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Protocol: Generating Templates and Growth Charts for School-Aged Brain Development

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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
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Book: Casting Light on The Dark Side of Brain Imaging

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Most people find colorful brain scans highly compelling—and yet, many experts don’t. This discrepancy begs the question: What can we learn from neuroimaging? Is brain information useful in fields such as psychiatry, law, or education? How do neuroscientists create brain activation maps and why do we admire them? Casting Light on The Dark Side of Brain Imaging　tackles these questions through a critical and constructive lens—separating fruitful science from misleading neuro-babble. In a breezy writing style accessible to a wide readership, experts from across the brain sciences offer their uncensored thoughts to help advance brain research and debunk the craze for reductionist, headline-grabbing neuroscience. This collection of short, enlightening essays is suitable for anyone interested in brain science, from students to professionals. Together, we take a hard look at the science behind brain imaging and outline why this technique remains promising despite its seldom-discussed short
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Individual Differences: A Theory of Measurements

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We proposed a theoretical framework refining the concepts of reliability and validity in connecting  the classical measurement theory with individual variability [1]. Science has the mission to fill the gap from reliability to validity. Read more: [1]  Harnessing reliability for neuroscience research [ ShareIt ]
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Reading Note: A Reproducibility Manifesto

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In reading two papers about reproducibility published in Nature Human Behaviour [1,2], I posted this reading note in its 'A picture is worth a thousand words' version. Read more: [1]  A manifesto for reproducible science [2]  A visual tool for defining reproducibility and replicability
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CoRR: Theory Comment

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Neuroscientists are amassing the large-scale datasets needed to study individual differences and identify biomarkers. However, measurement reliability within individual samples is often suboptimal, thereby requiring unnecessarily large samples. We focus our comment on reliability in neuroimaging and provide examples of how the reliability can be increased.  Read more:  https://t.co/LlshxZXEqy?amp=1 https://www.nature.com/articles/s41562-019-0655-x A framework on measurement reliability
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CoRR: Perspective and Data Papers

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The Consortium for Reliability and Reproducibility (CoRR) is working to establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites. To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. This enables users to assess the impact of commonly encountered artifacts on characterizations of inter-individual variation, datasets of varying quality are included. Read More: [1] Perspective paper : Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics [2] Data paper : An open science resource for establishing reliability and reproducibility in functional connectomics [3]  Human Brain MRI Reproducibility Collection [4]  A testbed for reproducibl
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A Time of Computational Neuroscience Coming

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Today is the first day of 2010. I closed reading an excellent review paper " Computational and dynamic models in neuroimaging " which was in press in NeuroImage. In this review, from a perspective of mathematical modeling, Dr. Friston summarized those efforts on modeling brain's function and biophysics, which have extensively enriched the neuroimaging data exploration. Of particular importance, computational neuroscience now is tending to unify the resting-state and stimulus-invoked brain, which is an extremely important transition of neuroimaging research to go beyond understanding the human brain whatever rest or task involved. We can predict, in the future (e.g., see 2010 :), that the mining schemes from computational neuroscience, machine leaning and game theory will become pretty strong for both brain mechanism and prediction. In practice, two things might attract researchers: to develop a unify measure on brain dynamic, which means that the relevant measures shou
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