Altered resting-state dynamic functional brain networks in major depressive disorder: Findings from the REST-meta-MDD consortium DOI Creative Commons
Yicheng Long, Hengyi Cao, Chao‐Gan Yan

et al.

NeuroImage Clinical, Journal Year: 2020, Volume and Issue: 26, P. 102163 - 102163

Published: Jan. 1, 2020

Major depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed characterize using a large multi-site sample novel network-based approach. Resting-state magnetic resonance imaging (fMRI) data were acquired from total 460 473 healthy controls, as part REST-meta-MDD consortium. networks constructed for each subject sliding-window Multiple spatio-temporal networks, including temporal variability, clustering efficiency, then compared between subjects at both global local levels. The group showed significantly higher lower correlation coefficient (indicating decreased clustering) shorter characteristic path length increased efficiency) controls (corrected p < 3.14×10−3). Corresponding changes mainly found default-mode, sensorimotor subcortical areas. Measures variability correlated depression severity 0.05). Moreover, observed between-group differences robustly present first-episode, drug-naïve (FEDN) non-FEDN patients. Our findings suggest that excessive variations FC, reflecting abnormal communications large-scale bran over time, may underlie neuropathology MDD.

Language: Английский

A decade of test-retest reliability of functional connectivity: A systematic review and meta-analysis DOI Creative Commons
Stephanie Noble, Dustin Scheinost, R. Todd Constable

et al.

NeuroImage, Journal Year: 2019, Volume and Issue: 203, P. 116157 - 116157

Published: Sept. 5, 2019

Once considered mere noise, fMRI-based functional connectivity has become a major neuroscience tool in part due to early studies demonstrating its reliability. These fundamental revealed only the tip of iceberg; over past decade, many test-retest reliability have continued add nuance our understanding this complex topic. A summary these diverse and at times contradictory perspectives is needed. We aimed summarize existing knowledge regarding most basic unit analysis: individual edge level. This entailed (1) meta-analytic estimate (2) review factors influencing search Scopus was conducted identify that estimated edge-level To facilitate comparisons across studies, eligibility restricted measuring via intraclass correlation coefficient (ICC). The meta-analysis included random effects pooled mean ICC, with nested within datasets. narrative ICC. From an initial pool 212 44 were identified for qualitative 25 quantitative meta-analysis. On average, edges exhibited "poor" ICC 0.29 (95% CI = 0.23 0.36). reliable measurements tended involve: stronger, within-network, cortical edges, eyes open, awake, active recordings, (3) more within-subject data, (4) shorter intervals, (5) no artifact correction (likely artifact), (6) full correlation-based shrinkage. study represents first systematic investigating connectivity. Key findings suggest there room improvement, but care should be taken avoid promoting expense validity. By pooling key facet accuracy, supports broader efforts improve inferences field.

Language: Английский

Citations

520
Quantitative assessment of structural image quality DOI
Adon F.G. Rosen, David R. Roalf, Kosha Ruparel

et al.

NeuroImage, Journal Year: 2017, Volume and Issue: 169, P. 407 - 418

Published: Dec. 24, 2017

Language: Английский

Citations

398
Cerebellar-Prefrontal Network Connectivity and Negative Symptoms in Schizophrenia DOI Open Access
Roscoe O. Brady,

Irene Gonsalvez,

Ivy Lee

et al.

American Journal of Psychiatry, Journal Year: 2019, Volume and Issue: 176(7), P. 512 - 520

Published: Jan. 30, 2019

The interpretability of results in psychiatric neuroimaging is significantly limited by an overreliance on correlational relationships. Purely studies cannot alone determine whether behavior-imaging relationships are causal to illness, functionally compensatory processes, or purely epiphenomena. Negative symptoms (e.g., anhedonia, amotivation, and expressive deficits) refractory current medications among the foremost causes disability schizophrenia. authors used a two-step approach identifying then empirically testing brain network model schizophrenia symptoms.In first cohort (N=44), data-driven resting-state functional connectivity analysis was identify with that corresponds negative symptom severity. In second (N=11), this modulated 5 days twice-daily transcranial magnetic stimulation (TMS) cerebellar midline.A breakdown specific dorsolateral prefrontal cortex-to-cerebellum directly corresponded Restoration TMS amelioration symptoms, showing statistically significant strong relationship change response change.These demonstrate between cerebellum right cortex associated severity correction ameliorates severity, supporting novel hypothesis for medication-refractory suggesting manipulation may establish markers clinical phenomena.

Language: Английский

Citations

328
The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features DOI Creative Commons
Zaixu Cui, Gaolang Gong

NeuroImage, Journal Year: 2018, Volume and Issue: 178, P. 622 - 637

Published: June 2, 2018

Language: Английский

Citations

319
Reproducibility of R‐fMRI metrics on the impact of different strategies for multiple comparison correction and sample sizes DOI Open Access
Xiao Chen, Bin Lu, Chao‐Gan Yan

et al.

