Institute for Cognitive Neuroscience, Department of Biopsychology, Ruhr-Universität Bochum, Universitätsstrasse 150, D-44780 Bochum, Germany.
Curr Biol. 2013 Jun 3;23(11):R489-99. doi: 10.1016/j.cub.2013.04.044.
Achieving high-level skills is generally considered to require intense training, which is thought to optimally engage neuronal plasticity mechanisms. Recent work, however, suggests that intensive training may not be necessary for skill learning. Skills can be effectively acquired by a complementary approach in which the learning occurs in response to mere exposure to repetitive sensory stimulation. Such training-independent sensory learning induces lasting changes in perception and goal-directed behaviour in humans, without any explicit task training. We suggest that the effectiveness of this form of learning in different sensory domains stems from the fact that the stimulation protocols used are optimized to alter synaptic transmission and efficacy. While this approach directly links behavioural research in humans with studies on cellular plasticity, other approaches show that learning can occur even in the absence of an actual stimulus. These include learning through imagery or feedback-induced cortical activation, resulting in learning without task training. All these approaches challenge our understanding of the mechanisms that mediate learning. Apparently, humans can learn under conditions thought to be impossible a few years ago. Although the underlying mechanisms are far from being understood, training-independent sensory learning opens novel possibilities for applications aimed at augmenting human cognition.
高水平技能的获得通常被认为需要高强度的训练,因为这种训练被认为能够最大限度地激发神经元的可塑性机制。然而,最近的研究表明,技能的学习并不一定需要高强度的训练。通过一种互补的方法,即仅仅通过重复的感官刺激来学习,也可以有效地获得技能。这种无需训练的感官学习可以在人类中引起感知和目标导向行为的持久变化,而无需进行任何明确的任务训练。我们认为,这种学习形式在不同感官领域的有效性源于这样一个事实,即使用的刺激方案经过优化,可以改变突触传递和效能。虽然这种方法将人类行为研究与细胞可塑性研究直接联系起来,但其他方法表明,即使没有实际刺激,学习也可以发生。这些方法包括通过意象或反馈引起的皮层激活进行学习,从而在没有任务训练的情况下进行学习。所有这些方法都挑战了我们对介导学习的机制的理解。显然,人类可以在几年前被认为不可能的条件下学习。尽管潜在的机制还远未被理解,但无需训练的感官学习为旨在增强人类认知的应用开辟了新的可能性。