Individual Differences in Computational Psychiatry: A Review of Current Challenges DOI Open Access
Povilas Karvelis, Martin P. Paulus, Andreea O. Diaconescu

et al.

Published: Dec. 11, 2022

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. To contextualize this, also provide a more general perspective on key developments that are needed translating assays clinical practice. Emerging evidence suggests most show poor-to-moderate reliability often little improvement over simple behavioral measures. Furthermore, used test accounts lack convergent validity, which compromises their interpretability. Taken together, these issues pose risk invalidating previous findings undermining ongoing research efforts using study (and even group) We suggest single-task designs, currently dominate landscape, partly blame problems therefore not suitable solving them. Instead, validity need be studied systematically longitudinal designs batteries tasks. Finally, enable applications, it will necessary establish predictive make efficient burdensome.

Language: Английский

Improving the Reliability of Cognitive Task Measures: A Narrative Review DOI Creative Commons
Samuel Zorowitz, Yael Niv

Biological Psychiatry Cognitive Neuroscience and Neuroimaging, Journal Year: 2023, Volume and Issue: 8(8), P. 789 - 797

Published: Feb. 25, 2023

Language: Английский

Citations

52
Individual differences in computational psychiatry: A review of current challenges DOI Creative Commons
Povilas Karvelis, Martin P. Paulus, Andreea O. Diaconescu

et al.

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

Citations

49
The Burden of Reliability: How Measurement Noise Limits Brain-Behaviour Predictions DOI Creative Commons
Martin Gell, Simon B. Eickhoff, Amir Omidvarnia

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 10, 2023

Abstract Major efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. An essential prerequisite identifying generalizable replicable brain-behaviour prediction models is sufficient measurement reliability. However, the selection of targets predominantly guided scientific interest or data availability rather than reliability considerations. Here we demonstrate impact low phenotypic on out-of-sample performance. Using simulated empirical Human Connectome Projects, found that levels common across many can markedly limit ability link behaviour. Next, using 5000 subjects UK Biobank, show only highly reliable fully benefit increasing sample sizes hundreds thousands participants. Overall, our findings highlight importance brain–behaviour associations differences.

Language: Английский

Citations

43
Dextrose gel prophylaxis for neonatal hypoglycaemia and neurocognitive function at early school age: a randomised dosage trial DOI
Xingyu Wei, Nike Franke, Jane M. Alsweiler

et al.

Archives of Disease in Childhood Fetal & Neonatal, Journal Year: 2024, Volume and Issue: 109(4), P. 421 - 427

Published: Feb. 2, 2024

Objective To investigate the effect of different doses prophylactic dextrose gel on neurocognitive function and health at 6–7 years. Design Early school-age follow-up pre-hPOD (hypoglycaemia Prevention with Oral Dextrose) study. Setting Schools communities. Patients Children born ≥35 weeks ≥1 risk factor for neonatal hypoglycaemia: maternal diabetes, small or large gestational age, late preterm. Interventions Four interventions commencing 1 hour age: (40%) 200 mg/kg; 400 mg/kg repeated before three feeds (800 mg/kg); (1000 compared equivolume placebo (combined analysis). Main outcomes measures Toolbox cognitive motor batteries, as well tests motion perception, numeracy cardiometabolic health, were used. The primary outcome was impairment, defined a standard score more than SD below age-corrected mean one tests. Findings Of 392 eligible children, 309 assessed outcome. There no significant differences in rate impairment between those randomised to (56%) (200 46%: adjusted difference (aRD)=−14%, 95% CI −35%, 7%; 48%: aRD=−7%, −27%, 12%; 800 45%: aRD=−14%, −36%, 9%; 1000 50%: aRD=−8%, −29%, 13%). exposed any dose (combined), placebo, had lower (3% vs 14%, aRD=-11%, −19%, −3%) higher (SD) scores (106.0 (15.3) 101.1 (15.7), difference=5.4, 1.8, 8.9). Conclusions Prophylactic did not alter early school age but may have benefits. Further studies are needed.

Language: Английский

Citations

6
Genetic and Environmental Variation in Continuous Phenotypes in the ABCD Study® DOI Creative Commons
Hermine H. Maes, Dana M. Lapato, J. Eric Schmitt

et al.

Behavior Genetics, Journal Year: 2022, Volume and Issue: 53(1), P. 1 - 24

Published: Nov. 10, 2022

Abstract Twin studies yield valuable insights into the sources of variation, covariation and causation in human traits. The ABCD Study® (abcdstudy.org) was designed to take advantage four universities known for their twin research, neuroimaging, population-based sampling, expertise genetic epidemiology so that representative could be performed. In this paper we use data to: (i) provide initial estimates heritability wide range phenotypes assessed Study using a consistent direct variance estimation approach, assuring both methodology are sound; (ii) an online resource researchers can serve as reference point future behavior publicly available dataset. Data were analyzed from 772 pairs twins aged 9–10 years at study inception, with zygosity determined genotypic data, recruited hub sites. tool provides correlations standardized unstandardized additive genetic, environmental variation 14,500 continuously distributed phenotypic features, including: structural functional neurocognition, personality, psychopathology, substance propensity, physical, trait variables. obtained unconstrained they incorporated directly meta-analyses without upwardly biasing aggregate estimates. results indicated broad consistency prior literature where provided novel or those different ages. Effects site, self-identified race/ethnicity, age sex statistically controlled. Results modeling all 53,172 continuous variables, including 38,672 MRI will accessible via user-friendly open-access web interface have established, updated new released Study. This overview embedded within Study, introduction primary research domains methodology, evaluation findings focus on quality suitability introductory material is recognition multidisciplinary appeal While focuses univariate analyses, emphasize opportunities multivariate, developmental causal well evaluating heterogeneity by key moderators such sex, demographic factors background.

