Brain functional connectivity and anatomical features as predictors of cognitive behavioral therapy outcome for anxiety in youths DOI
André Zugman, Grace Ringlein, Emily S. Finn

et al.

Psychological Medicine, Journal Year: 2025, Volume and Issue: 55

Published: Jan. 1, 2025

Abstract Background Because pediatric anxiety disorders precede the onset of many other problems, successful prediction response to first-line treatment, cognitive-behavioral therapy (CBT), could have a major impact. This study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT symptoms. Methods Two datasets were studied: (A) one consisted n = 54 subjects with an diagnosis, who received 12 weeks CBT, (B) 15 treated for 8 weeks. Connectome predictive modeling (CPM) was used treatment response, as assessed PARS. The main analysis included network edges positively correlated outcome age, sex, baseline severity predictors. Results from alternative models analyses are also presented. Model assessments utilized 1000 bootstraps, resulting in 95% CI R 2 , r mean absolute error (MAE). model showed MAE approximately 3.5 (95% CI: [3.1–3.8]) points, 0.08 [−0.14–0.26], 0.38 [0.24–0.511]. When testing this left-out sample (B), results similar, 3.4 [2.8–4.7], −0.65 [−2.29–0.16], 0.4 [0.24–0.54]. anatomical metrics similar pattern, where rendered overall low . Conclusions that based on earlier promising failed clinical outcomes. Despite small size, does not support extensive use CPM outcomes anxiety.

Language: Английский

Functional Connectome–Based Predictive Modeling in Autism DOI
Corey Horien, Dorothea L. Floris, Abigail S. Greene

et al.

Biological Psychiatry, Journal Year: 2022, Volume and Issue: 92(8), P. 626 - 642

Published: April 26, 2022

Language: Английский

Citations

32
Replication of a neuroimaging biomarker for striatal dysfunction in psychosis DOI
José M. Rubio, Todd Lencz, Hengyi Cao

et al.

Molecular Psychiatry, Journal Year: 2024, Volume and Issue: 29(4), P. 929 - 938

Published: Jan. 4, 2024

Language: Английский

Citations

6
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance DOI
Yuqian Chen, Leo Zekelman, Chaoyi Zhang

et al.

Medical Image Analysis, Journal Year: 2024, Volume and Issue: 94, P. 103120 - 103120

Published: Feb. 23, 2024

Language: Английский

Citations

6
White matter association tracts underlying language and theory of mind: An investigation of 809 brains from the Human Connectome Project DOI Creative Commons
Leo Zekelman, Fan Zhang, Nikos Makris

et al.

NeuroImage, Journal Year: 2021, Volume and Issue: 246, P. 118739 - 118739

Published: Nov. 29, 2021

Language and theory of mind (ToM) are the cognitive capacities that allow for successful interpretation expression meaning. While functional MRI investigations able to consistently localize language ToM specific cortical regions, diffusion point an inconsistent sometimes overlapping set white matter tracts associated with these two domains. To further examine may underlie domains, we use a two-tensor tractography method investigate microstructure 809 participants from Human Connectome Project. 20 association (10 in each hemisphere) uniquely identified by leveraging neuroanatomist-curated automated tract atlas. The fractional anisotropy (FA), mean diffusivity (MD), number streamlines (NoS) measured tract. Performance on neuropsychological assessments semantic memory (NIH Toolbox Picture Vocabulary Test, TPVT) emotion perception (Penn Emotion Recognition PERT) used measure critical subcomponents networks, respectively. Regression models constructed how structural measurements left right influence performance across assessments. We find is influenced superior longitudinal fasciculus III (SLF-III), SLF-III. Additionally, both & FA arcuate (AF). results multiple, domains ToM. Results discussed terms hemispheric dominance concordance prior investigations.

Language: Английский

Citations

37
Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds DOI Creative Commons
Omid Kardan, Sydney Kaplan, Muriah D. Wheelock

et al.

Developmental Cognitive Neuroscience, Journal Year: 2022, Volume and Issue: 56, P. 101123 - 101123

Published: June 15, 2022

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize brain maturation in typically and atypically developing children adults. However, its reliability utility for predicting development infants toddlers is less well understood. Here, we use data from the Baby Connectome Project study measure uniqueness of rsFC predict age this sample (8-to-26 months old; n = 170). We observed medium within-session infant our sample, found that individual toddler’s connectomes were sufficiently distinct successful connectome fingerprinting. Next, trained tested support vector regression models age-at-scan rsFC. Models successfully predicted novel infants’ within ± 3.6 error a prediction R2 .51. To anatomy predictive networks, grouped connections into 11 infant-specific resting-state networks defined data-driven manner. between regions same network—i.e. within-network connections—predicted significantly better than between-network connections. Looking ahead, these findings can help changes organization infancy toddlerhood inform work developmental outcome measures range.

