scholarly journals Altered Dynamic Functional Connectivity of Cuneus in Schizophrenia Patients: A Resting-State fMRI Study

2021 ◽  
Vol 11 (23) ◽  
pp. 11392
Author(s):  
Charles Okanda Nyatega ◽  
Li Qiang ◽  
Mohammed Jajere Adamu ◽  
Ayesha Younis ◽  
Halima Bello Kawuwa
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Low Frequency ◽  
Temporal Correlation ◽  
Resting State Fmri ◽  
Mental Condition ◽  
Middle Temporal Gyrus ◽  
Healthy Controls ◽  
Dynamic Functional Connectivity ◽  
Sliding Windows

Objective: Schizophrenia (SZ) is a functional mental condition that has a significant impact on patients’ social lives. As a result, accurate diagnosis of SZ has attracted researchers’ interest. Based on previous research, resting-state functional magnetic resonance imaging (rsfMRI) reported neural alterations in SZ. In this study, we attempted to investigate if dynamic functional connectivity (dFC) could reveal changes in temporal interactions between SZ patients and healthy controls (HC) beyond static functional connectivity (sFC) in the cuneus, using the publicly available COBRE dataset. Methods: Sliding windows were applied to 72 SZ patients’ and 74 healthy controls’ (HC) rsfMRI data to generate temporal correlation maps and, finally, evaluate mean strength (dFC-Str), variability (dFC-SD and ALFF) in each window, and the dwelling time. The difference in functional connectivity (FC) of the cuneus between two groups was compared using a two-sample t-test. Results: Our findings demonstrated decreased mean strength connectivity between the cuneus and calcarine, the cuneus and lingual gyrus, and between the cuneus and middle temporal gyrus (TPOmid) in subjects with SZ. Moreover, no difference was detected in variability (standard deviation and the amplitude of low-frequency fluctuation), the dwelling times of all states, or static functional connectivity (sFC) between the groups. Conclusions: Our verdict suggest that dynamic functional connectivity analyses may play crucial roles in unveiling abnormal patterns that would be obscured in static functional connectivity, providing promising impetus for understanding schizophrenia disease.

scholarly journals Impact of anaesthesia on static and dynamic functional connectivity in mice

2021 ◽  
Author(s):  
Tomokazu Tsurugizawa ◽  
Daisuke Yoshimaru
Keyword(s):  
Functional Connectivity ◽  
Functional Mri ◽  
Resting State ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Network ◽  
List Type ◽  
Thalamic Nuclei ◽  
Dynamic Functional Connectivity ◽  
Subcortical Regions

AbstractA few studies have compared the static functional connectivity between awake and anaesthetized states in rodents by resting-state fMRI. However, impact of anaesthesia on static and dynamic fluctuations in functional connectivity has not been fully understood. Here, we developed a resting-state fMRI protocol to perform awake and anaesthetized functional MRI in the same mice. Static functional connectivity showed a widespread decrease under anaesthesia, such as when under isoflurane or a mixture of isoflurane and medetomidine. Several interhemispheric connections were key connections for anaesthetized condition from awake. Dynamic functional connectivity demonstrates the shift from frequent broad connections across the cortex, the hypothalamus, and the auditory-visual cortex to frequent local connections within the cortex only. Fractional amplitude of low frequency fluctuation in the thalamic nuclei decreased under both anaesthesia. These results indicate that typical anaesthetics for functional MRI alters the spatiotemporal profile of the dynamic brain network in subcortical regions, including the thalamic nuclei and limbic system.HighlightsResting-state fMRI was compared between awake and anaesthetized in the same mice.Anaesthesia induced a widespread decrease of static functional connectivity.Anaesthesia strengthened local connections within the cortex.fALFF in the thalamus was decreased by anaesthesia.

scholarly journals Insulin Resistance-Associated Interhemispheric Functional Connectivity Alterations in T2DM: A Resting-State fMRI Study

