Detecting and Analyzing Brain Networks of Adult ADHD Using Dual Temporal and Spatial Sparse Representation
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摘要: 注意力缺陷多动障碍（Attention deficit hyperactivity disorder，ADHD）主要表现为注意力分散、多动和冲动，是一种常见的精神障碍疾病.作为一种流行的脑功能成像技术，静息态功能核磁共振成像（Resting-state functional magnetic resonance imaging，rsfMRI）常应用于探索ADHD的神经机制.然而，由于rsfMRI数据的高维和少样本特性，采用传统的独立成分分析方法从rsfMRI数据中获得脑网络后，大多用基于体素级的方法进行推断，这难以检测出可靠的、与ADHD相关的脑网络.针对上述问题，本文提出了一种新颖的基于时空双稀疏表示（Dual temporal and spatial sparse representation，DTSSR）的方法和指标，以22名成人ADHD患者为研究对象，从大尺度脑网络级的角度检测出与ADHD相关的脑网络.首先采用DTSSR从ADHD的rsfMRI数据中提取出组脑网络及相应的耦合参数；然后将耦合参数均值池化作为网络的活跃度指标；最后，将活跃度指标与ADHD的量表分进行Spearman相关性分析，检测出与ADHD相关的脑网络.实验结果表明，背侧注意网络、执行控制网络的活跃度与ADHD量表分具有显著相关性.该结果在脑科学角度有合理的解释，且在不同字典尺寸下具有较高稳定性.本文所提方法，为探讨ADHD的潜在神经机制提供了一种新思路.Abstract: Attention deficit hyperactivity disorder (ADHD) is a highly prevalent psychiatric disorder, which is generally characterized by symptoms of inattentiveness, hyperactivity and impulsivity. As a popular functional imaging technique, the resting-state functional magnetic resonance imaging (rsfMRI) is frequently used to explore the neural mechanism of ADHD. However, after resting-state brain networks are obtained from the rsfMRI dataset with the traditional independent component analysis, it is difficult to detect reliable ADHD-related brain networks via voxel-level inference because of the high dimensions and relatively few samples of fMRI data. To address the problem, a novel framework and index using the dual temporal and spatial sparse representation (DTSSR) is proposed, which is able to detect the resting-state brain networks related to ADHD from a large scale network-level perspective in an rsfMRI dataset consisting of 22 adult ADHD patients. First, the group-wise brain networks and coupling parameters are inferred from the ADHD fMRI dataset via DTSSR. These coupling parameters are then processed by average-pooling as an index for activity of each group-wise network. Finally, the Spearman correlation analysis between those obtained indices and the ADHD rating scores is performed to detect the networks related to ADHD. Experiment demonstrates that the dorsal attention network and executive control network are significantly related to ADHD. The result shows high stability under different dictionary sizes and can be reasonably explained from brain science. The proposed framework can be used to explore the underlying neural mechanism of ADHD in a new perspective.1) 本文责任编委 朱朝喆
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图 1 基于DTSSR的ADHD_RSN的检测方法整体框图
Fig. 1 The framework for detecting adult ADHD_RSN using DTSSR
图 4 通过耦合参数识别ADHD_RSN示例图(RSN#1为例)
Fig. 4 Illustration of identifying ADHD_RSN by use of coupling parameters (RSN#1 as the example
图 5 采用DTSSR从ADHD组fMRI数据集中提取组RSN ("激活"体素采用MELODIC推断获得)
Fig. 5 The inferred group-wise RSNs with DTSSR from the ADHD dataset (The "activated" voxels were inferred by MELODIC)
图 7 ADHD_RSN空间分布图("激活"体素采用MELODIC推断)((a)背侧注意网络(RSN#6); (b)执行控制网络(RSN#11))
Fig. 7 The spatial maps of the ADHD_RSN (The "activated" voxels were inferred by MELODIC)((a) dorsal attention network (RSN#6); (b) executive control network (RSN#11)
图 8 不同字典尺寸下与背侧注意网络空间相关的ADHD_RSN
Fig. 8 The detected ADHD_RSNs is correlated to dorsal attention network in different dictionary sizes
