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学习的节奏:婴儿期的 theta 振荡作为主动学习的指标。

The rhythm of learning: Theta oscillations as an index of active learning in infancy.

机构信息

Rutgers University - Newark, Newark, New Jersey, USA.

Rutgers University - Newark, Newark, New Jersey, USA.

出版信息

Dev Cogn Neurosci. 2020 Oct;45:100810. doi: 10.1016/j.dcn.2020.100810. Epub 2020 Jun 30.

Abstract

Active learning is a critical component of human development, however, the mechanisms supporting it are not fully understood. Given that early learning experiences may affect both infants' immediate learning success, as well as their motivation to learn, it is particularly important to investigate the mechanisms of active learning in this period, when the foundations of learning habits and curiosity are built. Traditional behavioural approaches of studying infant learning face challenges that emerging tools from neuroscience may help relieve. We introduce one such tool, EEG theta oscillations, and propose this neural marker has great potential for offering novel insights into active learning. Theta activity, recorded prior to or during learning, has been shown to be predictive of learning success. We argue that this involvement in memory formation, combined with theta activity's tight association with reward processing, makes theta oscillations a uniquely suited tool for the investigation of motivational mechanisms underlying active learning. We outline research questions as well as methodological approaches pertinent to infant learning and suggest how and why theta oscillations may offer complementary insights. As such, we aim to bridge the gap between cognitive and neural approaches, and advance our knowledge of active learning in development more broadly.

摘要

主动学习是人类发展的关键组成部分,但支持它的机制尚未完全理解。鉴于早期学习经验可能会影响婴儿的即时学习成功,以及他们的学习动机,因此在这个时期(学习习惯和好奇心的基础正在建立的时期)研究主动学习的机制尤为重要。研究婴儿学习的传统行为方法面临着新兴神经科学工具可能有助于缓解的挑战。我们介绍了一种这样的工具,即 EEG theta 振荡,并提出这种神经标记物具有为主动学习提供新见解的巨大潜力。在学习之前或期间记录的 theta 活动已被证明可以预测学习成功。我们认为,这种与记忆形成的关联,加上 theta 活动与奖励处理的紧密关联,使得 theta 振荡成为研究主动学习背后的动机机制的独特工具。我们概述了与婴儿学习相关的研究问题和方法方法,并提出了 theta 振荡如何以及为何可能提供补充见解。因此,我们旨在弥合认知和神经方法之间的差距,并更广泛地推进我们对发展中主动学习的认识。

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