scholarly journals Analysis of Correlation Between White Matter Changes and Functional Responses in Post-stroke Depression

2021 ◽  
Vol 13 ◽  
Author(s):  
Xuefei Zhang ◽  
Yu Shi ◽  
Tao Fan ◽  
Kangling Wang ◽  
Hongrui Zhan ◽  
...  
Keyword(s):  
Neuropsychiatric Symptoms ◽  
Structural Connectivity ◽  
Brain Network ◽  
Functional Networks ◽  
Functional Responses ◽  
Clinical Trial Registration ◽  
Post Stroke ◽  
Post Stroke Depression ◽  
Structural Networks ◽  
The Relationship

Objective: Post-stroke depression (PSD) is one of the most common neuropsychiatric symptoms with high prevalence, however, the mechanism of the brain network in PSD and the relationship between the structural and functional network remain unclear. This research applies graph theory to structural networks and explores the relationship between structural and functional networks.Methods: Forty-five patients with acute ischemic stroke were divided into the PSD group and post-stroke without depression (non-PSD) group respectively and underwent the magnetic resonance imaging scans. Network construction and Module analysis were used to explore the structural connectivity-functional connectivity (SC-FC) coupling of multi-scale brain networks in patients with PSD.Results: Compared with non-PSD, the structural network in PSD was related to the reduction of clustering and the increase of path length, but the degree of modularity was lower.Conclusions: The SC-FC coupling may serve as a biomarker for PSD. The similarity in SC and FC is associated with cognitive dysfunction, retardation, and desperation. Our findings highlighted the distinction in brain structural-functional networks in PSD.Clinical Trial Registration: https://www.clinicaltrials.gov/ct2/show/NCT03256305, NCT03256305.

scholarly journals Analysis of correlation between white matter changes and functional responses in post-stroke depression

2020 ◽  
Author(s):  
Xuefei Zhang ◽  
Shimin Huang ◽  
Tao Fan ◽  
Kangling Wang ◽  
Wen Wu
Keyword(s):  
Neuropsychiatric Symptoms ◽  
Structural Connectivity ◽  
Brain Network ◽  
Functional Responses ◽  
Post Stroke ◽  
Graph Metrics ◽  
High Prevalence ◽  
Structural Network ◽  
Post Stroke Depression ◽  
The Relationship

Abstract ObjectivePSD is one of the most common neuropsychiatric symptoms with high prevalence, however, the mechanism of brain network in PSD and the relationship between the structural network and functional network remain unclear. This study incorporated multiple structural and functional connectivity metrics into a graph analysis framework in patients with PSD and PSND. MethodForty-five patients with acute ischemic stroke were divided into PSD group and non-PSD group respectively and underwent the magnetic resonance imaging scans. For the structural network, we compared commonly used connectivity metrics, including FA and MD. Moreover, we investigated the relationship between functional and structural connectivity networks. The whole brain network was characterized with graph theoretical metrics and decomposed into modules. Subsequently, the graph metrics and the connectivity within modules were related to depression. ResultsStructural network disturbances in PSD were related to decreased clustering and increased path length compared to PSND, while being less modular.ConclusionSC-FC coupling may serve as a biomarker for post-stroke depression. Some regional characteristics were altered in structural connectivity network, involving attention, sensorimotor, subcortical and default-mode networks. These regions with altered nodal characteristics likely reflect the pathophysiology of PSD. The similarity of structural-functional are associated with cognitive dysfunction, retardation and desperation. Our findings highlighted the distinction in brain structural-functional networks in PSD.

scholarly journals Integrative Structural Brain Network Analysis In Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Moo K. Chung ◽  
Jamie L. Hanson ◽  
Nagesh Adluru ◽  
Andrew L. Alexander ◽  
Richard J. Davidson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Brain Network ◽  
Node Degree ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
Structural Brain Network ◽  
Structural Networks

AbstractIn diffusion tensor imaging, structural connectivity between brain regions is often measured by the number of white matter fiber tracts connecting them. Other features such as the length of tracts or fractional anisotropy (FA) are also used in measuring the strength of connectivity. In this study, we investigated the effects of incorporating the number of tracts, the tract length and FA-values into the connectivity model. Using various node-degree based graph theory features, the three connectivity models are compared. The methods are applied in characterizing structural networks between normal controls and maltreated children, who experienced maltreatment while living in post-institutional settings before being adopted by families in the US.

scholarly journals Association among depression, cognitive impairment and executive dysfunction after stroke

2012 ◽  
Vol 6 (3) ◽  
pp. 152-157 ◽  
Author(s):  
Luisa Terroni ◽  
Matildes F.M. Sobreiro ◽  
Adriana B. Conforto ◽  
Carla C. Adda ◽  
Valeri D. Guajardo ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Neuropsychological Tests ◽  
Executive Dysfunction ◽  
Stroke Survivors ◽  
Stroke Patients ◽  
Adequate Treatment ◽  
Post Stroke ◽  
Quantitative Studies ◽  
Post Stroke Depression ◽  
The Relationship

