mapping-regional-homogeneity-functional-connectivity-visual-cortex

Mapping Regional Homogeneity and Functional Connectivity of the Visual Cortex in Resting-State fMRI

A combined regional homogeneity (ReHo) and functional connectivity (FC) method, a type of noninvasive functional magnetic resonance imaging (fMRI) method, ...

Renmin hospital of Wuhan university

Previous neuroimaging studies have shown that the long-term effects of peripheral vision loss lead to functional and morphological reorganization in visual cortices. However, it has not been determined whether whole-brain functional network centrality changes occur during peripheral vision loss. This study aimed to investigate functional network centrality and connectivity changes in individuals with peripheral vision loss because of retinitis pigmentosa (RP) by using voxel-wise degree centrality (DC) and seed-based resting-state functional connectivity (rsFC) methods. In total, 30 RP patients (18 men and 12 women, mean age: 38.77±14.44 years) and 30 healthy controls (HCs) (18 men and 12 women, mean age: 34.57±10.70 years) matched for age, sex, cognition, education, and visual expertise underwent resting-state magnetic resonance imaging scans. Graph theory-based network analysis was carried out to investigate DC between the two groups. A seed-based rsFC analysis was then carried out to further reveal the abnormal functional connectivity of the altered DC brain region. Pearson's correlation was used to analyze the relationships of DC and rsFC index with the clinical variables in RP patients: visual function (best-corrected visual acuity and visual field, VF) and optical coherence tomography testing (mean retinal nerve fiber layer). Compared with HCs, RP patients had significantly lower DC values in the bilateral cuneus/calcarine/precuneus (CUN/CAL/PreCUN) [Brodmann's area (BA) 17/18/19/30/31]. In addition, RP patients showed decreased rsFC index, relative to that of HCs, from bilateral CUN/CAL/PreCUN to bilateral lingual/cuneus/calcarine (LIG/CUN/CAL) (BA 18/19/30) and the bilateral postcentral gyrus/superior parietal lobule (BA 3/5/7/40). In contrast, RP patients showed increased rsFC index, relative to that of HCs, from bilateral CUN/CAL/PreCUN to bilateral thalamus/caudate (voxel-level P<0.01; Gaussian random-field correction, cluster-level P<0.05). Moreover, the course of RP showed a negative correlation with the mean DC values of the bilateral CUN/CAL/PreCUN (r=-0.480; P=0.007) and the mean FC values of the bilateral LIG/CUN/CAL (r=-0.484; P=0.007); the mean DC values of the bilateral CUN/CAL/PreCUN in RP showed a negative correlation with the right eye VF (r=-0.411; P=0.024) and left eye VF (r=-0.426; P=0.019). Our results showed that RP patients showed abnormal function network hubs in various brain regions related to visual, thalamocortical, and sensorimotor networks; these might reflect impaired top-down modulations, visual imagery, and visuomotor coordination in RP patients. Moreover, the DC index can be used as a biomarker to indicate the severity of visual loss in RP patients.

Abnormal intrinsic functional network hubs and connectivity following peripheral visual loss because of inherited retinal degeneration.

There is increasing evidence that patients with retinal vein occlusion exhibit cerebral vascular changes and are at an increased risk of stroke. However, it remains unknown whether patients with retinal vein occlusion exhibit changes in intrinsic brain activity.

Assessment of cerebral low-frequency oscillations in patients with retinal vein occlusion: a preliminary functional MRI study.

Diabetic retinopathy (DR) patients are at an increased risk of cognitive decline and dementia. There is accumulating evidence that specific functional and structural architecture changes in the brain are related to cognitive impairment in DR patients. However, little is known regarding whether the functional architecture of resting-state networks (RSNs) changes in DR patients. The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53 ± 8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63 ± 11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the nine RSNs. Then, two-sample -tests were conducted to investigate different intranetwork FCs within nine RSNs between the two groups. The FNC toolbox was used to assess interactions among RSNs. Pearson correlation analysis was conducted to explore the relationship between intranetwork FCs and clinical variables in the DR group. A receiver operating characteristic (ROC) curve was conducted to assess the ability of the intranetwork FCs of RSNs in discriminating between the two groups. Compared to the HC group, DR patients showed significant decreased intranetwork FCs within the basal ganglia network (BGN), visual network (VN), ventral default mode network (vDMN), right executive control network (rECN), salience network (SN), left executive control network (lECN), auditory network (AN), and dorsal default mode network (dDMN). In addition, FNC analysis showed increased VN-BGN, VN-vDMN, VN-dDMN, vDMN-lECN, SN-BGN, lECN-dDMN, and AN-BGN FNCs in the DR group, relative to the HC group. Furthermore, altered intranetwork FCs of RSNs were significantly correlated with the glycosylated hemoglobin (HbA1c) level in DR patients. A ROC curve showed that these specific intranetwork FCs of RSNs discriminated between the two groups with a high degree of sensitivity and specificity. Our study highlighted that DR patients had widespread deficits in both low-level perceptual and higher-order cognitive networks. Our results offer important insights into the neural mechanisms of visual loss and cognitive decline in DR patients.

Large-Scale Neuronal Network Dysfunction in Diabetic Retinopathy.

Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide but can be a treatable retinal disease with appropriate and timely diagnosis. This study was performed to develop a robust intelligent system based on deep learning to automatically classify the severity of ROP from fundus images and detect the stage of ROP and presence of plus disease to enable automated diagnosis and further treatment.

Automated identification of retinopathy of prematurity by image-based deep learning.

Previously we developed TAT-N24 as a synthetic cell-permeable peptide inhibitor of p55PIK signaling and demonstrated its anti-inflammatory effects. This study aimed to evaluate the potential of TAT-N24 as a new agent for the treatment of ocular inflammatory diseases.

Qin-Qin Deng

Eye Center

Renmin hospital of Wuhan university

Mapping Regional Homogeneity and Functional Connectivity of the Visual Cortex in Resting-State fMRI

Qin-Qin Deng

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Renmin hospital of Wuhan university

Mapping Regional Homogeneity and Functional Connectivity of the Visual Cortex in Resting-State fMRI

Eye Center