A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth DOI Creative Commons
Corey Horien, Abigail S. Greene, Xilin Shen

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: July 25, 2022

Abstract Difficulty with attention is an important symptom in many conditions psychiatry, including neurodiverse such as autism. There a need to better understand the neurobiological correlates of and leverage these findings for individuals healthcare settings. Nevertheless, it remains unclear if possible build robust dimensional predictive models populations. Here, we use five datasets identify validate functional connectome-based markers attention. In dataset one, modelling observe successful prediction performance on in-scan sustained task sample youth. The predictions are not driven by confounds, head motion. two, find network model defined one generalizes predict separate neurotypical participants performing same task. three five, identification longitudinal scans probe stability across months years individual participants. Our results help elucidate brain youth support further development other clinically-relevant phenotypes.

Language: Английский

Brain connectivity in frailty: Insights from The Irish Longitudinal Study on Ageing (TILDA) DOI Creative Commons
Raquel Gutiérrez-Zúñiga, James Davis, Rory Boyle

et al.

Neurobiology of Aging, Journal Year: 2023, Volume and Issue: 124, P. 1 - 10

Published: Jan. 7, 2023

Frailty in older adults is associated with greater risk of cognitive decline. Brain connectivity insights could help understand the association, but studies are lacking. We applied connectome-based predictive modeling to a 32-item self-reported Index (FI) using resting state functional MRI data from The Irish Longitudinal Study on Ageing. A total 347 participants were included (48.9% male, mean age 68.2 years). From modeling, we obtained 204 edges that positively correlated FI and composed "frailty network" characterised by visual network (right); 188 negatively formed "robustness characterized basal ganglia. Both networks' highest degree node was caudate different patterns: frailty network; default mode robustness network. walking speed not metrics global cognition, reinforcing matching between brain pattern found (main predicted ganglia).

Language: Английский

Citations

6
A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth DOI
Corey Horien, Abigail S. Greene, Xilin Shen

et al.

Cerebral Cortex, Journal Year: 2022, Volume and Issue: 33(10), P. 6320 - 6334

Published: Dec. 27, 2022

Abstract Difficulty with attention is an important symptom in many conditions psychiatry, including neurodiverse such as autism. There a need to better understand the neurobiological correlates of and leverage these findings healthcare settings. Nevertheless, it remains unclear if possible build dimensional predictive models attentional state sample that includes participants conditions. Here, we use 5 datasets identify validate functional connectome-based markers attention. In dataset 1, modeling observe successful prediction performance on in-scan sustained task youth, condition. The predictions are not driven by confounds, head motion. 2, find network model defined 1 generalizes predict separate neurotypical performing same task. 3–5, identification longitudinal scans probe stability across months years individual participants. Our results help elucidate brain youth support further development other clinically relevant phenotypes.

Language: Английский

Citations

7
A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth DOI Creative Commons
Corey Horien, Abigail S. Greene, Xilin Shen

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: July 25, 2022

Abstract Difficulty with attention is an important symptom in many conditions psychiatry, including neurodiverse such as autism. There a need to better understand the neurobiological correlates of and leverage these findings for individuals healthcare settings. Nevertheless, it remains unclear if possible build robust dimensional predictive models populations. Here, we use five datasets identify validate functional connectome-based markers attention. In dataset one, modelling observe successful prediction performance on in-scan sustained task sample youth. The predictions are not driven by confounds, head motion. two, find network model defined one generalizes predict separate neurotypical participants performing same task. three five, identification longitudinal scans probe stability across months years individual participants. Our results help elucidate brain youth support further development other clinically-relevant phenotypes.

Language: Английский

Citations

2