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Neural signatures of reward and sensory error feedback processing in motor learning

机译:电机学习中奖励与感官误差反馈处理的神经签名

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At least two distinct processes have been identified by which motor commands are adapted according to movement-related feedback: reward-based learning and sensory error-based learning. In sensory error-based learning, mappings between sensory targets and motor commands are recalibrated according to sensory error feedback. In reward-based learning, motor commands are associated with subjective value, such that successful actions are reinforced. We designed two tasks to isolate reward- and sensory error-based motor adaptation, and we used electroencephalography in humans to identify and dissociate the neural correlates of reward and sensory error feedback processing. We designed a visuomotor rotation task to isolate sensory error-based learning that was induced by altered visual feedback of hand position. In a reward learning task, we isolated reward-based learning induced by binary reward feedback that was decoupled from the visual target. A fronto-central event-related potential called the feedback-related negativity (FRN) was elicited specifically by binary reward feedback but not sensory error feedback. A more posterior component called the P300 was evoked by feedback in both tasks. In the visuomotor rotation task, P300 amplitude was increased by sensory error induced by perturbed visual feedback and was correlated with learning rate. In the reward learning task, P300 amplitude was increased by reward relative to nonreward and by surprise regardless of feedback valence. We propose that during motor adaptation the FRN specifically reflects a reward-based learning signal whereas the P300 reflects feedback processing that is related to adaptation more generally.
机译:已经识别了至少两个不同的过程,通过该过程通过该方法根据运动相关的反馈来调整,基于奖励的学习和基于感官的学习。在基于感官误差的学习中,根据感官误差反馈重新校准感觉目标和电机命令之间的映射。在基于奖励的学习中,电机命令与主观值相关联,使得成功的操作被加强。我们设计了两个任务来隔离奖励和感官基于误差的电机适应,我们在人类中使用脑电图来识别和解散奖励和感官误差反馈处理的神经相关性。我们设计了一个visuomotor旋转任务,以隔离通过改变手势的视觉反馈而引起的基于感官误差的学习。在奖励学习任务中,我们孤立基于奖励的学习,由二进制奖励反馈从视觉目标解耦了。通过二进制奖励反馈特别引出称为与反馈相关的消极性(FRN)的传统事件相关的潜力,但不是感觉误差反馈。通过两个任务中的反馈引发了称为P300的更短的部件。在Visuomotor旋转任务中,通过扰动的视觉反馈引起的感觉误差增加了P300振幅,并与学习率相关。在奖励学习任务中,无论反馈价如何,P300幅度通过奖励增加,无论反馈价值如何,都会增加。我们提出在电动机适应期间,FRN专门地反映了基于奖励的学习信号,而P300则反映与适配相关的反馈处理。

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