Functional Connectivity Alterations in Children with Spastic and Dyskinetic Cerebral Palsy

Qin, Yun; Li, Yanan; Sun, Bo; He, Hong; Peng, Rui; Zhang, Tao; Li, Jianfu; Chen, Luo; Sun, Chengyan; Yao, Dezhong

doi:10.1155/2018/7058953

Cited by 36 publications

(59 citation statements)

References 79 publications

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“…Our group recently demonstrated FC dysfunction in the insula of mTBI patients 29,30 . In addition, the frontoparietal lobe is an important network of spatial attention, and the ECN is considered to have a good correspondence with the cognitive language paradigm 21 . Consistent with this notion, mTBI patients showed decreased FC in the right insula within the SN as well as the left SPL and the left SFG within the ECN, suggesting that dysfunction within the SN and ECN might contribute to the cognitive impairments observed in acute mTBI patients.…”

Section: Discussionmentioning

confidence: 99%

“…Among the 34 components resulting from ICA, we selected 13 components (7 nonartifactual RSNs) as the focus of the subsequent analyses (Figure 1) through visual inspection in accordance with previous rs‐fMRI studies 21,26 . For each RSN, the single‐sample t test was first used to obtain the z‐maps for each group, the false discovery rate (FDR) was used to correct, and the statistical figure was obtained at the threshold of P < .01.…”

Section: Methodsmentioning

confidence: 99%

“…To define different remote interaction patterns, independent component analysis (ICA) has been widely used for identifying resting‐state networks (RSNs) in view of its ability to isolate various brain function networks 18,19 . Meanwhile, the function network connectivity (FNC) can be used to represent the temporal correlation between these RSNs 20,21 . Therefore, exploration of the RSNs and FNC may provide more information to advance the understanding of the underlying neural mechanisms of cognitive impairment in mTBI.…”

Section: Introductionmentioning

confidence: 99%

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Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury

Shang

et al. 2020

CNS Neurosci Ther

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Aims This study aimed to detect alterations of brain functional connectivity (FC) in acute mild traumatic brain injury (mTBI) and to estimate the extent to which these FC differences predicted the characteristics of posttraumatic cognitive impairment. Methods Resting‐state fMRI data were acquired from acute mTBI patients (n = 50) and healthy controls (HCs) (n = 43). Resting‐state networks (RSNs) were established based on independent component analysis (ICA), and functional network connectivity (FNC) analysis was performed. Subsequently, we analyzed the correlations between FNC abnormalities and cognitive impairment outcomes. Results Altered FC within the salience network (SN), sensorimotor network (SMN), default mode network (DMN), executive control network (ECN), visual network (VN), and cerebellum network (CN) was found in the mTBI group relative to the HC group. Moreover, different patterns of altered network interactions were found between the mTBI patients and HCs, including the SN‐CN, VN‐SMN, and ECN‐DMN connections. Correlations between functional disconnection and cognitive impairment measurements in acute mTBI patients were also found. Conclusion This study indicated that widespread FNC impairment and altered integration existed in mTBI patients at acute stage, suggesting that FNC disruption as a biomarker may be applied for the early diagnosis and prediction of cognitive impairment in mTBI.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury

Shang

et al. 2020

CNS Neurosci Ther

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“…The grey mask used in this process was created by the T1 segmented images of two groups. The RSNs were identified based on the average power spectra and spatial pattern of the components [29, 30]. Thus, the time-courses and spatial maps were acquired for each participant, and the participant-specific maps were converted to Z-scores.…”

Section: Methodsmentioning

confidence: 99%

Aberrant Interhemispheric Functional Organization in Children with Dyskinetic Cerebral Palsy

Qin

Sun

Zhang

et al. 2019

BioMed Research International

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Background. Hemispheric asymmetry is one fundamental principle of neuronal organization. Interhemispheric connectivity and lateralization of intrinsic networks in the resting-state brain demonstrate the interhemispheric functional organization and can be affected by disease processes. This study aims to investigate the interhemispheric organization in children with dyskinetic cerebral palsy (DCP) based on resting-state functional MRI (fMRI). Methods. 24 children with DCP and 20 healthy children were included. Voxel-mirrored homotopic connectivity (VMHC) was calculated to detect the interhemispheric connectivity, and the lateralization of the resting-state networks was performed to examine the asymmetry of the intrinsic networks of brain. Results. Decreased interhemispheric connectivity was found at visual, motor, and motor-control related regions in children with DCP, while high cognitive related networks including the central executive network, the frontoparietal network, and the salience network represented decreased asymmetry in children with DCP. Abnormal VMHC in visual areas, as well as the altered lateralization in inferior parietal lobule and supplementary motor area, showed correlation with the gross motor function and activities of daily living in children with DCP. Conclusion. These findings indicate that the interhemispheric functional organization alteration exists in children with DCP, suggesting that abnormal interhemispheric interaction may be a pathophysiological mechanism of motor and cognitive dysfunction of CP.

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“…Independent component analysis (ICA) using a data-driven method (McKeown et al, 1998 ) without prior experimental models or assumptions decompose BOLD signal from the whole brain voxels into spatially and temporally independent components (ICs), which has been widely used in rs-fMRI and is capable of measuring interactions within and between multiple brain networks directly. Among them, resting-state function network connectivity (FNC) can be used to describe the temporal correlation between these RSNs (Wang et al, 2014 ; Qin et al, 2018 ). At present, ICA studies on the connectivity changes within and between networks in presbycusis have not been reported, just a few studies focused on intra-network FC alteration (Schmidt et al, 2013 ; Luan et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Disrupted Functional Network Connectivity Predicts Cognitive Impairment in Presbycusis Patients

Xing

Zhang²,

Cui

et al. 2020

Front. Aging Neurosci.

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Purpose: Individuals with presbycusis often show deficits in cognitive function, however, the exact neurophysiological mechanisms are not well understood. This study explored the alterations in intra-and inter-network functional connectivity (FC) of multiple networks in presbycusis patients, and further correlated FC with cognitive assessment scores to assess their ability to predict cognitive impairment. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) was performed in 40 presbycusis patients and 40 matched controls, and 12 resting-state networks (RSNs) were identified by independent component analysis (ICA) approach. A twosample t-test was carried out to detect the intra-network FC differences, and functional network connectivity (FNC) was calculated to compare the inter-network FC differences. Pearson or Spearman correlation analysis was subsequently used to explore the correlation between altered FC and cognitive assessment scores. Results: Our study demonstrated that patients with presbycusis showed significantly decreased FC in the subcortical limbic network (scLN), default mode network (DMN), executive control network (ECN), and attention network (AN) compared with the control group. Moreover, the connectivity for scLN-AUN (auditory network) and VN (visual network)-DMN were found significantly increased while AN-DMN was found significantly decreased in presbycusis patients. Ultimately, this study revealed the intra-and internetwork alterations associated with some cognitive assessment scores. Conclusion: This study observed intra-and inter-network FC alterations in presbycusis patients, and investigated that presbycusis can lead to abnormal connectivity of RSNs and plasticity compensation mechanism, which may be the basis of cognitive impairment, suggesting that FNC can be used to predict potential cognitive impairment in their early stage.

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Functional Connectivity Alterations in Children with Spastic and Dyskinetic Cerebral Palsy

Cited by 36 publications

References 79 publications

Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury

Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury

Aberrant Interhemispheric Functional Organization in Children with Dyskinetic Cerebral Palsy

Disrupted Functional Network Connectivity Predicts Cognitive Impairment in Presbycusis Patients

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