Perinatal brain maturation in children at risk of developing Autism Spectrum Conditions

自闭症谱系疾病（ASC）包括一系列神经发育障碍，其特征是社交沟通和互动受损，行为和兴趣受到限制，形成刻板印象。尽管病因尚不清楚，但有一种理论获得了相当大的关注，那就是连接中断理论。该理论认为，症状是由于大脑功能活动的非典型同步。患有自闭症谱系障碍的个体可能无法像正常发育的个体那样有效地参与或脱离大脑网络。静息状态功能磁共振成像（rs-fMRI）的研究为ASC[1]的连接中断理论提供了支持。然而，由于ASC是一种神经发育障碍，父母通常在孩子12-14个月时就报告了最初的担忧，因此尚不清楚异常在多大程度上反映了该疾病的原发性病理生理，以及在多大程度上是继发性或代偿性影响。这促使人们尽可能早地研究大脑，以免大脑受到后天机制或患有自闭症特征的生活经历的影响。由于有ASC家族史（FAM+）的婴儿比没有家族史（FAM-）的儿童更容易发生ASC，因此对这些婴儿的前瞻性研究为评估ASC易感的生物学机制提供了一种手段。第一个使用fMRI表征FAM+婴儿功能连接的研究表明，6个月时功能连接异常可以预测24个月时的诊断结果。随后的研究表明，12个月时枕部区域和24个月时基底神经节的过度连接与运动行为的延迟有关，视觉网络与额顶叶皮层和默认模式网络之间的连接不足与12个月时的仪式/相同行为有关，背侧注意网络与皮层下区域之间的过度连接。在默认模式网络和额顶叶网络之间与24个月大时的刻板行为有关。最近，我们的研究小组发现，FAM+新生儿在负责处理高阶社会信息的区域也有明显更高的神经活动。然而，迄今为止的研究都是使用整个时间序列来得出区域之间的平均连通性。这是在假设大脑的功能结构是静态的情况下进行的。然而，越来越多的人认识到，网络之间的神经通信是高度灵活的，因此在静态fMRI分析中可能会丢失重要的时间信息[b]。由于在典型发育和ASC风险增加的婴儿中，发育中的大脑动态功能连接仍未被探索，因此本研究旨在探索具有ASC家族史的婴儿的动态功能连接，并在理解典型大脑发育的背景下进行研究。这可能为ASC的病因学提供重要的新见解，可能导致基于大脑瞬态网络动力学的新生物标志物的开发。这项工作将增加我们小组在异常神经发育成像生物标志物方面的多年研究，这得益于新生儿成像方面的专业知识，以及神经发育障碍（如ASC）的临床方面。1)描述和关联典型发育婴儿的静态和动态功能连接测量2)探索观察到的动态连接模式如何与睡眠状态波动相关。候选人将通过解决下一组目标来探索典型连接模式的差异，即：3)探索典型发育婴儿和具有自闭症谱系疾病家族史的婴儿之间的瞬态连接状态差异

Autism spectrum conditions (ASC) comprise a range of neurodevelopmental disorders, characterized by impaired social communication and interaction and restricted, stereotyped behaviours and interests. Although the aetiology remains unclear, one theory that has gained considerable traction is the disrupted connectivity theory. This theory suggests that symptoms are due to atypical synchronization of brain functional activity. Individuals with ASD may be unable to engage or disengage brain networks as effectively as typically developing individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) studies offer support to the disrupted connectivity theory of ASC [1]. However, with ASC being a neurodevelopmental disorder, and parents often reporting initial concerns as early as 12-14 months, it is unclear to what extent abnormalities reflect a primary pathophysiology of the condition, and to what extent they are secondary or compensatory effects. This has motivated efforts to study the brain as early in life as possible, before it is shaped by postnatal mechanisms or the experiences of living with autistic traits. As infants with a family history of ASC (FAM+) are more vulnerable to developing ASC themselves than children without a family history (FAM-)[2], prospective study of these infants provides a mean of assessing biological mechanisms associated with vulnerability to ASC. The first study using fMRI to characterize functional connectivity in FAM+ infants demonstrated that abnormalities in functional connectivity at 6 months can predict diagnostic outcome at 24 months [3]. Subsequent studies showed that over-connectivity in occipital regions at 12 months and basal ganglia at 24 months is linked to delays in motor behaviour [4], that underconnectivity between the visual network and frontoparietal cortex and the default mode network is associated with ritualistic/sameness behaviour at 12 months, and that overconnectivity between dorsal attention network and subcortical regions, and between default mode network and the frontoparietal network is associated with stereotyped behaviours at 24 months [5]. Most recently, our group showed that FAM+ neonates also have significantly higher neural activity in regions responsible for processing higher-order social information [6]However, studies to date have used the entire time series to derive the average connectivity between regions. This operates under the assumption that the brain's functional architecture is static. There is however growing appreciation that neural communication between networks is highly flexible, and important temporal information may therefore be lost in static fMRI analysis [7]. As dynamic functional connectivity in the developing brain remains unexplored, both in typical development and in infants with an increased risk of ASC, the proposed work aims to explore dynamic functional connectivity in infants with a family history of ASC, embedded within the context of understanding typical brain development. This may provide critical new insights into the aetiology of ASC, potentially leading to the development of new biomarkers based on the brains transient network dynamics. This work will add to years of research in imaging biomarkers for abnormal neurodevelopment performed by our group, which benefits strongly from expertise in neonatal imaging, as well as the clinical aspects of neurodevelopmental disorders such as ASC. 1)To describe and relate static and dynamic functional connectivity measures in typically developing infants 2)To explore how the observed dynamic connectivity patterns relate to fluctuations in sleep state The candidate will then explore divergence from typical connectivity patterns by addressing the next set of aims, namely: 3)To explore differences in transient connectivity states between typically developing infants and infants with a family history of autism spectrum conditions