Leukoaraiosis (LA) is associated with cognitive impairment in the older people which can be demonstrated in functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI). This study is to explore the FC changes in LA patients with different cognitive status by three network models. Fifty-three patients with LA were divided into three groups: the normal cognition (LA-NC; n = 14, six males), mild cognitive impairment (LA-MCI; n = 27, 13 males), and vascular dementia (LA-VD; n = 12, six males), according to the Mini Mental State Exam (MMSE) and Clinical Dementia Rating (CDR). The three groups and 30 matched healthy controls (HCs; 11 males) underwent rs-fMRI. The data of rs-fMRI were analyzed by independent components analysis (ICA) and region of interest (ROI) analysis by the REST toolbox. Then the FC was respectively analyzed by the default-mode network (DMN), salience networks (SNs) and the central executive network (CEN) with their results compared among the different groups. For inter-brain network analysis, there were negative FC between the SN and DMN in LA groups, and the FC decreased when compared with HC group. While there were enhanced inter-brain network FC between the SN and CEN as well as within the SN. The FC in patients with LA can be detected by different network models of rs-fMRI. The multi-model analysis is helpful for the further understanding of the cognitive changes in those patients.

Background and Purpose: Non-alcoholic fatty liver disease (NAFLD) and cognitive impairment are common aging-related disorders. This study aims to explore the changes of cognitive function in middle-aged and elderly population with NAFLD from a Jidong impairment cohort.Methods: A total of 1,651 middle-aged and elderly participants (>40 years) without cognitive impairment were recruited into the current study in 2015 and were followed up until to 2019. Abdominal ultrasonography was used for diagnosis of NAFLD. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE). Cognitive impairment was defined as a score <18 for illiterates, a score <21 for primary school graduates, and a score <25 for junior school graduates or above. Multivariable regression analysis was performed to evaluate the association between NAFLD and the four-year cognitive changes.Results: Out of 1,651 participants, 795 (48.2%) of them had NAFLD in 2015. Cognitive impairment occurred in 241 (14.6%) participants in 2019. Patients with NAFLD had higher 4-year incidence of cognitive impairment than non-NAFLD patients did (17.7 vs. 11.7%, p < 0.001). Multivariable linear regression analysis showed significant association of baseline NAFLD with lower MMSE score in 2019 (β = −0.36, p < 0.05). Multivariable logistic analysis found that the adjusted odds ratio (OR) with 95% confidence interval (CI) of baseline NAFLD was 1.45 (1.00–2.11) for cognitive impairment in 2019 (p = 0.05). We also identified effects of baseline NAFLD on subsequent cognitive impairment as modified by age (interaction p < 0.01) and carotid stenosis (interaction p = 0.05) but not by gender.Conclusions: NAFLD is associated with cognitive decline, especially in middle-aged and with carotid stenosis population.

BACKGROUND Leukoaraiosis is characterized by white matter lesions (WMLs) on magnetic resonance imaging (MRI) and is associated with cognitive impairment. The small-world network is viewed as the optimal brain network with maximal efficiency in information processing. Patients with cognitive impairment are thought to have disrupted small-world networks. In this study, we compared the small-world network attributes between controls (study participants without memory complaints) and patients with WMLs with cognitive impairment. MATERIAL AND METHODS All study participants were prescreened using MRI and neuropsychological tests. Patients with WMLs were further divided into 2 groups according to the result of Montreal Cognitive Assessment (MoCA), i.e., WMLs with non-dementia vascular cognitive impairment (WMLs-VCIND) and WMLs with vascular dementia (WMLs-VaD). Resting-state functional MRI data were collected and applied with graph theoretical analysis to compare small-world properties between the 3 groups. RESULTS We found that the overall functional connectivity strength was lowest in the WMLs-VaD patients but highest in the normal control study participants. Patients in both the WMLs-VCIND and the WMLs-VaD groups had decreased small-world properties compared with the group of normal control study participants. Moreover, the small-world properties significantly correlated with MoCA scores. CONCLUSIONS These findings suggest potential constructive reorganization of brain networks secondary to WMLs, and provides novel insights into the role of small-world properties in cognitive dysfunction in WMLs.

