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

人类大脑在发育过程中是如何组织起来学习和推理世界的？虽然 年幼的婴儿对意外的刺激（例如， 当你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一个 无效行动）（German & Csibra，2003; Saffran，Aslin，&纽波特，1996; Spelke，Breinlinger， Macomber，& Jacobson，1992; Spelke & Kinzler，2007），支持他们的神经系统。 期望和惊讶是无法通过行为的测量来获得的。在本提案中，我们 使用婴儿友好的非侵入性神经成像技术，功能性近红外光谱 （fNIRS），研究允许婴儿和成人形成期望的神经系统， 在不同的情况下检测对这些期望的违反。我们测试了假设， 在学习过程中，感觉皮层编码任务和模式特定信息， 前额叶皮层（LPFC）检测随后对这些期望的违反，并且LPFC驱动 注意力集中在令人惊讶的刺激。如果是这样的话，我们应该能找到 在学习任务，但重叠LPFC活动在这些任务的惊喜， 反过来又能预测行为。Aim 1使用学习任务测试这些预测，其中人们 在实验室中形成新的期望（例如，关于“doti”或“lado”哪个词更有可能出现 从新学习的人工语言）（Marcus，1999; Saffran等人，1996年）。目标2调查 同样的预测在任务中需要对物体的预先预期（它们是固体）， 人（他们的行为是理性的）和概率（随机抽取的样本往往是 代表人口）（German & Csibra，2003; Spelke等人，1992年; Spelke & Kinzler， 2007; Xu & Garcia，2008）。目标3比较了让人们学习新知识的神经系统 期望（Aim 1）和使用先验期望（Aim 2）进行推理。在所有目标中，我们将测试 婴儿和成人在多个任务（例如，一个任务涉及人，另一个涉及物体）， 比较学习和惊讶过程中的神经活动，并使用这些神经活动 来预测行为。拟议的研究采取创新的，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）大脑的哪些区域与 形成期望并违背这些期望，（2）这些皮层区域是否 支持信念形成或特定任务和特定模式学习的一般，广泛的过程，以及 (3)它们如何调节婴儿和成人的行为。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。知道如何 培养学习和推理，在典型和非典型的发展，我们需要一个因果关系， 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， 有针对性的教育和养育干预措施。

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.