Geometric microstructural damage of white matter with functional compensation in post-stroke

Noninvasive brain stimulations modulated brain modular interactions to ameliorate working memory in community-dwelling older adults

Non-invasive brain stimulations have drawn attention in remediating memory decline in older adults. However, it remains unclear regarding the cognitive and neural mechanisms underpinning the neurostimulation effects on memory rehabilitation. We evaluated the intervention effects of 2-weeks of neurostimulations (high-definition transcranial direct current stimulation, HD-tDCS, and electroacupuncture, EA versus controls, CN) on brain activities and functional connectivity during a working memory task in normally cognitive older adults (age 60+, n = 60). Results showed that HD-tDCS and EA significantly improved the cognitive performance, potentiated the brain activities of overlapping neural substrates (i.e. hippocampus, dlPFC, and lingual gyrus) associated with explicit and implicit memory, and modulated the nodal topological properties and brain modular interactions manifesting as increased intramodular connection of the limbic-system dominated network, decreased intramodular connection of default-mode-like network, as well as stronger intermodular connection between frontal-dominated network and limbic-system-dominated network. Predictive model further identified the neuro-behavioral association between modular connections and working memory. This preliminary study provides evidence that noninvasive neurostimulations can improve older adults' working memory through potentiating the brain activity of working memory-related areas and mediating the modular interactions of related brain networks. These findings have important implication for remediating older adults' working memory and cognitive declines.

NODDI Identifies Cognitive Associations with In Vivo Microstructural Changes in Remote Cortical Regions and Thalamocortical Pathways in Thalamic Stroke

The roles of cerebral structures distal to isolated thalamic infarcts in cognitive deficits remain unclear. We aimed to identify the in vivo microstructural characteristics of remote gray matter (GM) and thalamic pathways and elucidate their roles across cognitive domains. Patients with isolated ischemic thalamic stroke and healthy controls underwent neuropsychological assessment and magnetic resonance imaging. Neurite orientation dispersion and density imaging (NODDI) was modeled to derive the intracellular volume fraction (VFic) and orientation dispersion index. Fiber density (FD) was determined by constrained spherical deconvolution, and tensor-derived fractional anisotropy (FA) was calculated. Voxel-wise GM analysis and thalamic pathway tractography were performed. Twenty-six patients and 26 healthy controls were included. Patients exhibited reduced VFic in remote GM regions, including ipsilesional insular and temporal subregions. The microstructural metrics VFic, FD, and FA within ipsilesional thalamic pathways decreased (false discovery rate [FDR]-p < 0.05). Noteworthy associations emerged as VFic within insular cortices (ρ = -0.791 to -0.630; FDR-p < 0.05) and FD in tracts connecting the thalamus and insula (ρ = 0.830 to 0.971; FDR-p < 0.001) were closely associated with executive function. The VFic in Brodmann area 52 (ρ = -0.839; FDR-p = 0.005) and FA within its thalamic pathway (ρ = -0.799; FDR-p = 0.003) correlated with total auditory memory scores. In conclusion, NODDI revealed neurite loss in remote normal-appearing GM regions and ipsilesional thalamic pathways in thalamic stroke. Reduced cortical dendritic density and axonal density of thalamocortical tracts in specific subregions were associated with improved cognitive functions. Subacute microstructural alterations beyond focal thalamic infarcts might reflect beneficial remodeling indicating post-stroke plasticity.

Assessment of bidirectional relationships between brain imaging-derived phenotypes and stroke: a Mendelian randomization study

BACKGROUND

Stroke is a major cause of mortality and long-term disability worldwide. Whether the associations between brain imaging-derived phenotypes (IDPs) and stroke are causal is uncertain.

METHODS

We performed two-sample bidirectional Mendelian randomization (MR) analyses to explore the causal associations between IDPs and stroke. Summary data of 587 brain IDPs (up to 33,224 individuals) from the UK Biobank and five stroke types (sample size range from 301,663 to 446,696, case number range from 5,386 to 40,585) from the MEGASTROKE consortium were used.

