Article Figures & Data
Figures
- Figure 1.
Schematic view of participant selection procedure and main analysis steps. a, From the original 1495 participants, 157 were excluded due to incomplete data, medical problems, poor brain coverage, or not being able to perform the task. A total of 567 participants were excluded due to excess head motion, and 12 participants were excluded due to low task accuracy. A total of 759 participants 8–23 years of age survived these exclusion criteria. b, Brain ROIs involved in emotion perception were identified using meta-analysis implemented in Neurosynth (Yarkoni et al., 2011). They included the following: vmPFC, dmPFC, vlPFC, dlPFC, lOFC, IPL, SPL, sgACC, pgACC, dACC, PCC, pre-SMA, BLA, vAI, dAI, PI, hippocampus (Hipp), and FFG. Subcortical ROIs, including CMA, BNST, and NAc, were identified using anatomical atlases (see also Table 3). ROIs were overlaid on a reference brain surface using BrainNet Viewer (Xia et al., 2013). c, Network analysis steps used to investigate development of the affective circuits. ci, ROI β series were derived from each task condition (fear, anger, sad, happy, or neutral) for each individual. cii, Functional connectivity matrices were computed for each individual. ciii, Functional connectivity matrices were fed into a community detection algorithm to determine community structure of the ROIs. civ, ROI nodal degree was computed over a wide range of sparsity (10% ≤ sparsity ≤ 40% with an interval of 5%), and then an integrated metric of nodal degree was obtained by computing the area under the curve. cv, Intramodule and intermodule interactions were computed. cvi, Deviation of individual community structure from template community structure was measured as the Jaccard overlap between the two. cvii, ROIs were further categorized into hubs or nonhubs, and then the probability of an ROI to be a hub within each age year was calculated. Permutation test was used to assess hub significance. cviii, These resulting brain metrics were further fed into linear mixed-effect models to assess age, emotion, and age × emotion effects. d, Reliability analyses assessed the robustness of age-related findings and the effect of sample size. Briefly, we randomly drew N (sample size) participants from the full sample and assessed age-related changes in the subsample. This was repeated 1000 times across a wide range of sample sizes (50 ≤ N ≤ 400, increased by 50). Correlation between age effects from a subsample and that from the full sample was calculated and then averaged across subsamples for each sample size. The resulting average correlation was used to measure reliability.
- Figure 2.
Developmental changes in behavior and reliability. Accuracy: The ability to correctly identify high arousal-negative (threat-related) emotions (fear and anger) improved with age in both the fMRI (ai) and full behavioral samples (bi). Only reliability of significant effects was assessed. RT: Time to identify an emotion decreased with age across all five emotion categories in both the fMRI (aii) and full behavioral samples (bii). c, Reliability was measured as the probability of observing a significant correlation between accuracy and age or that between RT and age. ci, Accuracy: Reliability of age-accuracy associations increased as sample size increased for conditions that showed significant age-related changes in accuracy in the fMRI (solid line) and the full behavioral (dashed line) samples. cii, RT: Reliability of age-RT associations increased as sample size increased for all five emotion categories in the fMRI (solid line) and the full behavioral (dashed line) samples. In general, a sample size of 300–350 was needed to identify reliable (reliability > 0.7) age-accuracy association and that of 200 was needed to identify reliable age-RT association.
- Figure 3.
Main effects of age and emotion on modular organization and connectivity. ai, Three functional modules were identified across all participants: the FP module (red), mPFC/PCC module (green), and SPI module (yellow). aii, As shown in the group consistency matrix, the FP module (red border) includes bilateral dlPFC, vlPFC, dACC, pre-SMA, IPL, SPL, and FFG. The mPFC/PCC module (blue border) includes bilateral NAc, sgACC, pgACC, PCC, vmPFC, and dmPFC. The SPI module (yellow border) includes BLA, CMA, vAI, PI, BNST, and hippocampus (Hipp). Color bar represents the probability of two nodes being classified in the same module across participants. b, As shown in the group consistency matrices, overall modular structure is stable across all five emotion categories and age groups (children 8–12 years, adolescents 13–17 years, adults 18–23 years). c, Intra-FP connectivity and FP-SPI connectivity increased with age; intra-FP, intra-SPI, and all intermodule connectivity measures varied across emotions; age-related changes in intra-mPFC/PCC connectivity were modulated by emotion category. d, Intramodule and intermodule connectivity varied across emotions. Data are mean ± SEM.
