Chinese Color Nest Project: Growing up in China

Yang, Ning; He, Ye; Zhang, Zhe; Dong, Hao-Ming; Zhang, Lei; Zhu, Xing-Ting; Hou, Xiaohui; Wang, Yinshan; Zhou, Quan; Gong, Zhu-Qing; Cao, Lizhi; Wang, Ping; Zhang, YiWeng; Sui, Danyang; Xu, Ting; Wei, Gao-Xia; Yang, Zhi; Jiang, Lili; Li, Huijie; Feng, Tingyong; Chen, Antao; Qiu, Jiang; Chen, Xu; Zuo, Xi‐Nian

doi:10.1360/n972017-00362

Cited by 28 publications

(23 citation statements)

References 28 publications

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“…We recruited 94 participants (47 females) between 3 to 16 years of age as part of the 152 Chinese Color Nest Project [39,48], a long-term (2013-2022) large-scale effort on 153 normative research for lifespan development of mind and brain (CLIMB) [9]. All 154 participants were from groups visiting during the Public Science Open Day of the 155 Chinese Academy of Sciences, with the approval of at least one legal guardian.…”

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confidence: 99%

DREAM: A Toolbox to Decode Rhythms of the Brain System

Gong

Gao

Jiang

et al. 2020

Preprint

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Rhythms of the brain are generated by neural oscillations across multiple frequencies.Following the natural log linear law of frequency distribution, these oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. This perspective on neural oscillations has been increasingly applied to study human brain function and related behaviors. In practice, relevant signals are commonly measured as a discrete time series, and thus the sampling period and number of samples determine the number and ranges of decodable frequency intervals. However, these limits have been often ignored by researchers who instead decode measured oscillations into multiple frequency intervals using a fixed sample period and numbers of samples. One reason for such misuse is the lack of an easy-to-use toolbox to implement automatic decomposition of frequency intervals. We report on a toolbox with a graphical user interface for achieving local and remote decoding rhythms of the brain system (DREAM) which is accessible to the public via GITHUB. We provide worked examples of DREAM used to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. Using the imaging data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands as well as their test-retest reliability. DREAM analyzed the head motion oscillation and found that younger children moved their heads more than older ones across all five frequency intervals, particularly in the higher frequency intervals. In the age interval from 7 to 9 years, boys moved more than girls across all frequency intervals. Such sex-related motion effects were not detectable for other ages. These findings demonstrate the applicability of DREAM for frequency-specific human brain mapping.

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confidence: 99%

DREAM: A Toolbox to Decode Rhythms of the Brain System

Gong

Gao

Jiang

et al. 2020

Preprint

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“…For a growing number of longitudinal neuroimaging cohort studies across the globe in recent years [24][25][26][27][28]40,41 , identification of typical developmental patterns is one of the primary research targets. The absence of a standard protocol impedes generalization between ethnic backgrounds, imaging settings and data processing procedures.…”

Section: Applications Of the Methodsmentioning

confidence: 99%

“…Volumetric measurements were quantified with aMRI of 674 school-age brains from two accelerated longitudinal cohorts with the same experimental design obtained in the United States (Enhanced Nathan Kline Institute Rockland Sample -eNKI sample) 40 and China (Chinese Color Nest Project -CCNP) 10,41 , respectively. Standard brain templates were constructed annually for each year of age and serve as a field-wide resource for generating growth charts on morphological development of brain tissues, lobes and networks.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, the SWU413 dataset was acquired as a trial stage implementation of the developmental phase of the Chinese Color Nest Project (CCNP-SWU413)10 , which is a five-year accelerated longitudinal study designed to delineate normative trajectories of brain development of Chinese children41 . The age and sex distributions of overall MRI scans for the three samples are listed inTable 1.…”

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confidence: 99%

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Generating Templates and Growth Charts for School-Aged Brain Development

Dong

Yang

Zhang

et al. 2019

Preprint

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Office/Fax: +86-10-64853798; Cell: +8613810191181 Standard brain templates and growth charts provide an invaluable resource for basic science research, with the eventual goal of contributing to the clinical care of neuropsychiatric conditions. Here, we report on a protocol to generate MRI brain templates in children and adolescents at one-year intervals from 6-to-18 years of age, with their corresponding growth charts, using a large-scale neuroimaging data resource (948 brain images from China and United States).To assure that the brain templates and growth charts are reliable and accurate, we developed a refined pipeline consisting of template construction, image registration, brain area labeling and growth chart modeling. The pipeline comprises multiple modular workflows that can be used for multiple applications. In our approach, population-and age-specific templates were first constructed to avoid systemic bias in registration. Brain areas were then labeled based on the appropriate templates, and their morphological metrics were extracted for modeling associated growth curves. We implemented warp cost as a function of age differences between individual brains and template brains. A strong U-shaped cost function was revealed, indicating larger age differences are associated with greater registration errors. This validates the necessity of age-specific reference templates in pediatric brain imaging studies. Growth chart analyses revealed preferential shape differences between Chinese and US samples in lateral frontal and parietal areas, aspects of cortex which are most variable across individuals with regard to structure and function as well as associated behavioral performance. This growth distinction is largely driven by neurodevelopmental differences between Chinese and US age-specific brain templates. The pipeline together with the brain templates and charts are publicly available and integrated into the Connectome Computation System.

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“…The team will use these data to model the normal neurodevelopmental trajectory for Chinese individuals across the life span. The CCNP will be integrated into the national Chinese Brain Project (Yang et al, ).…”

Section: Policies and Practices Related To Educational Neurosciencementioning

confidence: 99%

Education and visual neuroscience: A mini‐review

Chen

2019

PsyCh Journal

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Neuroscience, especially visual neuroscience, is a burgeoning field that has greatly shaped the format and efficacy of education. Moreover, findings from visual neuroscience are an ongoing source of great progress in pedagogy. In this mini‐review, I review existing evidence and areas of active research to describe the fundamental questions and general applications for visual neuroscience as it applies to education. First, I categorize the research questions and future directions for the role of visual neuroscience in education. Second, I juxtapose opposing views on the roles of neuroscience in education and reveal the “neuromyths” propagated under the guise of educational neuroscience. Third, I summarize the policies and practices applied in different countries and for different age ranges. Fourth, I address and discuss the merits of visual neuroscience in art education and of visual perception theories (e.g., those concerned with perceptual organization with respect to space and time) in reading education. I consider how vision‐deprived students could benefit from current knowledge of brain plasticity and visual rehabilitation methods involving compensation from other sensory systems. I also consider the potential educational value of instructional methods based on statistical learning in the visual domain. Finally, I outline the accepted translational framework for applying findings from educational neuroscience to pedagogical theory.

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Chinese Color Nest Project: Growing up in China

Cited by 28 publications

References 28 publications

DREAM: A Toolbox to Decode Rhythms of the Brain System

DREAM: A Toolbox to Decode Rhythms of the Brain System

Generating Templates and Growth Charts for School-Aged Brain Development

Education and visual neuroscience: A mini‐review

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