ABSTRACT The relationship between depression and cognitive impairment, frequent after stroke, is complex and has not been sufficiently elucidated. Objective: To review the relationship between post-stroke depression and cognitive impairment. Methods: We performed a PubMed database search spanning the last ten years, using the terms post-stroke depression, cognitive dysfunction, cognitive impairment and neuropsychological tests. Our target studies were original quantitative studies that investigated the relationship between post-stroke depression (PSD) and cognitive impairment in stroke patients. Articles published in English, Spanish, Italian and Portuguese were considered. Selection criteria were the use of neuropsychological tests to assess cognitive function, and of either instruments to diagnose major depression, or scales to assess depressive symptoms, within the first three months after stroke. Results: Six original quantitative studies fulfilled the criteria. The prevalence of PSD within the first three months after stroke ranged from 22% to 31%. Incidence ranged from 25% to 27% and was evaluated in only two studies. PSD was associated with increased cognitive impairment. Cognitive impairment was reported in 35.2% to 87% of the patients. Post-stroke cognitive deficits were reported mostly in executive function, memory, language, and speed of processing. Conclusion: Executive dysfunction and depression occur in stroke survivors, are frequently coexistent, and also associated with worse stroke prognosis. Healthcare professionals need to address and provide adequate treatment for depression and executive dysfunctions in stroke patients early in the first three months after stroke. Future studies should evaluate the efficacy of programs evaluating the early detection and treatment of PSD and executive dysfunction in stroke survivors.

scholarly journals Enhanced prefrontal functional–structural networks to support postural control deficits after traumatic brain injury in a pediatric population

2017 ◽  
Vol 1 (2) ◽  
pp. 116-142 ◽  
Author(s):  
Ibai Diez ◽  
David Drijkoningen ◽  
Sebastiano Stramaglia ◽  
Paolo Bonifazi ◽  
Daniele Marinazzo ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Cognitive Control ◽  
Postural Control ◽  
Pediatric Population ◽  
Structural Connectivity ◽  
Brain Network ◽  
Body Sway ◽  
Brain Network Reorganization ◽  
Structural Networks

Traumatic brain injury (TBI) affects structural connectivity, triggering the reorganization of structural–functional circuits in a manner that remains poorly understood. We focus here on brain network reorganization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severe TBI, comparing them to young, typically developing control participants. TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: (1) a subcortical network, including parts of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulate gyrus, and precuneus; and (2) a task-positive network, involving regions of the dorsal attention system, together with dorsolateral and ventrolateral prefrontal regions. We also found that the increased prefrontal connectivity in TBI patients was correlated with some postural control indices, such as the amount of body sway, whereby patients with worse balance increased their connectivity in frontal regions more strongly. The increased prefrontal connectivity found in TBI patients may provide the structural scaffolding for stronger cognitive control of certain behavioral functions, consistent with the observations that various motor tasks are performed less automatically following TBI and that more cognitive control is associated with such actions.

scholarly journals The Distinct Disrupted Plasticity in Structural and Functional Network in Mild Stroke With Basal Ganglia Region Infarcts

2021 ◽  
Author(s):  
Hua Zhu ◽  
Lijun Zuo ◽  
Wanlin Zhu ◽  
Jing Jing ◽  
Zhe Zhang ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Basal Ganglia ◽  
Functional Connectivity ◽  
Network Analysis ◽  
Structural Connectivity ◽  
Functional Network ◽  
Imaging Biomarkers ◽  
Functional Networks ◽  
Stroke Patients ◽  
Post Stroke

Abstract ObjectiveTo characterize brain structural and functional networks in post-stroke patients with or without cognitive impairment. MethodsGraph theory analysis was applied to diffusion-weighted imaging (DWI) data and resting-state functional MRI (fMRI) data from 23 post-stroke patients with cognitive impairment (PSCI), 17 post-stroke patients without cognitive impairment (NPSCI), and 29 healthy controls (HC). Structural and functional connectivity between 90 cortical and subcortical brain regions was estimated and thresholded to construct a set of undirected graphs. Network-based statistics (NBS) was used to characterize altered connectivity patterns among the three groups. ResultsCompared to HC, the PSCI group demonstrated substantial reductions in all three types of connections - rich club, feeder, and local - in structural and functional networks. Specifically, in structural network analysis, reduced connections were observed within basal ganglia and basal ganglia-frontal networks, whereas in the functional network analysis, reduced connections were observed in fronto-parietal network (FPN) and cingulo-opercular networks (CON). Meanwhile, compared to HC, the NPSCI group demonstrated reductions in both feeder and local connections only within occipital area and occipital-temporal structural networks. ConclusionsThe findings of reduced structural connectivity in regions stemming from a basal ganglia core and reduced functional connectivity in FPN and CON may indicate a bottom-up cognitive impairment induced by stroke. Graph analysis and connectomics may aid clinical diagnosis and serve as potential imaging biomarkers for post-stroke patients with cognitive impairment.

