Wisniewski Matthew G
U.S. Air Force Research Laboratory, Bldg. 441, Area B, Wright-Patterson Air Force Base, Dayton, OH, USA.
Exp Brain Res. 2017 Apr;235(4):1233-1245. doi: 10.1007/s00221-016-4866-3. Epub 2017 Feb 11.
Discrimination learning can cause improved and worsened ability to perceive differences. This subsequently affects how stimuli are associated with meanings and behaviors. Here, human listeners were trained with frequency-modulated (FM) tonal sweeps (500-1000 Hz) in a paradigm where one FM rate (8.29 octaves per second) required a 'Target' response, while a rate either slower (5.76 octaves per second) or faster (11.94 octaves per second) required a 'Non-Target' response. Training led to a shift in 'Target' responding along the FM rate dimension away from the 'Target' in a direction opposite the trained 'Non-Target'. This peak shift was paralleled by an asymmetry in acuity along the FM rate dimension in an untrained ABX task (a.k.a. match-to-sample). Performance improved relative to pre-training on trials where the 'Target' was contrasted with stimuli nearer the trained 'Non-Target'. Performance worsened on trials containing stimuli displaced along the FM dimension further from the trained 'Non-Target'. A connectionist model of perceptual learning containing non-associative representational modification and associative-based task-specific reweighting was able to simulate behavior. Simulations generated novel testable predictions regarding peak shift and worsening as a result of discrimination learning. Data have theoretical and practical consequences for predicting trends in the generalization of learned behaviors and modifiable perceptual acuities.
辨别学习会导致感知差异的能力提高或降低。这随后会影响刺激如何与意义和行为相关联。在此,人类听众在一种范式中接受了调频(FM)音调扫描(500 - 1000赫兹)训练,其中一种调频速率(每秒8.29个八度)需要做出“目标”反应,而较慢(每秒5.76个八度)或较快(每秒11.94个八度)的速率则需要做出“非目标”反应。训练导致“目标”反应在调频速率维度上发生偏移,朝着与训练的“非目标”相反的方向偏离“目标”。在未训练的ABX任务(也称为匹配样本任务)中,这种峰值偏移与调频速率维度上的敏锐度不对称现象同时出现。与训练前相比,当“目标”与更接近训练的“非目标”的刺激进行对比时,表现有所改善。在包含沿调频维度远离训练的“非目标”的刺激的试验中,表现变差。一个包含非关联表征修改和基于关联的任务特定重新加权的感知学习联结主义模型能够模拟行为。模拟产生了关于辨别学习导致的峰值偏移和变差的新的可测试预测。数据对于预测学习行为和可修改的感知敏锐度的泛化趋势具有理论和实际意义。