Language: Английский

Citations

24
Optimizing network neuroscience computation of individual differences in human spontaneous brain activity for test-retest reliability DOI Creative Commons
Chao Jiang, Ye He, Richard F. Betzel

et al.

Network Neuroscience, Journal Year: 2023, Volume and Issue: 7(3), P. 1080 - 1108

Published: Jan. 1, 2023

A rapidly emerging application of network neuroscience in neuroimaging studies has provided useful tools to understand individual differences intrinsic brain function by mapping spontaneous activity, namely functional (ifNN). However, the variability methodologies applied across ifNN studies-with respect node definition, edge construction, and graph measurements-makes it difficult directly compare findings also challenging for end users select optimal strategies networks. Here, we aim provide a benchmark best practices systematically comparing measurement reliability under different analytical using test-retest design Human Connectome Project. The results uncovered four essential principles guide studies: (1) use whole parcellation define nodes, including subcortical cerebellar regions; (2) construct networks activity multiple slow bands; (3) optimize topological economy at level; (4) characterize information flow with specific metrics integration segregation. We built an interactive online resource assessments future (https://ibraindata.com/research/ifNN).

Language: Английский

Citations

13
Connectome-based fingerprinting: reproducibility, precision, and behavioral prediction DOI
Jivesh Ramduny, Clare Kelly

Neuropsychopharmacology, Journal Year: 2024, Volume and Issue: 50(1), P. 114 - 123

Published: Aug. 15, 2024

Language: Английский

Citations

5
Higher-order connectomics of human brain function reveals local topological signatures of task decoding, individual identification, and behavior DOI Creative Commons
Andrea Santoro, Federico Battiston, Maxime Lucas

et al.

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

Published: Nov. 26, 2024

Abstract Traditional models of human brain activity often represent it as a network pairwise interactions between regions. Going beyond this limitation, recent approaches have been proposed to infer higher-order from temporal signals involving three or more However, day remains unclear whether methods based on inferred outperform traditional ones for the analysis fMRI data. To address question, we conducted comprehensive using time series 100 unrelated subjects Human Connectome Project. We show that greatly enhance our ability decode dynamically various tasks, improve individual identification unimodal and transmodal functional subsystems, strengthen significantly associations behavior. Overall, approach sheds new light organization series, improving characterization dynamic group dependencies in rest revealing vast space unexplored structures within data, which may remain hidden when approaches.

Language: Английский

Citations

5
Future directions for cognitive neuroscience in psychiatry: recommendations for biomarker design based on recent test re-test reliability work DOI
James Blair, Avantika Mathur, Nathaniel Haines

et al.

Current Opinion in Behavioral Sciences, Journal Year: 2022, Volume and Issue: 44, P. 101102 - 101102

Published: Feb. 24, 2022

Language: Английский

Citations

22
Investigating cognitive neuroscience theories of human intelligence: A connectome‐based predictive modeling approach DOI Creative Commons
Evan D. Anderson, Aron K. Barbey

Human Brain Mapping, Journal Year: 2022, Volume and Issue: 44(4), P. 1647 - 1665

Published: Dec. 20, 2022

Abstract Central to modern neuroscientific theories of human intelligence is the notion that general depends on a primary brain region or network, engaging spatially localized (rather than global) neural representations. Recent findings in network neuroscience, however, challenge this assumption, providing evidence may depend system‐wide mechanisms, suggesting local representations are necessary but not sufficient account for architecture intelligence. Despite importance key theoretical distinction, prior research has systematically investigated role versus global predicting We conducted large‐scale connectome‐based predictive modeling study ( N = 297), administering resting‐state fMRI and comprehensive cognitive battery evaluate efficacy intelligence, including (Lateral Prefrontal Cortex Theory, Parieto‐Frontal Integration Multiple Demand Theory) recent accounts (Process Overlap Theory Network Neuroscience Theory). The results our demonstrate can be predicted by functional connectivity profiles most robustly explained whole‐brain connectivity. Our further suggest improved reducible greater strength number connections, instead from considering both strong weak connections provide basis (as highlight context information‐processing architecture, future directions theory‐driven mechanisms underlying

Language: Английский

Citations

21