Alterations in resting‐state global brain connectivity in bipolar I disorder patients with prior suicide attempt

2020 ◽  
Author(s):  
Xiaofang Cheng ◽  
Jianshan Chen ◽  
Xiaofei Zhang ◽  
Yihe Zhang ◽  
Qiuxia Wu ◽  
...  
Keyword(s):  
Suicide Attempt ◽  
Resting State ◽  
Brain Connectivity ◽  
Bipolar I Disorder ◽  
Global Brain

scholarly journals Controlling for the effect of arterial-CO2 fluctuations in resting-state fMRI: Comparing end-tidal CO2 clamping and retroactive CO2 correction

2020 ◽  
Author(s):  
Ali M. Golestani ◽  
J. Jean Chen
Keyword(s):  
Resting State ◽  
Grey Matter ◽  
Brain Connectivity ◽  
Free Breathing ◽  
Resting State Fmri ◽  
Heart Beat ◽  
Physiological Noise ◽  
Intrinsic Connectivity ◽  
End Tidal ◽  
Global Brain

AbstractThe BOLD signal, as the basis of functional MRI, arises from both neuronal and vascular factors, with their respective contributions to resting state-fMRI still unknown. Among the factors contributing to “physiological noise”, dynamic arterial CO2 fluctuations constitutes the strongest and the most widespread modulator of the grey-matter rs-fMRI signal. Some important questions are: (1) if we were able to clamp arterial CO2 such that fluctuations are removed, what would happen to rs-fMRI measures? (2) falling short of that, is it possible to retroactively correct for CO2 effects with equivalent outcome? In this study 13 healthy subjects underwent two rs-fMRI acquisition: During the “clamped” run, end-tidal CO2 (PETCO2) is clamped to the average PETCO2 level of each participant, while during the “free-breathing” run, the PETCO2 level is passively monitored but not controlled. PETCO2 correction was applied to the free-breathing data by convolving PETCO2 with its BOLD response function, and then regressing out the result. We computed the BOLD resting-state fluctuation amplitude (RSFA), as well as seed-independent mean functional connectivity (FC) as the weighted global brain connectivity (wGBC). Furthermore, connectivity between conditions were compared using coupled intrinsic-connectivity distribution (ICD) method. We ensured that PETCO2 clamping did not significantly alter heart-beat and respiratory variation. We found that neither PETCO2 clamping nor correction produced significant change in RSFA and wGBC. In terms of the ICD, PETCO2 clamping and correction both reduced FC strength in the majority of grey matter regions, although the effect of PETCO2 correction is considerably smaller than the effect of PETCO2 clamping. Furthermore, while PETCO2 clamping reduced inter-subject variability in FC, PETCO2 correction increased the variability. Overall PETCO2 correction is not the equivalent of PETCO2 clamping, although it shifts FC values towards the same direction as clamping does.

scholarly journals Changes in global brain connectivity in LSD-induced altered states of consciousness are attributable to the 5-HT2A receptor

2017 ◽  
Author(s):  
Katrin H. Preller ◽  
Joshua B. Burt ◽  
Jie Lisa Ji ◽  
Charles Schleifer ◽  
Brendan Adkinson ◽  
...  
Keyword(s):  
Receptor Antagonist ◽  
Resting State ◽  
Brain Connectivity ◽  
Subjective Effects ◽  
Critical Role ◽  
Resting State Fmri ◽  
Data Driven ◽  
Resting State Functional Connectivity ◽  
Double Blind ◽  
Global Brain

ABSTRACTLysergic acid diethylamide (LSD) is a psychedelic drug with predominantly agonist activity at various serotonin (5-HT) and dopamine receptors. Despite the therapeutic and scientific interest in LSD, the specific receptor contributions to its neurobiological effects remain largely unknown. To address this knowledge gap, we conducted a double-blind, randomized, counterbalanced, cross-over study during which 24 healthy participants received either i) placebo+placebo, ii) placebo+LSD (100 μg po), or iii) ketanserin – a selective 5-HT2A receptor antagonist. Here we focus on resting-state fMRI, a measure of spontaneous neural fluctuations that can map functional brain connectivity. We collected resting-state data 75 and 300 minutes after LSD/placebo administration. We quantified resting-state functional connectivity via a fully data-driven global brain connectivity (GBC) method to comprehensively map LSD neuropharmacological effects. LSD administration caused widespread GBC alterations that followed a specific topography: LSD reduced connectivity in associative areas, but concurrently increased connectivity across sensory and somatomotor areas. The 5-HT2A receptor antagonist, ketanserin, fully blocked the subjective and neural LSD effects. We show that whole-brain data-driven spatial patterns of LSD effects matched 5-HT2A receptor cortical gene expression in humans, which along with ketanserin effects, strongly implicates the 5-HT2A receptor in LSD’s neuropharmacology. Critically, the LSD-induced subjective effects were associated with somatomotor networks GBC changes. These data-driven neuropharmacological results pinpoint the critical role of 5-HT2A in LSD’s mechanism, which informs its neurobiology and guides rational development of psychedelic-based therapeutics

scholarly journals Resting-State Functional Connectivity of the Punishment Network Associated With Conformity

