Disrupted structural network of inferomedial temporal regions in relapsing-remitting multiple sclerosis compared with neuromyelitis optica spectrum disorder.

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are two representative chronic inflammatory demyelinating disorders of the central nervous system. We aimed to determine and compare the alterations of white matter (WM) connectivity between MS, NMOSD, and healthy controls (HC). This study included 68 patients with relapsing-remitting MS, 50 with NMOSD, and 26 HC. A network-based statistics method was used to assess disrupted patterns in WM networks. Topological characteristics of the three groups were compared and their associations with clinical parameters were examined. WM network analysis indicated that the MS and NMOSD groups had lower total strength, clustering coefficient, global efficiency, and local efficiency and had longer characteristic path length than HC, but there were no differences between the MS and NMOSD groups. At the nodal level, the MS group had more brain regions with altered network topologies than did the NMOSD group when compared with the HC group. Network alterations were correlated with Expanded Disability Status Scale score and disease duration in both MS and NMOSD groups. Two distinct subnetworks that characterized the disease groups were also identified. When compared with NMOSD, the most discriminative connectivity changes in MS were located between the thalamus, hippocampus, parahippocampal gyrus, amygdala, fusiform gyrus, and inferior and superior temporal gyri. In conclusion, MS patients had greater network dysfunction compared to NMOSD and altered short connections within the thalamus and inferomedial temporal regions were relatively spared in NMOSD compared with MS.

Decreased Cortical Thickness and Local Gyrification in Individuals with Subjective Cognitive Impairment.

OBJECTIVE: Subjective cognitive impairment (SCI) is associated with future cognitive decline. This study aimed to compare cortical thickness and local gyrification index (LGI) between individuals with SCI and normal control (NC) subjects. METHODS: Forty-seven participants (27 SCI and 20 NC) were recruited. All participants underwent brain magnetic resonance imaging scanning and were clinically assessed using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery of tests. We compared cortical thickness and LGI between the two groups and analyzed correlations between cortical thickness/LGI and scores on CERAD protocol subtests in the SCI group for region of interests with significant between-group differences. RESULTS: Cortical thickness reduction in the left entorhinal, superior temporal, insular, rostral middle frontal, precentral, superior frontal, and supramarginal regions, and right supramarginal, precentral, insular, postcentral, and posterior cingulate regions was observed in the SCI compared to the NC group. Cortical thickness in these regions correlated with scores of constructional praxis, word list memory, word list recall, constructional recall, trail making test A, and verbal fluency under the CERAD protocol. Significantly decreased gyrification was observed in the left lingual gyrus of the SCI group. In addition, gyrification of this region was positively associated with scores of constructional praxis. CONCLUSION: Our results may provide an additional reference to the notion that SCI may be associated with future cognitive impairment. This study may help clinicians to assess individuals with SCI who may progress to mild cognitive impairment and Alzheimer's dementia.

Overconnectivity of the right Heschl's and inferior temporal gyrus correlates with symptom severity in preschoolers with autism spectrum disorder.

Previous studies have reported varying findings regarding the association of brain connectivity in autism spectrum disorder (ASD) with overconnectivity, underconnectivity, or both. Despite the emerging understanding that ASD is a developmental disconnection syndrome, very little is known about structural brain networks in preschool-aged children with low-functioning ASD. We aimed to investigate the structural brain connectivity of low-functioning ASD using diffusion magnetic resonance imaging and graph theory to examine alterations in different brain network topologies and identify any correlations with the clinical severity of ASD in preschool-aged children. Fifty-two preschool-aged children (28 with ASD and 24 with typical development) were included in the analysis. Graph-based network analysis was performed to examine the global and local structural brain networks. Nodal network measures exhibited increased nodal strength in the right Heschl's gyrus, which was positively associated with all autistic clinical symptoms (Autism Diagnostic Observation Schedule and Childhood Autism Rating Scale [CARS]). The nodal strength of the right inferior temporal gyrus showed a moderate correlation with the CARS score. Using network-based statistics, we identified a subnetwork with increased connections encompassing the right Heschl's gyrus and the right inferior temporal gyrus in preschool-aged children with ASD. The asymmetric value in the inferior temporal gyrus exhibited right dominance of nodal strength in children with ASD compared to that in typically developing children. Our findings support the theory of aberrant brain growth and overconnectivity as the underlying mechanism of ASD and provides new insights into potential regional biomarkers that can detect low-functioning ASD in preschool-aged children. LAY SUMMARY: This study supports the theory of aberrant brain growth and overconnectivity as an explanation for ASD. Measuring the right HG and inferior temporal gyrus provides new insights of potential regional biomarkers underpinning ASD in preschool-aged children.

Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression.

Late-life depression (LLD) may increase the risk of Alzheimer's dementia (AD). While amyloidopathy accelerates AD progression, its role in such patients has not yet been elucidated. We hypothesized that cerebral amyloidopathy distinctly affects the alteration of brain network topology and may be associated with distinct cognitive symptoms. We recruited 26 and 27 depressed mild cognitive impairment (MCI) patients with (LLD-MCI-A(+)) and without amyloid accumulation (LLD-MCI-A(-)), respectively, and 21 normal controls. We extracted structural brain networks using their diffusion-weighted images. We aimed to compare the distinct network deterioration in LLD-MCI with and without amyloid accumulation and the relationship with their distinct cognitive decline. Thus, we performed a group comparison of the network topological measures and investigated any correlations with neurocognitive testing scores. Topological features of brain networks were different according to the presence of amyloid accumulation. Disrupted network connectivity was highly associated with impaired recall and recognition in LLD-MCI-A(+) patients. Inattention and dysexecutive function were more influenced by the altered networks involved in fronto-limbic circuitry dysfunction in LLD-MCI-A(-) patients. Our results show that alterations in brain network topology may reflect different cognitive dysfunction depending on amyloid accumulation in depressed older adults with MCI.

Comparison of neurodegenerative types using different brain MRI analysis metrics in older adults with normal cognition, mild cognitive impairment, and Alzheimer's dementia.

Several metrics of analysis of magnetic resonance imaging (MRI) have been used to assess Alzheimer's disease (AD)-related neurodegeneration. We compared four structural brain MRI analysis metrics, cortical thickness, volume, surface area, and local gyrification index (LGI), in different stages of AD-related cognitive decline. Participants with normal cognition, mild cognitive impairment, and AD were included (34 participants per group). All undertook the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) battery of neuropsychological tests and brain MRI scanning. We analyzed associations between morphometric measures and CERAD total/ Mini Mental State Examination (MMSE) scores for the regions of interest (ROIs), identifying three types of curves: U-shaped, inverted U-shaped, and linear. Cortical thickness and volume analyses showed linear types in most of the significant ROIs. Significant ROIs for the cortical thickness analysis were located in the temporal and limbic lobes, whereas those for volume and surface area were distributed over more diffuse areas of the brain. LGI analysis showed few significant ROIs. CERAD total scores were more sensitive to early changes of cortical structures than MMSE scores. Cortical thickness analysis may be preferable in assessing brain structural MRI changes during AD-related cognitive decline, whereas LGI analysis may have limited capability to reflect the cognitive decrease. Our findings may provide a reference for future studies and help to establish optimal analytical approaches to brain structural MRI in neurodegenerative diseases.

Diffusion tensor imaging reveals abnormal brain networks in elderly subjects with subjective cognitive deficits.

PURPOSE: Some elders with subjective cognitive deficits (SCD) develop prodromal phase of dementia over time; however, little is known about how they differ from those with normal cognition (NC). Thus, we aim to distinguish the differences in the brain network of elders with SCD and NC. METHODS: Multiple diffusion-weighted images (DWI) and T1-weighted images were obtained from 18 subjects with NC and 26 subjects with SCD. Using network-based statistics (NBS) analysis, we extracted abnormal brain subnetworks and localized abnormal brain connectivity. We also ran correlation analysis to compare the affected regions and the results of the neurocognitive assessments. RESULTS: Altered subnetworks were found in the superior parietal gyrus, angular gyrus, precuneus, posterior cingulum, putamen, precentral gyrus, postcentral gyrus, and paracentral lobule. They were also associated with scores on the word list recall, word list recognition, and Boston naming test. CONCLUSIONS: Elders with SCD had distinctive brain network alterations when compared with those of elders with NC. The results are also in line with the previously identified characteristics of mild cognitive impairment (MCI) and of Alzheimer's disease (AD) in a milder form. We speculate that it may be possible to predict AD progression early in the SCD stage using NBS analysis.