- Figure 4.
Developmentally stable hubs in mPFC. a, ROI nodal degree for each emotion category. Node size is in proportion to integrated nodal degree measure. b, Probability measures averaged across all regions within each module at each age year. Overall, the mPFC/PCC module has a higher probability to be a functional hub across age than the FP and SPI modules. Data are mean ± SEM. c, Multiple regions of the mPFC/PCC module, including pgACC, vmPFC, and dmPFC of the mPFC/PCC module were identified as functional hub regions for all five emotion categories and were stable over development. Here, probability matrices are masked by the 95th percentile of empirical null distribution at each region and age year, with probability values ≤95th percentile set as 0. An age year includes all participants whose age was larger than or equal to the current age year and less than the next age year (e.g., age 8 includes all participants with age ≥8 and <9).
- Figure 5.
Main effects of age and emotion on regional connectivity. a, Connectivity within FP and SPI modules, between FP and SPI modules, and between mPFC/PCC and SPI modules increased with age, including left dlPFC connectivity with right dAI, right vAI connectivity with right sgACC and bilateral PI, right BNST connectivity with right IPL and SPL, and right BLA connectivity with left PI. Connectivity within mPFC/PCC and SPI modules decreased with age, including right sgACC connectivity with left vmPFC and left CMA connectivity with right CMA and left PI. Emotion effects are widespread, especially within FP module, between FP and mPFC/PCC modules, between FP and SPI modules, and between mPFC/PCC and SPI modules. b, Reliability of age-related changes in regional connectivity across all brain regions increased with sample size. A sample size of 50 is sufficient for reliability to surpass the 95th percentile of its corresponding empirical null distribution (dashed line), and a minimum sample size of 200–250 was needed to identify reliable age-related changes. c, Classification analysis showed that it was sufficient to discriminate all pairs of emotion categories using all interregional links, with classification accuracy ranging from 56.2% to 67.2% and significantly higher than chance level as assessed by permutation test.
- Figure 6.
Main effects of age and emotion on regional activity. ai, Brain regions showing age-related changes. Activity in cognitive control regions, including bilateral pre-SMA, dACC, dlPFC, left SPM, right IPL, and right lOFC, decreased with age. Node size was scaled to present effect size of age-related decrease. aii, Reliability of age-related changes across all brain regions. A minimum sample size of 50–100 was needed for reliability to surpass the 95th percentile of its corresponding empirical null distribution (dashed line), and a minimum sample size of 50–100 was needed to identify reliable (correlation > 0.7) age-related changes. bi, Brain regions showing emotion effects. Node size was scaled to present F value of emotion effect. bii, Activity in all brain regions, except bilateral BNST, varied across emotion category.
Tables
- Table 1.
