Author
M. Daniela Cornejo
Other affiliations: University of Wisconsin-Madison, Pontifical Catholic University of Chile, Oregon Health & Science University ...read more
Bio: M. Daniela Cornejo is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Cognitive development & Cognition. The author has an hindex of 7, co-authored 9 publications receiving 875 citations. Previous affiliations of M. Daniela Cornejo include University of Wisconsin-Madison & Pontifical Catholic University of Chile.
Papers
More filters
••
Cornell University1, Yale University2, Washington University in St. Louis3, University of Michigan4, University of Vermont5, University of Colorado Boulder6, Florida International University7, Virginia Commonwealth University8, University of Minnesota9, University of California, San Diego10, Harvard University11
TL;DR: An overview of the imaging procedures of the ABCD study is provided, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature are provided.
1,114 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, Boston University30, United States Department of Veterans Affairs31
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: For instance, this article found that negative self-focused thought (negative-SFT) is associated with depression and negative self focused thought (SFT was associated with increased resting-state functional connectivity (rsFC) for brain regions implicated in SFT.
Abstract: A central feature of major depression (MDD) is heightened negative self-focused thought (negative-SFT). Neuroscientific research has identified abnormalities in a network of brain regions in MDD, including brain areas associated with SFT such as medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC). To our knowledge no studies have investigated the behavioral and neural correlates of negative-SFT using a sentence completion task in a sample of individuals with varying depression histories and severities. We test the following hypotheses: (1) negative-SFT will be associated with depression; and (2) depression and negative-SFT will be related to resting-state functional connectivity (rsFC) for brain regions implicated in SFT. Seventy-nine women with varying depression histories and severities completed a sentence completion task and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Standard seed-based voxelwise rsFC was conducted for self-network regions of interest: dorsomedial PFC (dmPFC) and pregenual ACC (pgACC). We performed linear regression analyses to examine the relationships among depression, negative-SFT, and rsFC for the dmPFC and pgACC. Greater negative-SFT was associated with depression history and severity. Greater negative-SFT predicted increased rsFC between dmPFC and pgACC seeds and dorsolateral prefrontal (dlPFC) and parietal regions; depression group was also associated with increased pgACC-dlPFC connectivity. These findings are consistent with previous literature reporting elevated negative-SFT thought in MDD. Our rs-fMRI results provide novel support linking negative-SFT with increased rsFC between self-network and frontoparietal network regions across different levels of depression. Broadly, these findings highlight a dimension of social-affective functioning that may underlie MDD and other psychiatric conditions.
46 citations
••
TL;DR: Analysis of data from over 11,500 9- to 10-year-olds enrolled in the Adolescent Brain Cognitive Development Study establishes relationships between working memory, other cognitive abilities, and frontoparietal brain activity during a working memory challenge, but not during other cognitive challenges.
Abstract: Working memory function changes across development and varies across individuals. The patterns of behavior and brain function that track individual differences in working memory during human development, however, are not well understood. Here, we establish associations between working memory, other cognitive abilities, and functional MRI (fMRI) activation in data from over 11,500 9- to 10-year-old children (both sexes) enrolled in the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing longitudinal study in the United States. Behavioral analyses reveal robust relationships between working memory, short-term memory, language skills, and fluid intelligence. Analyses relating out-of-scanner working memory performance to memory-related fMRI activation in an emotional n-back task demonstrate that frontoparietal activity during a working memory challenge indexes working memory performance. This relationship is domain specific, such that fMRI activation related to emotion processing during the emotional n-back task, inhibitory control during a stop-signal task (SST), and reward processing during a monetary incentive delay (MID) task does not track memory abilities. Together, these results inform our understanding of individual differences in working memory in childhood and lay the groundwork for characterizing the ways in which they change across adolescence.SIGNIFICANCE STATEMENT Working memory is a foundational cognitive ability that changes over time and varies across individuals. Here, we analyze data from over 11,500 9- to 10-year-olds to establish relationships between working memory, other cognitive abilities, and frontoparietal brain activity during a working memory challenge, but not during other cognitive challenges. Our results lay the groundwork for assessing longitudinal changes in working memory and predicting later academic and other real-world outcomes.
44 citations
Cited by
More filters
••
9,362 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: 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
•
TL;DR: Clark, Beck, and Alford as mentioned in this paper provide a comprehensive review of the literature pertaining to the key hypotheses of the cognitive model of depression and provide a valuable source companion to the classic but outdated treatment manual originally published in 1979 by Dr. Beck and colleagues (Cognitive Therapy of Depression) and the excellent how-to book, Cognitive Therapy: Basics and Beyond, which was published in 1995.
Abstract: Although there are dozens of books on cognitive therapy of depression, a majority are edited volumes and relatively few are distinguished by the comprehensive mastery of the material and clarity of exposition apparent in this book by Clark, Beck, and Alford. This volume offers a relatively up-to-date (circa 1999) and scholarly review of the phenomenology of depressive disorders from the cognitive perspective, along with detailed evaluations of the literature pertaining to the key hypotheses of the cognitive model of depression.
The book is well written, but it is not for the cognitive therapy neophyte. It is rather lengthy and detailed. Moreover, as might be expected, the discussions of criticisms of the cognitive model are somewhat partisan, and the authors consistently present the cognitive model as dynamic and organic (as opposed to static) in response to new and at times contradictory data. Nevertheless, it provides a valuable source companion to the classic but outdated treatment manual originally published in 1979 by Dr. Beck and colleagues (Cognitive Therapy of Depression) and the excellent how-to book by Dr. Judith Beck, Cognitive Therapy: Basics and Beyond, which was published in 1995.
Subheads, periodic summaries, and statements of key points within each chapter focus the reader's attention and enhance comprehension; the authors are, after all, expert cognitive therapists. There is a minimum of redundancy across the 11 chapters, and although the copyediting is not infallible (e.g., influential early behaviorist Charles Ferster is referred to as “Fester” in both the text and the reference list), typographical errors are few.
As a treatment researcher, I was disappointed that the authors did not devote at least one chapter to reviewing the comparative outcome research studies of CT. Outcomes data has been one of the key aspects of the scientific foundation of CT for nearly 25 years.1 This is a shortcoming, particularly in view of work linking early evidence of CT's superiority (over other therapies) to strong allegiance effects2 and the increasing number of studies in which CT has not performed so well under more “neutral”3,4 or even potentially “allegiance-disadvantaged”5–7 conditions. Ultimately, the most pragmatic benefit of an elegant, scientifically strong model of psychopathology is the ability to translate such knowledge into greater or more enduring benefits for our patients. In this regard, it is not yet clear that the elaborate suprastructure of schema theory actually adds such benefits relative to simpler behavioral5 or interpersonal6 models of intervention.
457 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, Boston University30, United States Department of Veterans Affairs31
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