning activity to movement corrections in the frontal cortex.

The paper introduces a closed-loop neurofeedback and movement feedback system for mice, showing improved performance and adaptation to rule changes in both neural activity and movement tasks.

The paper uses force monitoring in a stop signal task to show that higher initial force delays movement generation and aids inhibition.

The paper identifies thalamic neurons that integrate signals from the basal ganglia and cerebellum during motor learning and shows their critical role in motor task execution.

This paper develops MOMM to map motor movement representations of multiple limbs in awake mice and finds cortical topographies for coordinated movements.

This paper introduces a 15-second smartphone-based motor skill assessment that quantifies movement variability, revealing age-related changes and practice effects in hand and foot motor skills.

The paper examines how participants manage gaze competition during object manipulation and environmental monitoring tasks, showing they prioritize sensorimotor control and adjust timing based on event statistics.

The paper investigates how motor compensation, not sensory error, drives serial learning in speech production through experimental designs and behavioral analysis.

The paper compares motor control and learning by analyzing how participants adjust movement velocity and duration during self-paced tasks and visuomotor perturbations, finding distinct optimization strategies.

The paper tests a Bayesian model of arm posture perception using a VR task, finding that a Gaussian prior better explains individual biases than a uniform prior.

The paper investigates the pause-then-cancel model of action-stopping by measuring motor system physiology during action-stopping, finding evidence for both Pause and Cancel processes.

This study shows that new motor skills can be learned by reusing existing motor commands rather than generating new ones, using a myoelectric interface task with muscle activation.

This study investigates how cerebellar climbing fibers respond to reward-predictive stimuli and finds they generate flexible, context-sensitive reward prediction signals.

This study uses high-density EEG to analyze perceptual, attentional, and working memory processes during motor learning with random vs. blocked practice schedules.

This study identifies a dissociation between short-term and long-term sensorimotor memory in individuals with cerebellar degeneration, revealing the cerebellum's role as a gateway for long-term memory formation.

The paper investigates how protein synthesis in the primary motor cortex contributes to the consolidation of sequential movement learning in non-human primates.

This study shows that posture affects motor maps in marmoset monkeys' primary motor cortex, with hindlimb posture having a strong influence, while body angle does not.

This study investigates how the timing of contextual movements affects motor memory formation and generalization in bimanual tasks, finding distinct temporal generalization patterns based on the timing of contextual cues.

The paper identifies evolving point attractors in the M2 cortex during motor learning, showing how they reduce behavioral variation through training.

The paper investigates dynamic lateralization in contralateral-projecting corticospinal neurons during motor learning in mice, finding heterogeneous activity changes and flexible network reconfiguration.

This paper uses curriculum-based reinforcement learning to train a neural network to control a musculoskeletal hand model, revealing insights into motor control and synergy analysis.

The paper introduces a kinematic deviation index (KDI) to assess forelimb function in rodents, demonstrating its ability to detect movement differences and response to interventions.

The paper investigates how humans prefer to invest physical effort over time in an isometric task and finds that effort is preferred earlier, supported by a subjective utility model.

This study investigates why motor preparation occurs in RNN models of motor control and finds that optimal input-driven control leads to multiple phases of preparation during reach sequences.

This study shows that sequence production can be either separate or coarticulated based on task-dependent control, validated through simulations and human experiments.

This study investigates the functional differences between direct corticomotoneuronal and indirect corticospinal pathways in primate hand movement control during a precision grip task.

The paper maps human motor cortex using microelectrode recordings, finding whole-body representations and challenging the traditional motor homunculus model.