2020 ◽  
Vol 14 ◽  
Author(s):  
Yin Du ◽  
Yinan Wang ◽  
Mengxia Yu ◽  
Xue Tian ◽  
Jia Liu
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Resting State ◽  
Brain Connectivity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Resting State Functional Connectivity ◽  
Three Phase ◽  
The Right ◽  
Global Brain

Fear of punishment prompts individuals to conform. However, why some people are more inclined than others to conform despite being unaware of any obvious punishment remains unclear, which means the dispositional determinants of individual differences in conformity propensity are poorly understood. Here, we explored whether such individual differences might be explained by individuals’ stable neural markers to potential punishment. To do this, we first defined the punishment network (PN) by combining all potential brain regions involved in punishment processing. We subsequently used a voxel-based global brain connectivity (GBC) method based on resting-state functional connectivity (FC) to characterize the hubs in the PN, which reflected an ongoing readiness state (i.e., sensitivity) for potential punishment. Then, we used the within-network connectivity (WNC) of each voxel in the PN of 264 participants to explain their tendency to conform by using a conformity scale. We found that a stronger WNC in the right thalamus, left insula, postcentral gyrus, and dACC was associated with a stronger tendency to conform. Furthermore, the FC among the four hubs seemed to form a three-phase ascending pathway, contributing to conformity propensity at every phase. Thus, our results suggest that task-independent spontaneous connectivity in the PN could predispose individuals to conform.

951. Changes in Resting-State Global Brain Connectivity in LSD-Induced Altered States of Consciousness are Attributable to the 5-HT2A Receptor

2017 ◽  
Vol 81 (10) ◽  
pp. S385 ◽  
Author(s):  
Katrin Preller ◽  
Charles Schleifer ◽  
Philipp Stämpfli ◽  
John Krystal ◽  
Franz Vollenweider ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Altered States Of Consciousness ◽  
Altered States ◽  
States Of Consciousness ◽  
Global Brain

scholarly journals Identifying Depressed Essential Tremor Using Resting-State Voxel-Wise Global Brain Connectivity: A Multivariate Pattern Analysis

2021 ◽  
Vol 15 ◽  
Author(s):  
Yufen Li ◽  
Li Tao ◽  
Huiyue Chen ◽  
Hansheng Wang ◽  
Xiaoyu Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prefrontal Cortex ◽  
Essential Tremor ◽  
Resting State ◽  
Pattern Analysis ◽  
Brain Connectivity ◽  
Support Vector ◽  
Multivariate Pattern Analysis ◽  
Multivariate Pattern ◽  
Global Brain

Background and Objective: Although depression is one of the most common non-motor symptoms in essential tremor (ET), its pathogenesis and diagnosis biomarker are still unknown. Recently, machine learning multivariate pattern analysis (MVPA) combined with connectivity mapping of resting-state fMRI has provided a promising way to identify patients with depressed ET at the individual level and help to reveal the brain network pathogenesis of depression in patients with ET.Methods: Based on global brain connectivity (GBC) mapping from 41 depressed ET, 49 non-depressed ET, 45 primary depression, and 43 healthy controls (HCs), multiclass Gaussian process classification (GPC) and binary support vector machine (SVM) algorithms were used to identify patients with depressed ET from non-depressed ET, primary depression, and HCs, and the accuracy and permutation tests were used to assess the classification performance.Results: While the total accuracy (40.45%) of four-class GPC was poor, the four-class GPC could discriminate depressed ET from non-depressed ET, primary depression, and HCs with a sensitivity of 70.73% (P < 0.001). At the same time, the sensitivity of using binary SVM to discriminate depressed ET from non-depressed ET, primary depression, and HCs was 73.17, 80.49, and 75.61%, respectively (P < 0.001). The significant discriminative features were mainly located in cerebellar-motor-prefrontal cortex circuits (P < 0.001), and a further correlation analysis showed that the GBC values of significant discriminative features in the right middle prefrontal gyrus, bilateral cerebellum VI, and Crus 1 were correlated with clinical depression severity in patients with depressed ET.Conclusion: Our findings demonstrated that GBC mapping combined with machine learning MVPA could be used to identify patients with depressed ET, and the GBC changes in cerebellar-prefrontal cortex circuits not only posed as the significant discriminative features but also helped to understand the network pathogenesis underlying depression in patients with ET.

Replicating Global Brain Connectivity As an Imaging Marker for Depression - Influence of Preprocessing Strategies and Placebo-Controlled Ketamine Treatment

2019 ◽  
Author(s):  
Christoph Kraus ◽  
Anahit Mkrtchian ◽  
Bashkim Kadriu ◽  
Allison C. Nugent ◽  
Carlos A. Zarate Jr. ◽  
...  
Keyword(s):  
Brain Connectivity ◽  
Global Brain

Tracking whole-brain connectivity dynamics in the resting-state fMRI with post-facial paralysis synkinesis

2021 ◽  
Author(s):  
Zhen-Zhen Ma ◽  
Jia-Jia Wu ◽  
Xu-Yun Hua ◽  
Mou-Xiong Zheng ◽  
Xiang-Xin Xing ◽  
...  
Keyword(s):  
Facial Paralysis ◽  
Resting State ◽  
Brain Connectivity ◽  
Resting State Fmri ◽  
Whole Brain
Sign in / Sign up

Export Citation Format

Share Document