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Perceptual learning in clear displays optimizes perceptual expertise: Learning the limiting process

机译:清晰显示中的感知学习可优化感知专业知识:学习限制过程

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摘要

Human operators develop expertise in perceptual tasks by practice or perceptual learning. For noisy displays, practice improves performance by learned external-noise filtering. For clear displays, practice improves performance by improved amplification or enhancement of the stimulus. Can these two mechanisms of perceptual improvement be trained separately? In an orientation task, we found that training with clear displays generalized to performance in noisy displays, but we did not find the reverse to be true. In noisy displays, the noise in the stimulus limits performance. In clear displays, performance is limited by noisiness of internal representations and processes. Our results suggest that training in one display condition optimizes the limiting factor(s) in performance in that condition and that noise filtering is also improved by exposure to the stimulus in clear displays. The asymmetric pattern of transfer implies the existence of two independent mechanisms of perceptual learning, which may reflect channel reweighting in adult visual system. These results also suggest that training operators with clear stimuli may suffice to improve performance in a range of clear and noisy environments by simultaneous learning by two mechanisms.
机译:操作员通过练习或知觉学习来发展有关知觉任务的专业知识。对于嘈杂的显示器,实践可通过学习外部噪声过滤来提高性能。对于清晰的显示器,实践可通过改进刺激的放大或增强来提高性能。这两种感知改善的机制是否可以分别进行训练?在迎新任务中,我们发现使用清晰的显示屏进行的训练通常可以提高在嘈杂的显示屏中的表现,但我们发现并非如此。在嘈杂的显示器中,刺激中的噪声会限制性能。在清晰的显示器中,性能受到内部表示和流程的嘈杂的限制。我们的结果表明,在一种显示条件下进行训练可以优化该条件下性能的限制因素,并且通过暴露于清晰显示中的刺激也可以改善噪声过滤。转移的不对称模式意味着存在两种独立的知觉学习机制,这可能反映了成人视觉系统中的通道权重。这些结果还表明,通过两种机制同时学习,训练具有清晰刺激的操作员可能足以在一系列清晰和嘈杂的环境中提高性能。

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