Studies that examined age-related changes in amygdala activity and connectivity underlying emotion perceptiona
Study Sample size Age (yr) Contrast and no. of trials Task Findings Gee et al. (2013) 45 (19F) 4–22 Fearful face versus fixation (no. of trials = 24) Participants viewed fearful faces interspersed with neutral faces in one run, and viewed happy faces interspersed with neutral faces in the other run Amygdala activity decreased with age; amygdala-vmPFC connectivity decreased with age Kujawa et al. (2016) 61 (35F) TD 7–25 Emotional faces (happy, angry, or fearful) versus shapes (no. of trials per emotion category = 12) Participants were instructed to match emotion (happy, angry, or fearful) of the target face in face blocks and match shapes in shape blocks No age-related effect in amygdala activity; amygdala-dACC connectivity decreased with age in TD but increased with age in AD for all emotions 57 (34F) AD Wu et al. (2016) 61 (35F) 7–25 Emotional faces (angry, fearful, or happy) versus shapes (no. of trials per emotion category = 12) Participants were instructed to match emotion (angry, fearful, or happy) of the target face in face blocks and match shapes in shape blocks No age-related effect in amygdala activity; amygdala-ACC/mPFC connectivity decreased with age for all emotions Vink et al. (2014) 60 (28F) 10–24 Positive versus neutral (no. of trials = 32), negative versus neutral (no. of trials = 32) Participants viewed each picture selected from the IAPS and label the valence (negative, neutral, or positive) Amygdala activity decreased with age; amygdala-mOFC connectivity increased with age Wolf and Herringa (2016) 24 (13F) TD 8–18 Threat versus neutral (no. of trials = 16) Participants viewed threat and neutral images selected from the IAPS and label the valence No age-related effect in amygdala activity; amygdala-mOFC connectivity increased with age in TD but decreased with age in PTSD 24 (16F) PTSD ↵aIf not specified, healthy individuals were recruited in the listed studies. Functional connectivity was measured by PPI in Gee et al. (2013), Vink et al. (2014), and Wolf and Herringa (2016) and by gPPI in Kujawa et al. (2016) and Wu et al. (2016). AD, Anxiety disorder; IAPS, International Affective Picture System; PPI, psychophysiological interaction; PTSD, post-traumatic stress disorder; TD, typically developing. For MNI coordinates of amygdala and PFC regions used in these studies, see Table 4. For results of replication analysis, see Tables 5–7.
Characteristic Mean ± SD (n = 759) Age (yr) 16.20 ± 3.27 Sex (female/male) 419/340 Race (Caucasian/other) 408/351 Motion (mm) 0.073 ± 0.03 Fluid intelligencea 12.62 ± 3.97 Fear accuracy 0.89 ± 0.11 Anger accuracy 0.92 ± 0.09 Sad accuracy 0.88 ± 0.11 Neutral accuracy 0.91 ± 0.09 Happy accuracy 0.99 ± 0.03 Fear RT (s) 2.65 ± 0.46 Anger RT (s) 2.48 ± 0.44 Sad RT (s) 2.68 ± 0.46 Happy RT (s) 2.09 ± 0.40 Neutral RT (s) 2.34 ± 0.44 ↵aFluid intelligence is measured by Penn Matrix Reasoning Test scores (i.e., total correct responses for all test trials). RT, Response time (median). For age distribution, see also Figure 1a.
