Karavallil Achuthan Smitha, Coburn Kelly L, Beckerson Meagan E, Kana Rajesh K
Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA.
Department of Speech-Language Pathology & Audiology, Towson University, Towson, Maryland, USA.
Autism Res. 2023 Jan;16(1):84-98. doi: 10.1002/aur.2846. Epub 2022 Nov 9.
Resting state fMRI (rs-fMRI) provides an excellent platform for examining the amplitude of low frequency fluctuations (ALFF) and fractional amplitude of low frequency fluctuations (fALFF), which are key indices of brain functioning. However, ALFF and fALFF have been used only sporadically to study autism. rs-fMRI data from 69 children (40 autistic, mean age = 8.47 ± 2.20 years; age range: 5.2 to 13.2; and 29 non-autistic, mean age = 9.02 ± 1.97 years; age range 5.9 to 12.9) were obtained from the Autism Brain Imaging Data Exchange (ABIDE II). ALFF and fALFF were measured using CONN connectivity toolbox and SPM12, at whole-brain & network-levels. A two-sampled t-test and a 2 Group (autistic, non-autistic) × 7 Networks ANOVA were conducted to test group differences in ALFF and fALFF. The whole-brain analysis identified significantly reduced ALFF values for autistic participants in left parietal opercular cortex, precuneus, and right insula. At the network level, there was a significant effect of diagnostic group and brain network on ALFF values, and only significant effect of network, not group, on fALFF values. Regression analyses indicated a significant effect of age on ALFF values of certain networks in autistic participants. Such intrinsically different network-level responses in autistic participants may have implications for task-level recruitment and synchronization of brain areas, which may in turn impact optimal cognitive functioning. Moreover, differences in low frequency fluctuations of key networks, such as the DMN and SN, may underlie alterations in brain responses in autism that are frequently reported in the literature.
静息态功能磁共振成像(rs-fMRI)为检查低频波动幅度(ALFF)和低频波动分数幅度(fALFF)提供了一个极佳的平台,这两个指标是大脑功能的关键指标。然而,ALFF和fALFF仅偶尔被用于自闭症研究。来自自闭症脑成像数据交换库(ABIDE II)的69名儿童(40名自闭症儿童,平均年龄 = 8.47 ± 2.20岁;年龄范围:5.2至13.2岁;以及29名非自闭症儿童,平均年龄 = 9.02 ± 1.97岁;年龄范围5.9至12.9岁)的rs-fMRI数据被获取。使用CONN连接工具箱和SPM12在全脑和网络层面测量ALFF和fALFF。进行双样本t检验和二组(自闭症组、非自闭症组)×7网络方差分析以检验ALFF和fALFF的组间差异。全脑分析发现,自闭症参与者在左侧顶叶岛盖皮质、楔前叶和右侧岛叶的ALFF值显著降低。在网络层面,诊断组和脑网络对ALFF值有显著影响,而对fALFF值只有网络有显著影响,组没有显著影响。回归分析表明年龄对自闭症参与者某些网络的ALFF值有显著影响。自闭症参与者这种本质上不同的网络层面反应可能对大脑区域的任务层面募集和同步有影响,进而可能影响最佳认知功能。此外,关键网络如默认模式网络(DMN)和突显网络(SN)的低频波动差异可能是文献中频繁报道的自闭症大脑反应改变的基础。