Language: Английский

Citations

26
Construct validity of the NIH toolbox cognitive domains: A comparison with conventional neuropsychological assessments. DOI Creative Commons
Lauren R. Ott, Mikki Schantell,

Madelyn P. Willett

et al.

Neuropsychology, Journal Year: 2022, Volume and Issue: 36(5), P. 468 - 481

Published: April 28, 2022

Previous studies have assessed the construct validity of individual subtests in National Institutes Health (NIH) Toolbox Cognition Battery (NIHTB-CB), though none examined cognitive domains. Importantly, original NIHTB-CB validation were administered on a desktop computer, is now solely via an iPad. We each domain NIHTB-CB, including motor dexterity using iPad application compared to neuropsychological battery sample healthy adults.

Language: Английский

Citations

21
Childhood Listening and Associated Cognitive Difficulties Persist Into Adolescence DOI
Katsuaki Kojima, Lin Li, Lauren Petley

et al.

Ear and Hearing, Journal Year: 2024, Volume and Issue: 45(5), P. 1252 - 1263

Published: May 20, 2024

Listening difficulty (LiD) refers to the challenges individuals face when trying hear and comprehend speech other sounds. LiD can arise from various sources, such as hearing sensitivity, language comprehension, cognitive function, or auditory processing. Although some children with have loss, many clinically normal audiometric thresholds. To determine impact of factors on in a audiogram, we conducted longitudinal study. The Evaluation Children's & Processing Skills (ECLiPS), validated standardized caregiver evaluation tool, was used group participants either typically developing (TD). Our previous study aimed characterize 6- 13-year-old during project's baseline, cross-sectional phase. We found that needed higher signal-to-noise ratio speech-in-speech tests scored lower all assessed components NIH Cognition Toolbox than TD children. primary goal this examine if differences between groups are temporary enduring throughout childhood.

Language: Английский

Citations

4
Regional, but not brain-wide, graph theoretic measures are robustly and reproducibly linked to general cognitive ability DOI
M. Fiona Molloy, Aman Taxali, Mike Angstadt

et al.

Cerebral Cortex, Journal Year: 2025, Volume and Issue: 35(4)

Published: April 1, 2025

Abstract General cognitive ability (GCA), also called “general intelligence,” is thought to depend on network properties of the brain, which can be quantified through graph theoretic measures such as small worldness and module degree. An extensive set studies examined links between GCA graphical resting state connectomes. However, these often involved samples, applied just a few theory in each study, yielded inconsistent results, making it challenging identify architectural underpinnings GCA. Here, we address limitations by systematically investigating univariate multivariate relationships 17 whole-brain node-level individuals from Adolescent Brain Cognitive Development Study (n = 5937). We demonstrate that measures, including global efficiency, fail exhibit meaningful with In contrast, multiple especially degree (within-network connectivity), strong associations establish robustness results replicating them second large sample, Human Connectome Project 847), across variety modeling choices. This study provides most comprehensive definitive account date complex interrelationships brain’s intrinsic functional architecture.

Language: Английский

Citations

0
Using the Mobile Toolbox in child and adolescent samples: A feasibility study DOI Creative Commons
Stephanie Ruth Young, Miriam A. Novack, Elizabeth M. Dworak

et al.

Child Development, Journal Year: 2024, Volume and Issue: 95(4), P. 1416 - 1424

Published: Jan. 13, 2024

Cognitive research with developmental samples requires improved methods that support large-scale, diverse, and open science. This paper offers initial evidence to the Mobile Toolbox (MTB), a self-administered remote smartphone-based cognitive battery, in youth populations, from pilot sample of 99 children (M

Language: Английский

Citations

3
How measurement noise limits the accuracy of brain-behaviour predictions DOI Creative Commons
Martin Gell, Simon B. Eickhoff, Amir Omidvarnia

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Dec. 12, 2024

Abstract Major efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. To identify generalisable replicable brain-behaviour prediction models, sufficient measurement reliability is essential. However, the selection of targets predominantly guided scientific interest or data availability rather than psychometric considerations. Here, we demonstrate impact low on out-of-sample performance. Using simulated empirical four large-scale datasets, that levels common across many can markedly limit ability link behaviour. Next, using 5000 participants UK Biobank, show only highly reliable fully benefit increasing sample sizes hundreds thousands participants. Our findings highlight importance identifying meaningful brain–behaviour associations underscore need greater emphasis psychometrics future research.

Language: Английский

Citations

3