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Wenqing Xia ◽  
Shaohua Wang ◽  
Andrea M. Spaeth ◽  
Hengyi Rao ◽  
Pin Wang ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Middle Temporal Gyrus ◽  
Model Assessment ◽  
Healthy Controls ◽  
Resting State Functional Connectivity

We aim to investigate whether decreased interhemispheric functional connectivity exists in patients with type 2 diabetes mellitus (T2DM) by using resting-state functional magnetic resonance imaging (rs-fMRI). In addition, we sought to determine whether interhemispheric functional connectivity deficits associated with cognition and insulin resistance (IR) among T2DM patients. We compared the interhemispheric resting state functional connectivity of 32 T2DM patients and 30 healthy controls using rs-fMRI. Partial correlation coefficients were used to detect the relationship between rs-fMRI information and cognitive or clinical data. Compared with healthy controls, T2DM patients showed bidirectional alteration of functional connectivity in several brain regions. Functional connectivity values in the middle temporal gyrus (MTG) and in the superior frontal gyrus were inversely correlated with Trail Making Test-B score of patients. Notably, insulin resistance (log homeostasis model assessment-IR) negatively correlated with functional connectivity in the MTG of patients. In conclusion, T2DM patients exhibit abnormal interhemispheric functional connectivity in several default mode network regions, particularly in the MTG, and such alteration is associated with IR. Alterations in interhemispheric functional connectivity might contribute to cognitive dysfunction in T2DM patients.

scholarly journals Low-Frequency Repetitive Transcranial Magnetic Stimulation Restores Dynamic Functional Connectivity in Subcortical Stroke

2021 ◽  
Vol 12 ◽  
Author(s):  
Yin Qin ◽  
Xiaoying Liu ◽  
Xiaoping Guo ◽  
Minhua Liu ◽  
Hui Li ◽  
...  
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Functional Connectivity ◽  
Cognitive Control ◽  
Resting State ◽  
Magnetic Stimulation ◽  
Dwell Time ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Low Frequency ◽  
Healthy Controls ◽  
Dynamic Functional Connectivity

Background and Purpose: Strokes consistently result in brain network dysfunction. Previous studies have focused on the resting-state characteristics over the study period, while dynamic recombination remains largely unknown. Thus, we explored differences in dynamics between brain networks in patients who experienced subcortical stroke and the effects of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) on dynamic functional connectivity (dFC).Methods: A total of 41 patients with subcortical stroke were randomly divided into the LF-rTMS (n = 23) and the sham stimulation groups (n = 18). Resting-state functional MRI data were collected before (1 month after stroke) and after (3 months after stroke) treatment; a total of 20 age- and sex-matched healthy controls were also included. An independent component analysis, sliding window approach, and k-means clustering were used to identify different functional networks, estimate dFC matrices, and analyze dFC states before treatment. We further assessed the effect of LF-rTMS on dFCs in patients with subcortical stroke.Results: Compared to healthy controls, patients with stroke spent significantly more time in state I [p = 0.043, effect size (ES) = 0.64] and exhibited shortened stay in state II (p = 0.015, ES = 0.78); the dwell time gradually returned to normal after LF-rTMS treatment (p = 0.015, ES = 0.55). Changes in dwell time before and after LF-rTMS treatment were positively correlated with changes in the Fugl–Meyer Assessment for Upper Extremity (pr = 0.48, p = 0.028). Moreover, patients with stroke had decreased dFCs between the sensorimotor and cognitive control domains, yet connectivity within the cognitive control network increased. These abnormalities were partially improved after LF-rTMS treatment.Conclusion: Abnormal changes were noted in temporal and spatial characteristics of sensorimotor domains and cognitive control domains of patients who experience subcortical stroke; LF-rTMS can promote the partial recovery of dFC. These findings offer new insight into the dynamic neural mechanisms underlying effect of functional recombination and rTMS in subcortical stroke.Registration:http://www.chictr.org.cn/index.aspx, Unique.identifier: ChiCTR1800019452.