Region/abbreviation MNI coordinates Brodmann area x y z Left BLA (BLA.L) −20 −6 −20 Right BLA (BLA.R) 26 −4 −20 Left CMA (CMA.L) −24 −9 9 Right CMA (CMA.R) 27 −10 −9 Left sgACC (sgACC.L) −2 14 −16 BA 25 Right sgACC (sgACC.R) 6 20 −12 BA 25 Left pgACC (pgACC.L) −2 42 6 BA 32 Right pgACC (pgACC.R) 2 42 8 BA 32 Left dACC (dACC.L) −4 22 30 BA 32 Right dACC (dACC.R) 4 22 30 BA 32 Left PCC (PCC.L) −2 −54 28 BA 31 Right PCC (PCC.R) 4 −54 28 BA 31 Left vmPFC (vmPFC.L) −8 50 −4 BA 10 Right vmPFC (vmPFC.R) 8 50 −4 BA 10 Left vmPFC (vmPFC.L) −2 50 −12 BA 32 Right vmPFC (vmPFC.R) 4 50 −12 BA 32 Left vmPFC (vmPFC.L) −4 38 −10 BA 32 Right vmPFC (vmPFC.R) 4 38 −10 BA 32 Left dmPFC (dmPFC.L) −2 58 20 BA 9 Right dmPFC (dmPFC.R) 2 58 20 BA 9 Left pre-SMA (preSMA.L) −2 18 46 BA 6 Right pre-SMA (preSMA.R) 6 24 38 BA 32 Left lOFC (lOFC.L) −46 26 −6 BA 47 Right lOFC (lOFC.R) 46 26 −4 BA 47 Left lOFC (lOFC.L) −28 18 −16 BA 47 Right lOFC (lOFC.R) 26 22 −18 BA 47 Left vlPFC (vlPFC.L) −48 28 10 BA 45 Right vlPFC (vlPFC.R) 48 28 10 BA 45 Left dlPFC (dlPFC.L) −46 8 30 BA 9 Right dlPFC (dlPFC.R) 46 8 30 BA 9 Left dlPFC (dlPFC.L) −41 22 43 BA 8 Right dlPFC (dlPFC.R) 41 22 43 BA 8 Left IPL (IPL.L) −54 −50 44 BA 40 Right IPL (IPL.R) 46 −48 44 BA 40 Left SPL (SPL.L) −30 −56 44 BA 7 Right SPL (SPL.R) 38 −50 52 BA 7 Left FFG (FFG.L) −42 −48 −20 BA 37 Right FFG (FFG.R) 42 −48 −20 BA 37 Left dAI (dAI.L) −34 22 0 BA 13 Right dAI (dAI.R) 38 22 −4 BA 13 Left vAI (vAI.L) −38 −2 −10 BA 13 Right vAI (vAI.R) 44 6 −10 BA 13 Left PI (PI.L) −38 −18 14 BA 13 Right PI (PI.R) 38 −14 16 BA 13 Left BNST (BNST.L) −6 2 0 Right BNST (BNST.R) 6 2 0 Left NAc (NAc.L) −10 12 −8 Right NAc (NAc.R) 10 12 −8 Left hippocampus (Hipp.L) −34 −18 −16 Right hippocampus (Hipp.R) 32 −14 −16 - Table 4.
MNI coordinates of amygdala and PFC regions used in previous developmental studies of face emotion perceptiona
Study Amygdala (x, y, z) Connectivity Seed (x, y, z) and target (x, y, z) Gee et al. (2013) (32, −1, −16) Right amygdala (32, −1, −16) and right vmPFC (2, 32, 8) Kujawa et al. (2016) (−20, −2, −20), (24, −2, −22) Left amygdala (AAL) and left dACC (−4, 30, 16) Right amygdala (AAL) and right dACC (2, 34, 14) Wu et al. (2016) Left and right amygdala from AAL atlas Left amygdala (AAL) and left ACC/mPFC (−6, 34, 16) Right amygdala (AAL) and left ACC/mPFC (−4, 36, 14) Left amygdala (AAL) and left ACC (−8, 28, 18) Right amygdala (AAL) and right ACC (6, 36, 12) ↵aAAL, Automated anatomical labeling. While no age-related effects were revealed in amygdala activity in Kujawa et al. (2016) and Wu et al. (2016), we created amygdala ROI based on coordinates showing significant main effect of emotion category in Kujawa et al. (2016) or used amygdala AAL atlas, which was a seed region in connectivity analysis in Wu et al. (2016), to examine age-related effects of amygdala activity in our PNC cohort.
- Table 5.
