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

项目概要/摘要 大脑有能力通过一种机制来过滤和优先考虑那些不和谐的外部视觉刺激 引起注意。注意力控制甚至在出生时就存在，并在整个发育过程中得到调整。传统上， 注意力被认为是由目标驱动的机制（自上而下，由额顶叶支持）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，自上而下的注意力达到成熟的速度较慢， 而不是由下而上的注意力，因为额叶皮层发育迟缓。然而，最近的工作突出表明， 一种不适合这种二分法的注意力类型：一种由先前经验驱动（即，选择历史） 这可以被描述为一种习惯。这种习惯性的注意力表现出行为的不稳定性， 注意力和基底神经节障碍，并且存在于从婴儿到老年的整个生命周期中。尽管 广泛的行为研究，潜在的神经回路在成人中是有争议的，在婴儿中是未知的， 孩子在这里，我们的目标是描述习惯性注意力的神经基础，以阐明先前如何 早在婴儿时期，经验就能使注意力产生偏差。我们假设，这种新发现的机制， 注意力是由皮层下结构驱动的。我们将利用基于神经成像任务（使用上下文 提示范式），结构（弥散加权成像）和功能（静息状态）的连接性-在两者中 健康成人（18岁以上）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协议以及分层贝叶斯建模，以确保可靠的个体 目标1：识别支持习惯性注意的神经结构。 此外，我们将从结构和功能连接性预测个体神经组织， 使用机器学习的个人行为目标2：描述典型的婴儿和成人 皮质-纹状体回路之间的动态，并将每个人的连接指纹与 注意力习惯的强度a）在他们的年龄组内B）在他们的年龄组之间。阐明 习惯性注意力的神经基础可以让我们更好地理解、识别和治疗认知障碍。 儿童的注意力缺陷相关障碍，以及晚年的亨廷顿病和帕金森病。 此外，这项工作将从发展的早期描述注意习惯的个体差异， 可能揭示了改善儿童和成人注意力习惯的方法。该提案具有必要的 资源和匹配良好的团队来揭示习惯性注意力的神经基础，这令人兴奋 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.