Brain basis and neural circuitry of habit-like attention in infants and adults

项目摘要/摘要 大脑有能力通过一种机制过滤并优先处理通常是无关的视觉刺激的刺激物 引起了人们的注意。注意力控制甚至在出生时就存在，并在整个发育过程中进行调整。传统上， 注意力被认为是由目标驱动的机制(自上而下，由额顶支持)引导的 大脑网络)或刺激驱动机制(自下而上，由视觉网络支持)。这些 机制也遵循不同的发展轨迹，其中自上而下的注意达到成熟的速度较慢 而不是自下而上的注意，这是由于额叶皮质发育的延迟。然而，最近的研究强调了 一种不符合这种二分法的注意力：一种由先前经验(即，选择历史)驱动的注意力 这可以说是一种习惯。这种习惯性的注意力表现出行为上的僵化， 注意力和基底节障碍，存在于从婴儿期到老年的整个生命周期。尽管 在广泛的行为研究中，成年人对潜在的神经回路存在争议，而婴儿和儿童则未知。 孩子们。在这里，我们的目标是描述习惯类注意的神经基础，以阐明 在婴儿时期，经验就会使注意力发生偏向。我们假设这一新发现的机制 注意力由皮质下结构驱动。我们将使用基于任务的神经成像(使用上下文 提示范式)、结构(弥散加权成像)和功能(静息状态)连接性-在两者中 健康成人(18岁)和婴儿(6-10个月)。我们将利用最先进的神经成像技术 针对婴儿和成人的专门方案和分层贝叶斯建模，以确保个体健壮 评估神经活动以达到目标1：确定支持习惯性注意力的神经结构。 此外，我们将根据结构和功能的连通性来预测单个神经组织 使用机器学习的个人行为目标2：表征典型的婴儿和成人 皮质-纹状体回路之间的动力学，并将每个人的连接指纹与 他们的注意习惯的强度a)在他们的年龄组b)在他们的年龄组之间。澄清 习惯类注意力的神经基础可能会让我们更好地理解、识别和治疗认知 儿童注意力相关障碍的缺陷，以及晚年亨廷顿和帕金森氏症。 此外，这项工作将表征注意习惯的个体差异，从早期的发展和 可能会揭示出改善儿童和成人注意力习惯的方法。这项建议有必要 资源和匹配良好的团队，以揭示习惯性注意力的神经基础，这有令人兴奋的 对未来注意力缺陷的早期预测和潜在干预的影响。

Project Summary/ Abstract The brain has the ability to filter and prioritize a cacophony of often extraneous visual stimuli via a mechanism called attention. Attentional control is present even at birth and is tuned throughout development. Traditionally, attention is thought to be guided by either a goal-driven mechanism (top-down, supported by fronto-parietal brain networks) or a stimulus-driven mechanism (bottom-up, supported by visual networks). These mechanisms also follow distinct developmental trajectories where top-down attention reaches maturity slower than bottom-up attention due to the delay of frontal cortex development. However, recent work has highlighted a type of attention that does not fit within this dichotomy: one driven by prior experience (i.e., selection history) that can be characterized as a habit. This habit-like attention demonstrates behavioral inflexibility, deficits in attentional and basal ganglia disorders, and is present throughout the lifespan from infancy to old age. Despite extensive behavioral research, the underlying neural circuitry is debated in adults, and unknown in infants and children. Here, we aim to characterize the neural underpinnings of habit-like attention to elucidate how prior experience can bias attention as early as infancy. We hypothesize that this newly identified mechanism of attention is driven by subcortical structures. We will utilize neuroimaging—task-based (using a contextual cueing paradigm), structural (diffusion-weighted imaging), and functional (resting state) connectivity—in both healthy adults (18+) and infants (6—10 months). We will utilize state-of-the-art neuroimaging techniques with specialized protocols for infants and for adults and hierarchical Bayesian modeling to ensure robust individual estimation of neural activity to Aim 1: Identify the neural structures that support habitual attention. Further, we will relate predict individual neural organization from structural and functional connectivity to individual behavior using machine learning to Aim 2: Characterize the prototypical infant and adult dynamics between cortico-striatal circuitry and relate each individual’s connectivity fingerprints to the strength of their attentional habits a) within their age group b) between their age groups. Elucidating the neural underpinnings of habit-like attention may allow us to better understand, identify, and treat cognitive deficits in attention related-disorders in children, and Huntington’s and Parkinson’s diseases later in life. Moreover, this work will characterize individual differences in attentional habits from early in development and may reveal ways to improve attentional habits in both children and adults. This proposal has the necessary resources and well-matched team to uncover the neural basis of habit-like attention, which has exciting implications for early prediction and potential interventions for future attentional deficits.