Age-related changes in amygdala activity in the PNC sample using coordinates from previous studiesa
Region Emotion F(1,754) p Effect size Right amygdala in Gee et al. (2013)↓ Neutral 1.121 0.290 −0.040 Fear 0.228 0.633 0.018 Anger 0.174 0.677 −0.016 Sad 1.965 0.161 0.052 Happy 0.109 0.741 −0.012 Left amygdala in Kujawa et al. (2016)b Neutral 0.953 0.329 0.036 Fear 12.617 0.0004 0.132 Anger 1.844 0.175 0.051 Sad 15.140 0.0001 0.144 Happy 9.020 0.003 0.111 Right amygdala in Kujawa et al. (2016)b Neutral 0.566 0.452 0.028 Fear 2.650 0.104 0.061 Anger 0.123 0.726 0.013 Sad 2.801 0.095 0.063 Happy 0.726 0.394 0.032 Left amygdala (AAL) in Wu et al. (2016)b Neutral 1.583 0.209 0.047 Fear 15.796 7.73e-05 0.147 Anger 4.571 0.033 0.080 Sad 20.755 6.08e-06 0.168 Happy 10.009 0.002 0.117 Right amygdala (AAL) in Wu et al. (2016)b Neutral 0.277 0.599 0.020 Fear 5.741 0.017 0.089 Anger 1.946 0.163 0.052 Sad 5.784 0.016 0.089 Happy 1.553 0.213 0.046 ↵aEffect size is measured by the standardized partial coefficient of the age term. AAL, Automated anatomical labeling; ↓, developmental decreases in amygdala with mPFC was reported in the cited study. AAL indicates that the amygdala ROI was derived based on AAL atlas.
↵bNo significant developmental changes were found in the cited study.
- Table 6.
Age-related changes in amygdala connectivity in the PNC sample using coordinates from previous studiesa
Connectivity Emotion F(1,754) p Effect size AMY.R-vmPFC.R in Gee et al. (2013)↓ Neutral 0.210 0.647 0.017 Fear 3.497 0.062 0.069 Anger 1.880 0.171 0.051 Sad 0.963 0.327 0.036 Happy 0.288 0.591 0.020 AMY.L-dACC.L in Kujawa et al. (2016)↓ Neutral 0.008 0.929 −0.003 Fear 8.921 0.003 0.109 Anger 2.569 0.109 0.059 Sad 0.388 0.533 0.023 Happy 4.596 0.032 0.079 AMY.R-dACC.R in Kujawa et al. (2016)↓ Neutral 0.214 0.644 0.017 Fear 6.602 0.010 0.094 Anger 7.661 0.006 0.101 Sad 4.420 0.036 0.077 Happy 3.232 0.073 0.066 AMY.L-mPFC.L in Wu et al. (2016)↓ Neutral 0.012 0.914 −0.004 Fear 4.139 0.042 0.075 Anger 1.198 0.274 0.040 Sad 0.003 0.958 0.002 Happy 1.199 0.274 0.040 AMY.R-mPFC.L in Wu et al. (2016)↓ Neutral 0.334 0.563 0.021 Fear 3.712 0.054 0.071 Anger 7.566 0.006 0.101 Sad 1.333 0.249 0.004 Happy 2.743 0.098 0.061 AMY.L-ACC.L in Wu et al. (2016)↓ Neutral 0.019 0.890 0.005 Fear 4.351 0.037 0.076 Anger 3.000 0.084 0.064 Sad 0.602 0.438 0.028 Happy 2.769 0.097 0.061 AMY.R-ACC.R in Wu et al. (2016)↓ Neutral 0.013 0.909 0.004 Fear 4.551 0.033 0.078 Anger 5.901 0.015 0.089 Sad 4.496 0.034 0.078 Happy 1.261 0.262 0.041 ↵aEffect size is measured by the standardized partial coefficient of age term. ↓, Developmental decrease in amygdala-mPFC connectivity (reported in the cited study).
- Table 7.
Replicability of previous developmental findings in amygdala activity and connectivity underlying face emotion perception
Study Findings Replicability Amygdala activity Amygdala connectivity Gee et al. (2013) Amygdala activity decreased with age; amygdala-vmPFC connectivity decreased with age No No Kujawa et al. (2016) No age-related effect in amygdala activity; amygdala-dACC connectivity decreased with age in TD but increased with age in AD for all emotions Partially yes No Wu et al. (2016) No age-related effect in amygdala activity; amygdala-ACC/mPFC connectivity decreased with age for all emotions Partially yes No
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