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Mission Statements

Our long-term goal is to create neurobiologically sound developmental curves for the brain to characterize phenomenological changes associated with the onset of varying forms of mental health and learning disorders, as well as to predict the developmental status (i.e., age-expected values) of an individual brain’s structure or function. Beyond neurodevelopment, lifespan perspectives can help reveal commonalities and differences among pathophysiologic processes that manifest similar symptom profiles at different stages in life. From a neurological perspective, brain maturation and aging curves may prove useful for identifying factors that can mitigate neurocognitive decline and potentially identify optimal periods for intervention. With this tool, we are seeking knowledge that will translate into a better life style and diagnosis/treatment for patients.

Chinese Color Nest Project (CCNP)

This ongoing large-scale project is supported by Chinese Academy of Sciences (CAS), Natural Science Foundation of China (NSFC), the Ministry of Science and Technology of the People´s Republic of China and Beijing Municipal Science & Tech Commission. The CCNP aims at collecting large-scale lifespan data of the human brain and behavior (1200 participants) via a cross-sectional and longitudinal mixed sampling design or accelerated longitudinal design over a span of 10 years (2013 - 2022). CCNP comprises three connected components:

1) The stdCCNP recruits total 240 adults (20-60 years) as participants, and each participant visits three ultra-high field (two 3T and one 7T) MRI scanners located at the CAS Institute of Psychology (GE) and the CAS Institute of Biophysics (Simens), generating 5 scans including two-week test-retest data at the two 3T scanners (see the illustration of its design in below). This component (2016 - 2017) serves resources for standardizing pipelines of data collection, storage and analyses based upon the test-retest reliability and reproducibility across scanners, which will be employed for other two components.

devCCNP trial

2) The devCCNP (2017 - 2022) targets longitudinal data from 480 typically developing kids (see the illustration of its design in below). As a trial sample using the devCCNP design has been tested at Southwest University, which includes 3 waves of neuroimaging data from 192 developing children (6-18 years) across five years (2013 - 2017). The data from this trial stage of devCCNP will be released to the public in early 2017 (by summer).

devCCNP trial

3) The ageCCNP (2017 - 2022) collects a longitudinal dataset from 480 healthy old adults (see the illustration of its design in below). The age span of the ageCCNP is 60-84 years.

ageCCNP trial

References

[13]. Zuo XN*, He Y, Betzel RF, Colcombe S, Sporns O, Milham MP*. Human connectomics across the lifespan. Trends in Cognitive Sciences, 2017, 21(2): 32-45.

[12]. Yan ZX, Liu X, Tan SP,Tan YL,Wei GX, Yang Z, Zuo XN*. Developmental cognitive neurosciecne: Functional connectomics agenda for human brain lifespan development. Chinese Science Bulletin. 2016; 61(7):718-727.

[11]. He Y, Xu T, Zhang W, Zuo XN*. Lifespan anxiety is reflected in intrinsic amygdala cortical connectivity. Human Brain Mapping, 2016; 37(3):1178-1193.

[10]. Betzel R, Avena-Koenigsberger A, Goni J, He Y, de Reus M, Griffa A, Vertes P, Misic B, Hagmann P, Thiran JP, van den Heuvel M, Zuo XN, Bullmore Ed, Sporns O*. Generative models of the human connectome. 2016; NeuroImage, 124(Part A):1054-1064.

[9]. Wang J, Yang N, Liao W, Zhang H, Yan CG, Zang YF, Zuo XN*. Dorsal anterior cingulate cortex in typically developing children: Laterality analysis. Developmental Cognitive Neurosciences, 2015; 15:117-129.

[8]. Zhao T, Cao M, Niu H, Zuo XN, Evans A, He Y, Dong Q, Shu N*. Age-related changes in the topological organization of the white matter structural connectome across the human lifespan. Human Brain Mapping, 2015; 36(10):3777-3792.

[7]. Li HJ*, Hou XH, Liu HH, Yue CL, Lu GM, Zuo XN*. Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging. Neuroscience & Biobehavioral Reviews, 2015; 57:156-174.

[6]. Di Martino A, Fair DA, Kelly C, Satterthwaite TD, Castellanos FX, Thomason ME, Craddock RC, Luna B, Leventhal BL, Zuo XN, Milham MP*. Unraveling the miswired connectome: A developmental perspective. Neuron, 2014; 83(6):1335-353.

[5]. Betzel RF, Byrge L, He Y, Goni J, Zuo XN, Sporns O*. Changes in structural and functional connectivity among resting-state networks across the human lifespan. NeuroImage, 2014; 102:345-357.

[4]. Yang Z*, Chang C, Xu T, Jiang L, Handwerker DA, Castellanos FX, Milham MP, Bandettini PA, Zuo XN*. Connectivity trajectory across lifespan differentiates the precuneus from the default network. NeuroImage, 2014; 89:45-56.

[3]. Cao M, Wang JH, Dai ZJ, Cao XY, Jiang LL, Fan FM, Song XW, Xia MR, Shu N, Dong Q, Milham MP, Castellanos FX, Zuo XN*, He Y*. Topological organization of the human brain functional connectome across the lifespan. Developmental Cognitive Neurosciences, 2014; 7C:76-93.

[2]. Zuo XN*, Zhang Z, He Y, Zang YF. The human functional connectome: Its methodology, developmental trajectory and behavioral association. Chinese Science Bulletin, 2012; 57(35): p3399.

[1]. Zuo XN*, Kelly C, Di Martino A, Mennes M, Margulies DS, Bangaru S, Grzadzinski R, Evans AC, Zang YF, Castellanos FX, Milham MP*. Growing together and growing apart: regional and sex differences in the lifespan developmental trajectories of functional homotopy. The Journal of Neurosciences, 2010; 30(45):15034-15043.