scholarly journals Disrupted Functional Connectivity Within and Between Resting-State Networks in the Subacute Stage of Post-stroke Aphasia

2021 ◽  
Vol 15 ◽  
Author(s):  
Chao Zhang ◽  
Yingying Xia ◽  
Tao Feng ◽  
Ke Yu ◽  
Haiyan Zhang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Network ◽  
Lesion Volume ◽  
Focal Lesions ◽  
Verbal Comprehension ◽  
Post Stroke ◽  
Subacute Stage ◽  
Frontoparietal Network ◽  
The Relationship

Background: Post-stroke aphasia (PSA) results from brain network disorders caused by focal stroke lesions. However, it still remains largely unclear whether the impairment is present in intra- and internetwork functional connectivity (FC) within each resting-state network (RSN) and between RSNs in the subacute stage of PSA.Objectives: This study aimed to investigate the resting-state FC within and between RSNs in patients with PSA and observe the relationships between FC alterations and Western Aphasia Battery (WAB) measures.Methods: A total of 20 individuals with subacute PSA and 20 healthy controls (HCs) were recruited for functional MRI (fMRI) scanning, and only patients with PSA underwent WAB assessment. Independent component analysis was carried out to identify RSNs. Two-sample t-tests were used to calculate intra- and internetwork FC differences between patients with PSA and HCs. The results were corrected for multiple comparisons using the false discovery rate (FDR correction, p < 0.05). Partial correlation analysis was performed to observe the relationship between FC and WAB scores with age, gender, mean framewise displacement, and lesion volume as covariates (p < 0.05).Results: Compared to HCs, patients with PSA showed a significant increase in intranetwork FC in the salience network (SN). For internetwork FC analysis, patients showed a significantly increased coupling between left frontoparietal network (lFPN) and SN and decreased coupling between lFPN and right frontoparietal network (rFPN) as well as between lFPN and posterior default mode network (pDMN) (FDR correction, p < 0.05). Finally, a significant positive correlation was found between the intergroup difference of FC (lFPN-rFPN) and auditory-verbal comprehension (p < 0.05).Conclusion: Altered FC was revealed within and between multiple RSNs in patients with PSA at the subacute stage. Reduced FC between lFPN and rFPN was the key element participating in language destruction. These findings proved that PSA is a brain network disorder caused by focal lesions; besides, it may improve our understanding of the pathophysiological mechanisms of patients with PSA at the subacute stage.

The Structural and Functional Neuroanatomy of Post-Stroke Depression and Executive Dysfunction: A Review of Neuroimaging Findings and Implications for Treatment

2020 ◽  
pp. 089198872096827
Author(s):  
Abhishek Jaywant ◽  
Larissa DelPonte ◽  
Dora Kanellopoulos ◽  
Michael W. O’Dell ◽  
Faith M. Gunning
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Executive Dysfunction ◽  
Brain Network ◽  
Functional Neuroanatomy ◽  
Default Mode ◽  
Control Networks ◽  
Post Stroke ◽  
Efficacious Treatment ◽  
Post Stroke Depression

Post-stroke depression and executive dysfunction co-occur and are highly debilitating. Few treatments alleviate both depression and executive dysfunction after stroke. Understanding the brain network changes underlying post-stroke depression with executive dysfunction can inform the development of targeted and efficacious treatment. In this review, we synthesize neuroimaging findings in post-stroke depression and post-stroke executive dysfunction and highlight the network commonalities that may underlie this comorbidity. Structural and functional alterations in the cognitive control network, salience network, and default mode network are associated with depression and executive dysfunction after stroke. Specifically, post-stroke depression and executive dysfunction are both linked to changes in intrinsic functional connectivity within resting state networks, functional over-connectivity between the default mode and salience/cognitive control networks, and reduced cross-hemispheric frontoparietal functional connectivity. Cognitive training and noninvasive brain stimulation targeted at these brain network abnormalities and specific clinical phenotypes may help advance treatment for post-stroke depression with executive dysfunction.

The relationship between post-stroke depression and physical recovery

2015 ◽  
Vol 176 ◽  
pp. 56-60 ◽  
Author(s):  
Shiho Matsuzaki ◽  
Mamoru Hashimoto ◽  
Seiji Yuki ◽  
Asuka Koyama ◽  
Yoshifumi Hirata ◽  
...  
Keyword(s):  
Post Stroke ◽  
Post Stroke Depression ◽  
The Relationship ◽  
Physical Recovery
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