Human Brain Mapping, Journal Year: 2017, Volume and Issue: 39(1), P. 300 - 318

Published: Oct. 11, 2017

Abstract Concerns regarding reproducibility of resting‐state functional magnetic resonance imaging (R‐fMRI) findings have been raised. Little is known about how to operationally define R‐fMRI and what extent it affected by multiple comparison correction strategies sample size. We comprehensively assessed two aspects reproducibility, test–retest reliability replicability, on widely used metrics in both between‐subject contrasts sex differences within‐subject comparisons eyes‐open eyes‐closed (EOEC) conditions. noted permutation test with Threshold‐Free Cluster Enhancement (TFCE), a strict strategy, reached the best balance between family‐wise error rate (under 5%) reliability/replicability (e.g., 0.68 for 0.25 replicability amplitude low‐frequency fluctuations (ALFF) differences, 0.49 ALFF EOEC differences). Although indices attained moderate reliabilities, they replicated poorly distinct datasets (replicability < 0.3 0.5 By randomly drawing different sizes from single site, we found reliability, sensitivity positive predictive value (PPV) rose as size increased. Small 80 [40 per group]) not only minimized power (sensitivity 2%), but also decreased likelihood that significant results reflect “true” effects (PPV 0.26) differences. Our implications select highlight importance sufficiently large studies enhance reproducibility. Hum Brain Mapp 39:300–318, 2018 . © 2017 Wiley Periodicals, Inc.

Language: Английский

Citations

292
RESTplus: an improved toolkit for resting-state functional magnetic resonance imaging data processing DOI
Xize Jia, Jue Wang,

Haiyang Sun

et al.

Science Bulletin, Journal Year: 2019, Volume and Issue: 64(14), P. 953 - 954

Published: May 13, 2019

Language: Английский

Citations

268
A Hitchhiker's Guide to Functional Magnetic Resonance Imaging DOI Creative Commons
José Miguel Soares, Ricardo Magalhães, Pedro Silva Moreira

et al.

Frontiers in Neuroscience, Journal Year: 2016, Volume and Issue: 10

Published: Nov. 10, 2016

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics paradigm design to imaging artifacts, complex protocol definition, multitude processing methods analysis, well intrinsic methodological limitations) must be considered addressed in order optimize fMRI analysis arrive at the most accurate grounded interpretation data. In practice, researcher/clinician choose, many available options, suitable software tool for each stage pipeline. Herein we provide a straightforward guide designed address, major stages, techniques, tools involved process. We developed this help those new technique overcome critical difficulties its use, serve resource neuroimaging community.

Language: Английский

Citations

225
More than just statics: temporal dynamics of intrinsic brain activity predicts the suicidal ideation in depressed patients DOI
Jian Li, Xujun Duan, Qian Cui

et al.

Psychological Medicine, Journal Year: 2018, Volume and Issue: 49(5), P. 852 - 860

Published: June 18, 2018

Abstract Background Major depressive disorder (MDD) is associated with high risk of suicide. Conventional neuroimaging works showed abnormalities static brain activity and connectivity in MDD suicidal ideation (SI). However, little known regarding alterations dynamics. More broadly, it remains unclear whether temporal dynamics the could predict prognosis SI. Methods We included patients ( n = 48) without SI age-, gender-, education-matched healthy controls 30) who underwent resting-state functional magnetic resonance imaging. first assessed dynamic amplitude low-frequency fluctuation (dALFF) – a proxy for intrinsic (iBA) using sliding-window analysis. Furthermore, variability (dynamics) iBA was quantified as variance dALFF over time. In addition, prediction severity from conducted general linear model. Results Compared SI, group decreased (less variability) dorsal anterior cingulate cortex, left orbital frontal inferior gyrus, hippocampus. Importantly, these variabilities be used to r 0.43, p 0.03), whereas ALFF not current data set. Conclusions These findings suggest that regions involved executive emotional processing are patients. This novel predictive model useful developing neuromarkers clinical applications.

Language: Английский

Citations

178
Brain Structural and Functional Damage Network Localization of Suicide DOI
Xiaohan Zhang,

Ruoxuan Xu,

Haining Ma

et al.

Biological Psychiatry, Journal Year: 2024, Volume and Issue: 95(12), P. 1091 - 1099

Published: Jan. 10, 2024

Language: Английский

Citations

71
Network Localization of State and Trait of Auditory Verbal Hallucinations in Schizophrenia DOI
Fan Mo, Han Zhao, Yifan Li

et al.

Schizophrenia Bulletin, Journal Year: 2024, Volume and Issue: 50(6), P. 1326 - 1336

Published: Feb. 24, 2024

Abstract Background and Hypothesis Neuroimaging studies investigating the neural substrates of auditory verbal hallucinations (AVH) in schizophrenia have yielded mixed results, which may be reconciled by network localization. We sought to examine whether AVH-state AVH-trait brain alterations localize common or distinct networks. Study Design initially identified reported 48 previous studies. By integrating these affected locations with large-scale discovery validation resting-state functional magnetic resonance imaging datasets, we then leveraged novel connectivity mapping construct dysfunctional Results The neuroanatomically heterogeneous localized specific comprised a broadly distributed set regions mainly involving auditory, salience, basal ganglia, language, sensorimotor Contrastingly, manifested as pattern circumscribed principally implicating caudate inferior frontal gyrus. Additionally, aligned neuromodulation targets for effective treatment AVH, indicating possible clinical relevance. Conclusions Apart from unifying seemingly irreproducible neuroimaging results across prior AVH studies, our findings suggest different mechanisms underlying state trait perspective more inform future AVH.

Language: Английский

Citations

55