Below the surface DOI Creative Commons

Tom Bresser

Published: May 24, 2024

Insomnia disorder is a common and complex mental health problem that also risk factor for the development of major depressive disorder. Despite its high prevalence, neurobiological mechanism underlying insomnia remains elusive. Advancing our understanding mechanisms could ultimately contribute to more effective treatments. White matter, comprising myelinated axons, connects brain regions into functional circuits. Investigating deviations in people with advance circuits involved This thesis examined role white matter ensuing depression. In Chapter 2, comparative analysis whole-brain structural connectivity revealed hyperconnectivity within subnetwork anchored at right angular gyrus. overlapped multiple resting-state networks, including frontoparietal control network, cinguloopercular default-mode right-lateralized ventral attention network. Furthermore, strength this correlated reactive hyperarousal, key symptom. 3 delves microstructure, focusing on fractional anisotropy (FA) anterior limb internal capsule. Using data from three independent studies, lower FA capsule was replicated patients. addition, correlation showed severe symptoms Exploratory whole did not detect additional spatial clusters where significantly associated or severity. 4 uses longitudinal randomized controlled trial interventions determine if microstructure precede follow as consequence. Results indicated left retrolenticular part baseline predicted worse progression untreated participants pronounced alleviation treated participants. Additionally, combined cognitive behavioral therapy circadian rhythm support led small decrease mean diffusivity superior corona radiata. Across all participants, changes tract 5 investigates heterogeneity by examining different subtypes. The study patterns deviating subtypes, predominantly limbic default mode Subtype deviation profiles differed compared random subsamples entire group disregarding subtype. provided first indication subtypes show altered connectivity. conclusion, research shows linked connectivity, particularly frontal-subcortical networks related salience diverging between highlight possibility neural correlates contributing same single diagnostic label. Future will benefit larger samples, deeper phenotyping, dysfunctional advanced neuroimaging methods further disentangle

Language: Английский

A precision functional atlas of personalized network topography and probabilities DOI Creative Commons
Robert Hermosillo, Lucille A. Moore, Eric Feczko

et al.

Nature Neuroscience, Journal Year: 2024, Volume and Issue: 27(5), P. 1000 - 1013

Published: March 26, 2024

Abstract Although the general location of functional neural networks is similar across individuals, there vast person-to-person topographic variability. To capture this, we implemented precision brain mapping magnetic resonance imaging methods to establish an open-source, method-flexible set network atlases—the Masonic Institute for Developing Brain (MIDB) Precision Atlas. This atlas evolving resource comprising 53,273 individual-specific maps, from more than 9,900 ages and cohorts, including Adolescent Cognitive Development study, Developmental Human Connectome Project others. We also generated probabilistic maps multiple integration zones (using a new overlapping technique, Overlapping MultiNetwork Imaging). Using regions high invariance improved reproducibility executive function statistical in brain-wide associations compared group average-based parcellations. Finally, provide potential use case targeted neuromodulation. The expandable alternative datasets with online interface encouraging scientific community explore contribute understanding human precisely.

Language: Английский

Citations

24
Two common and distinct forms of variation in human functional brain networks DOI

Ally Dworetsky,

Benjamin A. Seitzman,

Babatunde Adeyemo

et al.

Nature Neuroscience, Journal Year: 2024, Volume and Issue: 27(6), P. 1187 - 1198

Published: April 30, 2024

Language: Английский

Citations

21
Structural-functional brain network coupling predicts human cognitive ability DOI Creative Commons
Johanna L. Popp, Jonas A. Thiele, Joshua Faskowitz

et al.

NeuroImage, Journal Year: 2024, Volume and Issue: 290, P. 120563 - 120563

Published: March 16, 2024

Individual differences in general cognitive ability (GCA) have a biological basis within the structure and function of human brain. Network neuroscience investigations revealed neural correlates GCA structural as well functional brain networks. However, whether relationship between networks, structural-functional network coupling (SC-FC coupling), is related to individual remains an open question. We used data from 1030 adults Human Connectome Project, derived connectivity diffusion weighted imaging, resting-state fMRI, assessed latent g-factor 12 tasks. Two similarity measures six communication were model possible interactions arising SC-FC was estimated degree which these align with actual connectivity, providing insights into different strategies. At whole-brain level, higher associated coupling, but only when considering path transitivity strategy. Taking region-specific variations strategy account differentiating positive negative associations GCA, allows for prediction scores cross-validated framework (correlation predicted observed scores: r = .25, p < .001). The same also predicts completely independent sample (N 567, .19, Our results propose neurobiological correlate suggest strategies efficient information processing predictive ability.

