Neural foundations of learning, reasoning, and surprise in human infants

人类的大脑是如何组织起来的，以便在发展过程中学习和推理世界？虽然 幼儿对意想不到的刺激表现出惊讶的行为迹象(例如，长时间注视)。 当听到一个全新的单词，看到一个物体漂浮在半空中，或者看到一个人表演 低效行动)(Gergely&Csibra，2003；Saffran，Aslin，&Newport，1996；Spelke，Blinlinger， Macomber，&Jacobson，1992；Spelke&Kinzler，2007)，神经系统支持他们的 期望和惊喜是不能通过衡量行为来获得的。在这项提案中，我们 使用一种对婴儿友好的非侵入性神经成像技术--功能性近红外光谱 (FNIRS)，研究允许婴儿和成年人形成期望和 在不同的情况下检测违反这些期望的情况。我们检验了假设 感觉皮质在学习过程中编码任务和通道特定信息，即侧部 前额叶皮质(LPFC)检测到随后违反这些预期的行为，LPFC驱动 关注这一令人惊讶的刺激措施。如果是这样，我们应该发现不同的感觉活动 在跨任务学习期间，但在那些任务中的突击期间重叠LPFC活动，这 应该反过来预测行为。Aim 1使用学习任务来测试这些预测，其中 在实验室中形成新的期望(例如，关于哪个词更有可能出现，Doti或Lado 来自新学的人工语言)(Marcus，1999；Saffran等人，1996)。AIM 2调查 同样的预测也适用于需要对物体进行事先预期的任务(即物体是固体的)， 人(他们的行为是理性的)和概率(随机抽样的样本往往是 人口代表)(Gergely&Csibra，2003；Spelke等人，1992；Spelke&Kinzler， 2007；Xu&Garcia，2008)。目标3比较了允许人们学习新知识的神经系统 期望(目标1)和使用先前期望的理由(目标2)。在所有目标上，我们将测试 婴儿和成年人在多个任务中(例如，一个任务涉及人，另一个涉及物体)， 比较学习过程中的神经活动和这些任务中的惊喜，并使用这种神经活动 来预测行为。拟议的研究采用创新的、跨学科的方法来推动 我们关于大脑如何组织以实现如此快速和丰富的学习的理论的前沿 跨越发展。它的发现将揭示(1)大脑的哪些区域受到牵连 形成预期并违反这些预期，(2)这些皮质区域是否 支持普遍、广泛的信念形成过程或特定于任务和通道的学习，以及 (3)它们如何调节婴儿和成年人的行为。因此，这项工作有可能 改变我们对婴儿在实验室内外如何学习和推理的理解。要知道如何 培养学习和推理，在典型和非典型的发展过程中，我们都需要一个因果关系 对学习和推理如何在头脑和大脑中工作的理论理解。这项工作需要 通过为设计和评估提供基准和措施，向这一目标迈进 有针对性的教育和育儿干预。

How is the human brain organized to learn and reason about the world during development? Although young infants show behavioral signs of surprise (e.g. longer looking) at unexpected stimuli (e.g. upon hearing a completely new word, seeing an object float in midair, or seeing a person perform an inefficient action) (Gergely & Csibra, 2003; Saffran, Aslin, & Newport, 1996; Spelke, Breinlinger, Macomber, & Jacobson, 1992; Spelke & Kinzler, 2007), the neural systems that support their expectation and surprise are not accessible through measurements of behavior. In this proposal, we use an infant-friendly, non-invasive neuroimaging technique, functional near-infrared spectroscopy (fNIRS), to investigate the neural systems that allow infants and adults to form expectations and detect violations of those expectations across different situations. We test the hypotheses that sensory cortex encode task- and modality specific information during learning, that lateral prefrontal cortex (LPFC) detects subsequent violations of those expectations, and that LPFC drives attention towards the surprising stimulus. If so, we should find differentiated sensory activity during learning across tasks, but overlapping LPFC activity during surprise in those tasks, which should in turn predict behavior. Aim 1 tests these predictions using learning tasks, wherein people form new expectations in the lab (e.g. about which word, 'doti' or 'lado', is more likely to come from a newly learned artificial language) (Marcus, 1999; Saffran et al., 1996). Aim 2 investigates the same predictions in tasks requiring prior expectations about objects (that they're solid), people (that they behave rationally), and probability (that randomly drawn samples tend to be representative of the population) (Gergely & Csibra, 2003; Spelke et al., 1992; Spelke & Kinzler, 2007; Xu & Garcia, 2008). Aim 3 compares the neural systems that allow people to learn new expectations (Aim 1) and reason using prior expectations (Aim 2). Across all aims, we will test infants and adults in multiple tasks (e.g. one task involving people, another involving objects), compare neural activity during learning and surprise in those tasks, and use this neural activity to predict behavior. The proposed research takes an innovative, cross-disciplinary approach to push the frontiers of our theories of how the brain is organized to enable such rapid and rich learning across development. Its findings will reveal (1) which regions of the brain are implicated in forming expectations and having those expectations violated, (2) whether those cortical regions support a general, broad process of belief formation or task- and modality-specific learning, and (3) how they modulate behavior in infants and adults. Thus, this work has the potential to transform our understanding of how infants learn and reason in and out of the lab. To know how to nurture learning and reasoning, during both typical and atypical development, we need a causal theoretical understanding of how learning and reasoning work in the mind and brain. This work takes strides towards this goal by providing benchmarks and measures for designing and evaluating targeted educational and parenting interventions.