A practical guide for researchers and reviewers using the ABCD Study and other large longitudinal datasets

Developmental Cognitive Neuroscience, Journal Year: 2022, Volume and Issue: 55, P. 101115 - 101115

Published: May 20, 2022

As the largest longitudinal study of adolescent brain development and behavior to date, Adolescent Brain Cognitive Development (ABCD) Study® has provided immense opportunities for researchers across disciplines since its first data release in 2018. The size scope also present a number hurdles, which range from becoming familiar with design structure employing rigorous reproducible analyses. current paper is intended as guide reviewers working ABCD data, highlighting features (and strengths limitations therein) well relevant analytical methodological considerations. Additionally, we explore justice, equity, diversity, inclusion efforts they pertain Study other large-scale datasets. In doing so, hope increase both accessibility transparency within field developmental cognitive neuroscience.

Language: Английский

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Individual differences in computational psychiatry: A review of current challenges

Neuroscience & Biobehavioral Reviews, Journal Year: 2023, Volume and Issue: 148, P. 105137 - 105137

Published: March 20, 2023

Bringing precision to the understanding and treatment of mental disorders requires instruments for studying clinically relevant individual differences. One promising approach is development computational assays: integrating models with cognitive tasks infer latent patient-specific disease processes in brain computations. While recent years have seen many methodological advancements modelling cross-sectional patient studies, much less attention has been paid basic psychometric properties (reliability construct validity) measures provided by assays. In this review, we assess extent issue examining emerging empirical evidence. We find that suffer from poor properties, which poses a risk invalidating previous findings undermining ongoing research efforts using assays study (and even group) provide recommendations how address these problems and, crucially, embed them within broader perspective on key developments are needed translating clinical practice.

Language: Английский

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The MR neuroimaging protocol for the Accelerating Medicines Partnership® Schizophrenia Program

Schizophrenia, Journal Year: 2025, Volume and Issue: 11(1)

Published: April 2, 2025

Abstract Neuroimaging with MRI has been a frequent component of studies individuals at clinical high risk (CHR) for developing psychosis, goals understanding potential brain regions and systems impacted in the CHR state identifying prognostic or predictive biomarkers that can enhance our ability to forecast outcomes. To date, most involving are likely not sufficiently powered generate robust generalizable neuroimaging results. Here, we describe prospective, advanced, modern protocol was implemented complex multi-site, multi-vendor environment, as part large-scale Accelerating Medicines Partnership® Schizophrenia Program (AMP® SCZ), including rationale various choices. This includes T1- T2-weighted structural scans, resting-state fMRI, diffusion-weighted imaging collected two time points, approximately 2 months apart. We also present preliminary variance analyses several measures, such signal- contrast-to-noise ratio (SNR/CNR) spatial smoothness, provide quantitative data on relative percentages participant, site, platform (i.e., scanner model) variance. Site-related is generally small (typically <10%). For SNR/CNR measures from fMRI participant largest (as desired; 40–76%). However, diffusion there substantial platform-related (>55%) due differences hardware capabilities different scanners. Also, smoothness large inherent, difficult control, between vendors their acquisitions reconstructions. These results illustrate some factors will need be considered AMP SCZ data, which cohort date. Watch Dr. Harms discuss this article https://vimeo.com/1059777228?share=copy#t=0 .

Language: Английский

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The Amygdala and Depression: A Sober Reconsideration

American Journal of Psychiatry, Journal Year: 2022, Volume and Issue: 179(7), P. 454 - 457

Published: July 1, 2022

Language: Английский

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Stability, change, and reliable individual differences in electroencephalography measures: A lifespan perspective on progress and opportunities

NeuroImage, Journal Year: 2023, Volume and Issue: 275, P. 120116 - 120116

Published: May 9, 2023

Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency test-retest reliability, constrain their ability differentiate individuals successfully. Rapid recent technological computational advancements research make it timely revisit topic reliability context difference analyses. Moreover, pediatric samples provide some most salient urgent opportunities apply approaches, but changes these populations experience over time also unique challenges from a perspective. Here we take developmental neuroscience perspective consider progress new for parsing stability measurements across lifespan. We first conceptually map different profiles measurement expected types analyses Next, summarize evaluate state field's empirical knowledge need testing measures power, event-related potentials, nonlinearity, functional connectivity ages. Finally, highlight how standardized pre-processing software denoising metrics data quality may be used further improve EEG-based moving forward. include recommendations resources throughout that researchers can implement utility reproducibility with