Background: To examine the effect of the triglyceride-glucose (TyG) index on longitudinal cognitive decline in a healthy middle-aged-to-elderly population. Methods: We conducted a population-based longitudinal study. A total of 1774 participants without cognitive impairment were enrolled in the 4-year follow-up. They were divided into four groups according to the quartile of the TyG index. Multivariable-adjusted Cox proportional hazard models were performed to examine the association between the TyG index and cognitive decline. Discrimination tests were used to evaluate the incremental predictive value of the TyG index beyond conventional risk factors. Results: During the follow-up, compared with those in the bottom quartile group, participants in the top TyG quartile group presented a 51% increase in the risk of cognitive decline (OR 1.51 (95% CI: 1.06–2.14)). As shown by discrimination tests, adding the TyG index into the conventional model resulted in a slight improvement in predicting the risk of cognitive decline (NRI 16.00% (p = 0.004)). Conclusion: This study demonstrated that increasing values of the TyG index were positively associated with the risk of cognitive decline. Monitoring the TyG index may help in the early identification of individuals at high risk of cognitive deterioration.

Accumulating evidence has shown the effectiveness of cognitive interventions, which can be divided into cognitive training (CT), cognitive stimulation (CS), cognitive rehabilitation (CR), and combined interventions (i.e., cognitive interventions combined with other non-pharmacological interventions such as physical exercise), in individuals with Alzheimer’s disease (AD). However, the effectiveness of cognitive interventions varies greatly among studies and more comprehensive studies are required. We aimed to evaluate whether the current evidence shows that cognitive interventions are effective at improving cognition, neuropsychiatric symptoms, depression, quality of life, and basic activities of daily living among individuals with possible or probable AD. Randomized controlled trials of all types of cognitive intervention were identified for inclusion in pairwise and network meta-analyses. There was a moderate and statistically significant post-intervention improvement in global cognition among individuals with AD for all types of cognitive intervention compared to control interventions (39 studies, g = 0.43, 95% CI: 0.28 to 0.58, p < 0.01; Q = 102.27, df = 38, p < 0.01; I² = 61.97%, τ² = 0.13). Regarding the specific types of cognitive intervention, combined interventions had the highest surface under the cumulative ranking curve (SUCRA) value (90.7%), followed by CT (67.8%), CS (53.4%), and lastly CR (28.9%). Significant effects of cognitive interventions were also found for working memory, verbal memory, verbal fluency, confrontation naming, attention, neuropsychiatric symptoms, basic activities of daily living, and quality of life.

Background: Non-linguistic cognitive training has been suggested to improve the communication skills of patients with post-stroke aphasia (PSA). However, the association between language and non-linguistic cognitive functions is not fully understood. In this study, we used the Loewenstein Occupational Therapy Cognitive Assessment (LOTCA) to evaluate the characteristics of non-linguistic cognitive impairments in Chinese PSA patients. Methods: A total of 86 stroke patients were recruited in this study. Language and non-linguistic cognitive impairments were evaluated by the Western Aphasia Battery (WAB) and LOTCA, respectively. The patients were divided into two groups (PSA and non-PSA), and the Chinese norm (the data came from 44 Chinese individuals without neurological disorders in a previous study) was used as the control group. The LOTCA scores were compared among the three groups. Patients in the PSA group were subdivided into the fluent aphasia group (FAG) and the non-FAG according to the Chinese aphasia fluency characteristic scale. The LOTCA scores were also compared between the PSA subdivisions. Potential confounders were adjusted in the analysis of covariance. Partial correlation analysis between the subscores of WAB and LOTCA was also performed. Results: The total LOTCA scores in the PSA group (75.11 ± 17.08) were significantly lower compared with scores in the non-PSA (96.80 ± 7.75, P < 0.001) and the control group (97.65 ± 16.24, P < 0.001). The PSA group also had lower orientation, visual perception (VP), spatial perception (SP), visuomotor organization, thinking operation, and attention scores. The total LOTCA, orientation, VP, SP, and MP scores were lower in the non-FAG (69.24 ± 18.06, 8.62 ± 5.09, 12.76 ± 2.47, 7.48 ± 3.01, and 9.62 ± 2.25, respectively) compared with the FAG (80.36 ± 14.07, 12.14 ± 3.99, 14.09 ± 1.93, 9.68 ± 3.01, 10.55 ± 1.63, respectively, P's < 0.05). The aphasia quotient was positively correlated with the total score of LOTCA and scores of orientation, VP, SP, and MP (r = 0.710, 0.744, 0.565, 0.597, and 0.616; P < 0.001). Conclusion: Compared with stroke patients without aphasia, patients with PSA often have more extensive and serious non-linguistic cognitive impairments. Patients with non-fluent aphasia often present with serious cognitive impairments than those with fluent aphasia, especially the impairments of orientation and SP. Non-linguistic cognitive impairments correlate with language impairments in aphasia.