Language: Английский

Citations

18
The challenges and prospects of brain-based prediction of behaviour DOI
Jianxiao Wu, Jingwei Li, Simon B. Eickhoff

et al.

Nature Human Behaviour, Journal Year: 2023, Volume and Issue: 7(8), P. 1255 - 1264

Published: July 31, 2023

Language: Английский

Citations

27
Investigative Approaches to Resilient Emotion Regulation Neurodevelopment in a South African Birth Cohort DOI Creative Commons
Tristan S. Yates,

Siphumelele Sigwebela,

Soraya Seedat

et al.

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

Published: Jan. 31, 2025

Language: Английский

Citations

1
Neurobiology of attention-deficit hyperactivity disorder: historical challenges and emerging frontiers DOI
Sanju Koirala, Gracie Grimsrud, Michael A. Mooney

et al.

Nature reviews. Neuroscience, Journal Year: 2024, Volume and Issue: 25(12), P. 759 - 775

Published: Oct. 24, 2024

Language: Английский

Citations

6
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
Psychiatric neuroimaging designs for individualised, cohort, and population studies DOI Creative Commons
Martin Gell, Stephanie Noble, Timothy O. Laumann

et al.

Neuropsychopharmacology, Journal Year: 2024, Volume and Issue: 50(1), P. 29 - 36

Published: Aug. 14, 2024

Abstract Psychiatric neuroimaging faces challenges to rigour and reproducibility that prompt reconsideration of the relative strengths limitations study designs. Owing high resource demands varying inferential goals, current designs differentially emphasise sample size, measurement breadth, longitudinal assessments. In this overview perspective, we provide a guide landscape psychiatric with respect balance scientific goals constraints. Through heuristic data cube contrasting key design features, discuss resulting trade-off among small sample, precision studies (e.g., individualised cohorts) large minimally longitudinal, population studies. Precision support tests within-person mechanisms, via intervention tracking course. Population generalisation across multifaceted individual differences. A proposed reciprocal validation model (RVM) aims recursively leverage these complementary in sequence accumulate evidence, optimise strengths, build towards improved long-term clinical utility.

Language: Английский

Citations

4
Enhancing task fMRI individual difference research with neural signatures DOI Creative Commons
David A. A. Baranger, Aaron J. Gorelik, Sarah E. Paul

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

Abstract Task-based functional magnetic resonance imaging (tb-fMRI) has advanced our understanding of brain-behavior relationships. Standard tb-fMRI analyses suffer from limited reliability and low effect sizes, machine learning (ML) approaches often require thousands subjects, restricting their ability to inform how brain function may arise contribute individual differences. Using data 9,024 early adolescents, we derived a classifier (‘neural signature’) distinguishing between high working memory loads in an emotional n-back fMRI task, which captures differences the separability activation two task conditions. Signature predictions were more reliable had stronger associations with performance, cognition, psychopathology than standard estimates regional activation. Further, signature was sensitive required smaller training sample (N=320) ML approaches. Neural signatures hold tremendous promise for enhancing informativeness research revitalizing its use.

Language: Английский

Citations

0
Resting-State Functional Connectivity Does Not Predict Individual Differences in Perceived Psychological Stress Among Midlife Adults: Evidence From a Preregistered Cross-Validation Study DOI
Chrystal Spencer, Javier Rasero, Rebecca G. Reed

et al.

Published: Feb. 1, 2025

It is theorized that appraisals of perceived psychological stress are represented in the brain. However, a neural signature reliably predicts has yet to be fully characterized. Accordingly, present preregistered study tested whether whole-brain resting-state functional connectivity patterns predict individual differences stress. Participants (N = 417; 53% female; 24.2% non-White; aged 30-54 years) completed 10-item Perceived Stress Scale and underwent 5-minute magnetic resonance imaging scan. Functional (FC) was computed between areas distributed across In total, 19,900 connections (edges) were retained for analyses. Cross-validated multivariate machine learning methods implemented. Using this approach, two penalized regression models with cross-validation-elastic net ridge-were conducted from edges. Across elastic ridge models, FC failed exploratory analyses, they successfully generalized cross-validation age both (elastic net: r 0.193, p < .0001, 95% CI 0.099-0.284, RMSE 6.661, MAE 5.715, R2 0.037; ridge: 0.197, 0.103-0.287), 6.613, 5.8140, 0.039). These results suggest may not self-reported among midlife adults.

Language: Английский

Citations

0