Author
Finnegan J. Calabro
Other affiliations: Boston University
Bio: Finnegan J. Calabro is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Medicine & Cognition. The author has an hindex of 15, co-authored 57 publications receiving 1001 citations. Previous affiliations of Finnegan J. Calabro include Boston University.
Topics: Medicine, Cognition, Psychology, Neuroscience, Prefrontal cortex
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TL;DR: In this article , the authors used three of the largest neuroimaging datasets currently available, with a total sample size of around 50,000 individuals, to quantify brain-wide association studies effect sizes and reproducibility as a function of sample size.
Abstract: Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
611 citations
TL;DR: In this paper , the authors used three of the largest neuroimaging datasets currently available, with a total sample size of around 50,000 individuals, to quantify brain-wide association studies effect sizes and reproducibility as a function of sample size.
Abstract: Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
520 citations
University of California, San Diego1, McGill University2, Oregon Health & Science University3, Florida International University4, Yale University5, Washington University in St. Louis6, Virginia Commonwealth University7, University of Vermont8, University of Michigan9, Medical University of South Carolina10, National Institutes of Health11, SRI International12, University of Southern California13, McGovern Institute for Brain Research14, Harvard University15, Medical College of Wisconsin16, University of California, Irvine17, University of California, Los Angeles18, University of California, San Francisco19, University of Colorado Boulder20, University of Florida21, University of Maryland, Baltimore22, University of Massachusetts Boston23, University of Minnesota24, University of Pittsburgh25, University of Rochester26, University of Tennessee27, University of Utah28, University of Wisconsin–Milwaukee29, United States Department of Veterans Affairs30, Boston University31
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the Adolescent Brain Cognitive Development Study are described to be a resource of unprecedented scale and depth for studying typical and atypical development.
431 citations
University of California1, McGill University2, Oregon Health & Science University3, Florida International University4, Yale University5, University of Washington6, Virginia Commonwealth University7, University of Vermont8, University of Michigan9, Medical University of South Carolina10, National Institute on Drug Abuse11, SRI International12, Children's Hospital Los Angeles13, National Institutes of Health14, McGovern Institute for Brain Research15, Harvard University16, Medical College of Wisconsin17, University of Colorado Boulder18, University of Florida19, University of Maryland, Baltimore20, University of Massachusetts Amherst21, University of Minnesota22, University of Pittsburgh23, University of Rochester24, University of Tennessee25, University of Utah26, University of Wisconsin–Milwaukee27, Boston University28
TL;DR: The baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes are described.
Abstract: The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The ABCD Study is a collaborative effort, including a Coordinating Center, 21 data acquisition sites across the United States, and a Data Analysis and Informatics Center (DAIC). The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data will provide a resource of unprecedented scale and depth for studying typical and atypical development. Here, we describe the baseline neuroimaging processing and subject-level analysis methods used by the ABCD DAIC in the centralized processing and extraction of neuroanatomical and functional imaging phenotypes. Neuroimaging processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI.
276 citations
TL;DR: It is shown that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure, and large consortia are needed to usher in a new era of reproducible human brain-wide association studies.
Abstract: Magnetic resonance imaging (MRI) continues to drive many important neuroscientific advances. However, progress in uncovering reproducible associations between individual differences in brain structure/function and behavioral phenotypes (e.g., cognition, mental health) may have been undermined by typical neuroimaging sample sizes (median N=25)1,2. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study3 (N=11,878), we estimated the effect sizes and reproducibility of these brain-wide associations studies (BWAS) as a function of sample size. The very largest, replicable brain-wide associations for univariate and multivariate methods were r=0.14 and r=0.34, respectively. In smaller samples, typical for brain-wide association studies (BWAS), irreproducible, inflated effect sizes were ubiquitous, no matter the method (univariate, multivariate). Until sample sizes started to approach consortium-levels, BWAS were underpowered and statistical errors assured. Multiple factors contribute to replication failures4–6; here, we show that the pairing of small brain-behavioral phenotype effect sizes with sampling variability is a key element in wide-spread BWAS replication failure. Brain-behavioral phenotype associations stabilize and become more reproducible with sample sizes of N⪆2,000. While investigator-initiated brain-behavior research continues to generate hypotheses and propel innovation, large consortia are needed to usher in a new era of reproducible human brain-wide association studies.
175 citations
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9,362 citations
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or
7,563 citations
TL;DR: In this paper, the authors offer a new book that enPDFd the perception of the visual world to read, which they call "Let's Read". But they do not discuss how to read it.
Abstract: Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd the perception of the visual world to read.
2,250 citations
TL;DR: In this article , the authors used three of the largest neuroimaging datasets currently available, with a total sample size of around 50,000 individuals, to quantify brain-wide association studies effect sizes and reproducibility as a function of sample size.
Abstract: Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.
611 citations
TL;DR: The COVID-19 pandemic and lockdown may have a negative outcome on the mental health of adolescents, although there is still no data on the long term impact of this crisis.
Abstract: The aim of this paper was to review the literature on adolescent psychiatric disorders related to the COVID-19 pandemic and lockdown Stressful life events, extended home confinement, brutal grief, intrafamilial violence, overuse of the Internet and social media are factors that could influence the mental health of adolescents during this period The COVID-19 pandemic could result in increased psychiatric disorders such as Post-Traumatic Stress, Depressive, and Anxiety Disorders, as well as grief-related symptoms Adolescents with psychiatric disorders are at risk of a break or change in their care and management; they may experience increased symptoms The COVID-19 pandemic and lockdown may have a negative impact on the mental health of adolescents, although there is still no data on the long term impact of this crisis Adolescents' individual, familial, and social vulnerability, as well as individual and familial coping abilities, are factors related to adolescent mental health in times of crisis Adolescents are often vulnerable and require careful consideration by caregivers and healthcare system adaptations to allow for mental health support despite the lockdown Research on adolescent psychiatric disorders in times of pandemics is necessary, as such a global situation could be prolonged or repeated
595 citations