Distinct dynamic functional connectivity patterns of pain and touch thresholds: A resting-state fMRI study

2019 ◽  
Vol 375 ◽  
pp. 112142
Author(s):  
Yueming Yuan ◽  
Li Zhang ◽  
Linling Li ◽  
Gan Huang ◽  
Ahmed Anter ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Dynamic Functional Connectivity ◽  
Fmri Study ◽  
Connectivity Patterns

High-Order Functional Connectivity Network for Differential Diagnosis of Depression

2019 ◽  
Vol 9 (6) ◽  
pp. 1095-1102
Author(s):  
Jian Yang ◽  
Xu Mao ◽  
Ning Liu ◽  
Ning Zhong
Keyword(s):  
Time Series ◽  
Differential Diagnosis ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Time ◽  
Time Window ◽  
Resting State Fmri ◽  
High Order ◽  
Healthy Controls ◽  
Resting State Functional Connectivity

Resting-state functional connectivity (FC) changes dynamically and major depressive disorder (MDD) has abnormality in functional connectivity networks (FCNs), but few existing resting-state fMRI study on MDD utilizes the dynamics, especially for identifying depressive individuals from healthy controls. In this paper, we propose a methodological procedure for differential diagnosis of depression, called HN3D, which is based on high-order functional connectivity networks (HFCN). Firstly, HN3D extracts time series by independent component analysis, and partitions them into overlapped short series by sliding time window. Secondly, it constructs a FCN for each time window and concatenates correlation matrices of all FCNs to generate correlation time series. Then, correlation time series are grouped into different clusters and high-order correlations for HFCN is calculated based on their means. Finally, graph based features of HFCNs are extracted and selected for a linear discriminative classifier. Tested on 21 healthy controls and 20 MDD patients, HN3D achieved its best 100% classification accuracy, which is much higher than results based on stationary FCNs. In addition, most discriminative components of HN3D locate in default mode network and visual network, which are consistent with existing stationary-based results on depression. Though HN3D needs to be studied further, it is helpful for the differential diagnosis of depression and might have potentiality in identifying relevant biomarkers.

scholarly journals Altered Intra- and Interregional Synchronization in Resting-State Cerebral Networks Associated with Chronic Tinnitus

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Chen Chen ◽  
Jian Zhang ◽  
Xiao-Wei Li ◽  
Wenqing Xia ◽  
Xu Feng ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Chronic Tinnitus ◽  
Healthy Controls ◽  
Tinnitus Distress ◽  
The Right

Objective. Subjective tinnitus is hypothesized to arise from aberrant neural activity; however, its neural bases are poorly understood. To identify aberrant neural networks involved in chronic tinnitus, we compared the resting-state functional magnetic resonance imaging (fMRI) patterns of tinnitus patients and healthy controls.Materials and Methods. Resting-state fMRI measurements were obtained from a group of chronic tinnitus patients (n=29) with normal hearing and well-matched healthy controls (n=30). Regional homogeneity (ReHo) analysis and functional connectivity analysis were used to identify abnormal brain activity; these abnormalities were compared to tinnitus distress.Results. Relative to healthy controls, tinnitus patients had significant greater ReHo values in several brain regions including the bilateral anterior insula (AI), left inferior frontal gyrus, and right supramarginal gyrus. Furthermore, the left AI showed enhanced functional connectivity with the left middle frontal gyrus (MFG), while the right AI had enhanced functional connectivity with the right MFG; these measures were positively correlated with Tinnitus Handicap Questionnaires (r=0.459,P=0.012andr=0.479,P=0.009, resp.).Conclusions. Chronic tinnitus patients showed abnormal intra- and interregional synchronization in several resting-state cerebral networks; these abnormalities were correlated with clinical tinnitus distress. These results suggest that tinnitus distress is exacerbated by attention networks that focus on internally generated phantom sounds.

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