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• Strong beta suppression in diplegic cerebral palsy (CP) can reflect hyperexcitation/activation of the primary sensorimotor (SM1) cortex contralateral to the stimulation. • Weak beta rebound in the ipsilateral SM1 cortex may indicate broadly impaired control of cortical inhibition in diplegic CP. • Strong ipsilateral rebound in controls may reflect the importance of interhemispheric inhibitory regulation in fine-motor actions. Our objective was to clarify the primary sensorimotor (SM1) cortex excitatory and inhibitory alterations in hemiplegic (HP) and diplegic (DP) cerebral palsy (CP) by quantifying SM1 cortex beta power suppression and rebound with magnetoencephalography (MEG). MEG was recorded from 16 HP and 12 DP adolescents, and their 32 healthy controls during proprioceptive stimulation of the index fingers evoked by a movement actuator. The related beta power changes were computed with Temporal Spectral Evolution (TSE). Peak strengths of beta suppression and rebound were determined from representative channels over the SM1 cortex. Beta suppression was stronger contralateral to the stimulus and rebound was weaker ipsilateral to the stimulation in DP compared to controls. Beta modulation strengths did not differ significantly between HP and the control group. The emphasized beta suppression in DP suggests less efficient proprioceptive processing in the SM1 contralateral to the stimulation. Their weak rebound further indicates reduced intra- and/or interhemispheric cortical inhibition, which is a potential neuronal mechanism for their bilateral motor impairments. The excitation-inhibition balance of the SM1 cortex related to proprioception is impaired in diplegic CP. Therefore, the cortical and behavioral proprioceptive deficits should be better diagnosed and considered to better target individualized effective rehabilitation in CP. [ABSTRACT FROM AUTHOR]

Objective The balance between action and reward during neurofeedback may influence reinforcement learning of brain self-regulation. Methods Eleven healthy volunteers participated in three runs of motor imagery-based brain–machine interface feedback where a robot passively opened the hand contingent to β-band modulation. For each run, the β-desynchronization threshold to initiate the hand robot movement increased in difficulty (low, moderate, and demanding). In this context, the incentive to learn was estimated by the change of reward per action, operationalized as the change in reward duration per movement onset. Results Variance analysis revealed a significant interaction between threshold difficulty and the relationship between reward duration and number of movement onsets ( p < 0.001), indicating a negative learning incentive for low difficulty, but a positive learning incentive for moderate and demanding runs. Exploration of different thresholds in the same data set indicated that the learning incentive peaked at higher thresholds than the threshold which resulted in maximum classification accuracy. Conclusion Specificity is more important than sensitivity of neurofeedback for reinforcement learning of brain self-regulation. Significance Learning efficiency requires adequate challenge by neurofeedback interventions. [ABSTRACT FROM AUTHOR]