Language: Английский

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Application of Deep Learning for Prediction of Alzheimer’s Disease in PET/MR Imaging

Bioengineering, Journal Year: 2023, Volume and Issue: 10(10), P. 1120 - 1120

Published: Sept. 24, 2023

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging promising technique combines the advantages PET and MR to provide both functional structural information brain. Deep learning (DL) subfield machine (ML) artificial intelligence (AI) focuses on developing algorithms models inspired by structure function human brain's neural networks. DL has been applied various aspects PET/MR in AD, such as image segmentation, reconstruction, diagnosis prediction, visualization pathological features. In this review, we introduce basic concepts types algorithms, feed forward networks, convolutional recurrent autoencoders. We then summarize current applications challenges discuss future directions opportunities for automated diagnosis, predictions models, personalized medicine. conclude great potential improve quality efficiency new insights into pathophysiology treatment devastating disease.

Language: Английский

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Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity

JAMA Psychiatry, Journal Year: 2024, Volume and Issue: 81(4), P. 414 - 414

Published: Feb. 7, 2024

Importance In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in neurobiology of addiction. However, no FDCR-derived biomarkers been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment FDCR literature evidence, its heterogeneity, and an evaluation possible uses biomarkers. Objective To summarize state field FDCR, assess their potential biomarker development, outline clear process qualification to guide future research validation efforts. Evidence Review The PubMed Medline databases were searched every original investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, task whether each provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, severity 1 more addictive disorders. Findings There 415 between 1998 Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), cocaine (46 [11.1%]), most used visual cues (354 [85.3%]). Together, these recruited 19 311 participants, including 13 812 individuals with past current substance use could support diagnostic (143 [32.7%]), response (141 [32.3%]), (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), susceptibility (2 [0.5%]) A total 155 interventional mostly investigate pharmacological (67 [43.2%]) cognitive/behavioral (51 [32.9%]) interventions; 141 as measure, which 125 (88.7%) reported significant alterations; intervention outcome predictor, 24 (96%) finding associations markers outcomes. Conclusions Relevance Based review proposed framework, there is pathway regulatory FDCR-based addiction recovery. Further measures, accelerating improving judgments.

Language: Английский

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Leveraging the adolescent brain cognitive development study to improve behavioral prediction from neuroimaging in smaller replication samples

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(6)

Published: May 15, 2024

Neuroimaging is a popular method to map brain structural and functional patterns complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from resting state magnetic resonance imaging (MRI). We leverage baseline data thousands children in the Adolescent Brain Cognitive DevelopmentSM Study inform replication sample size required with univariate multivariate methods across different modalities detect reproducible brain-behavior associations. demonstrate that by applying high-dimensional data, we can capture lower dimensional architecture correlate robustly phenotypes are only 41 individuals working memory-related MRI, ~ 100 subjects MRI. Even random re-samplings discovery, be adequately powered 66 cognition memory task These results point an important role neuroimaging translational neurodevelopmental research showcase how findings large samples associations small sizes at heart many programs grants.

Language: Английский

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Investigative Approaches to Resilient Emotion Regulation Neurodevelopment in a South African Birth Cohort

Biological Psychiatry Global Open Science, Journal Year: 2025, Volume and Issue: 5(3), P. 100457 - 100457

Published: Jan. 31, 2025

Language: Английский

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Differences in the functional brain architecture of sustained attention and working memory in youth and adults

PLoS Biology, Journal Year: 2022, Volume and Issue: 20(12), P. e3001938 - e3001938

Published: Dec. 21, 2022

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development unknown. We characterized functional architecture of SA WM 9- to 11-year-old children adults. First, we found that adult network predictors generalized predict individual differences fluctuations youth. A model predicted performance both across within children-and captured later recognition memory-but underperformed youth relative next connections differentially related compared Results revealed 2 configurations: a dominant predicting age groups secondary architecture, more prominent for than SA, each group differently. Thus, connectivity (FC) predicts youth, with differing between youths adults those SA.

Language: Английский

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