表 1 表 1 ADHD组人口统计学特性
Table 1 Demographic of the ADHD group
患者人数 性别比(男:女) 年龄 ADHD分值 22 17:5 34.6±9.4 30.8±8.6 
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表 2 ADHD组量表分、脑网络活跃程度指标、相关系数、$P$-$value$及ADHD_RSN检测结果
Table 2 The obtained ADHD_RSN, indexes for activity of brain networks, correlation\\ coefficients, $P$-$value$ and ADHD_RSN
患者 量表 RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN RSN 编号 分 #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 #11 #12 #13 #14 #15 #16 #17 #18 #19 #20 Sub. 1 32 61 74 96 75 83 96 90 94 52 73 101 78 72 104 90 111 58 68 54 92 Sub. 2 31 110 80 70 74 90 107 77 130 56 68 100 70 117 91 80 134 53 70 59 53 Sub. 3 48 88 85 89 58 97 87 87 92 54 55 125 80 78 80 83 123 38 80 58 68 Sub. 4 35 94 100 102 70 113 122 102 133 54 64 93 92 83 85 67 158 54 92 59 92 Sub. 5 21 73 70 74 60 68 84 77 88 65 104 88 75 70 95 66 123 43 68 54 82 Sub. 6 22 81 85 96 77 81 84 75 96 48 59 81 80 71 83 68 158 47 67 51 76 Sub. 7 42 72 72 100 65 94 104 77 108 64 83 106 95 93 91 90 106 37 84 57 88 Sub. 8 37 69 97 106 65 96 101 97 128 77 66 93 90 85 102 105 154 56 70 64 103 Sub. 9 29 88 55 57 49 66 54 64 92 41 67 67 55 62 58 56 139 29 66 43 85 Sub. 10 35 70 101 102 70 80 85 75 111 54 75 109 71 80 89 76 133 44 65 46 85 Sub. 11 41 73 84 61 52 73 92 78 106 85 48 106 65 81 90 65 115 48 61 56 50 Sub. 12 31 89 97 106 74 93 110 86 99 60 60 97 93 71 98 71 140 40 99 56 84 Sub. 13 11 56 67 77 64 87 70 77 71 53 43 73 56 66 89 48 124 37 28 44 49 Sub. 14 44 72 92 91 98 90 109 86 93 62 37 99 110 82 83 77 112 41 66 69 94 Sub. 15 21 87 56 53 50 85 58 55 90 52 67 65 50 70 50 56 116 37 59 39 102 Sub. 16 32 116 81 81 50 106 92 73 115 75 92 92 75 98 83 71 142 45 98 51 90 Sub. 17 23 76 96 81 78 90 102 88 113 67 50 107 106 89 98 83 107 55 70 58 55 Sub. 18 25 82 89 80 49 84 63 74 107 41 75 87 87 97 76 70 143 43 80 35 83 Sub. 19 30 63 53 71 65 61 76 77 66 42 31 81 59 55 69 65 107 46 48 60 61 Sub. 20 31 59 70 121 101 70 118 88 93 59 43 114 87 106 104 100 101 41 38 79 53 Sub. 21 28 103 86 93 79 145 88 86 156 96 71 108 74 71 86 93 146 56 92 59 106 Sub. 22 29 58 64 51 52 58 55 71 92 38 63 54 50 81 55 37 134 30 64 34 65 相关系数 0.01 0.41 0.39 0.12 0.36 0.56 0.40 0.33 0.33 0.06 0.57 0.39 0.44 0.17 0.49 0.14 0.14 0.26 0.47 0.22 $P$-$value$ 0.953 0.059 0.070 0.594 0.100 0.006 0.061 0.129 0.138 0.801 0.005 0.072 0.042 0.450 0.021 0.541 0.540 0.240 0.024 0.333 FDR校正 0.95 0.16 0.16 0.66 0.20 0.06 0.16 0.23 0.23 0.84 0.06 0.16 0.16 0.60 0.12 0.64 0.64 0.37 0.12 0.48 相关网络 × × × × × √ × × × × √ × × × × × × × × × 注: Sub. 1 $\sim$ Sub. 22表示患者编号; "×"表示与ADHD_RSN无关; "√"表示与ADHD_RSN相关.
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表 3 不同字典尺寸下与各模板网络空间相关的ADHD_RSN统计
Table 3 The count of the ADHD_RSN with each template in different dictionary sizes
字典尺寸 60 100 140 180 220 260 300 RSN#1 / 1 / / 1 / / RSN#2 / / / / / / / RSN#3 1 2 2 3 / / 1 RSN#4 / / / / / / 1 RSN#5 1 1 3 3 2 3 1 RSN#6 2 2 4 5 3 4 3 RSN#7 1 / 2 3 2 2 4 RSN#8 5 4 7 4 4 6 6 RSN#9 2 5 3 2 6 4 3 RSN#10 / / / / / / / RSN#11 2 1 4 3 3 2 2 RSN#12 / 2 2 1 1 1 / RSN#13 / / / / / / / RSN#14 / / 1 2 / / / RSN#15 / / 1 / 1 2 1 RSN#16 / 2 1 2 / / 1 RSN#17 / / 1 1 1 1 1 RSN#18 / / 1 1 1 / 1 RSN#19 / / / 1 1 1 2 RSN#20 / / / 1 2 1 / 注: "/"表示未检测到与模板网络相关的ADHD_RSN.
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