RESULTS

Forward MR indicated 14 IDPs belong to projection fibers or association fibers were associated with stroke. For example, higher genetically determined mean diffusivity (MD) in the right external capsule was causally associated with an increased risk of small vessel stroke (IVW OR = 2.76, 95% CI 2.07 to 3.68, P = 5.87 × 10^-12). Reverse MR indicated that genetically determined higher risk of any ischemic stroke was associated with increased isotropic or free water volume fraction (ISOVF) in body of corpus callosum (IVW β = 0.23, 95% CI 0.14 to 0.33, P = 3.22 × 10^-7). This IDP is a commissural fiber and it is not included in the IDPs identified by forward MR.

CONCLUSIONS

We identified 14 IDPs with statistically significant evidence of causal effects on stroke or stroke subtypes. We also identified potential causal effects of stroke on one IDP of commissural fiber. These findings might guide further work toward identifying preventative strategies at the brain imaging levels.

An accelerated degeneration of white matter microstructure and networks in the nondemented old-old

The nondemented old-old over the age of 80 comprise a rapidly increasing population group; they can be regarded as exemplars of successful aging. However, our current understanding of successful aging in advanced age and its neural underpinnings is limited. In this study, we measured the microstructural and network-based topological properties of brain white matter using diffusion-weighted imaging scans of 419 community-dwelling nondemented older participants. The participants were further divided into 230 young-old (between 72 and 79, mean = 76.25 ± 2.00) and 219 old-old (between 80 and 92, mean = 83.98 ± 2.97). Results showed that white matter connectivity in microstructure and brain networks significantly declined with increased age and that the declined rates were faster in the old-old compared with young-old. Mediation models indicated that cognitive decline was in part through the age effect on the white matter connectivity in the old-old but not in the young-old. Machine learning predictive models further supported the crucial role of declines in white matter connectivity as a neural substrate of cognitive aging in the nondemented older population. Our findings shed new light on white matter connectivity in the nondemented aging brains and may contribute to uncovering the neural substrates of successful brain aging.

Suboptimal states and frontoparietal network-centered incomplete compensation revealed by dynamic functional network connectivity in patients with post-stroke cognitive impairment

Background

Neural reorganization occurs after a stroke, and dynamic functional network connectivity (dFNC) pattern is associated with cognition. We hypothesized that dFNC alterations resulted from neural reorganization in post-stroke cognitive impairment (PSCI) patients, and specific dFNC patterns characterized different pathological types of PSCI.

Methods

Resting-state fMRI data were collected from 16 PSCI patients with hemorrhagic stroke (hPSCI group), 21 PSCI patients with ischemic stroke (iPSCI group), and 21 healthy controls (HC). We performed the dFNC analysis for the dynamic connectivity states, together with their topological and temporal features.

Results

We identified 10 resting-state networks (RSNs), and the dFNCs could be clustered into four reoccurring states (modular, regional, sparse, and strong). Compared with HC, the hPSCI and iPSCI patients showed lower standard deviation (SD) and coefficient of variation (CV) in the regional and modular states, respectively (p &lt; 0.05). Reduced connectivities within the primary network (visual, auditory, and sensorimotor networks) and between the primary and high-order cognitive control domains were observed (p &lt; 0.01).

Conclusion

The transition trend to suboptimal states may play a compensatory role in patients with PSCI through redundancy networks. The reduced exploratory capacity (SD and CV) in different suboptimal states characterized cognitive impairment and pathological types of PSCI. The functional disconnection between the primary and high-order cognitive control network and the frontoparietal network centered (FPN-centered) incomplete compensation may be the pathological mechanism of PSCI. These results emphasize the flexibility of neural reorganization during self-repair.

A High Neutrophil-to-Lymphocyte Ratio Predicts Higher Risk of Poststroke Cognitive Impairment: Development and Validation of a Clinical Prediction Model

Objective

Poststroke cognitive impairment (PSCI) is a serious complication of stroke. The neutrophil-to-lymphocyte ratio (NLR) is a marker of peripheral inflammation. The relationship between the NLR and PSCI is far from well studied, and the thesis of this study was to assess the predictive value of the NLR in patients with PSCI, and establish and verify the corresponding prediction model based on this relationship.

Methods

A total of 367 stroke patients were included in this study. Neutrophils, lymphocytes, and NLRs were measured at baseline, and clinical and neuropsychological assessments were conducted 3 months after stroke. The National Institutes of Health Scale (NIHSS) was used to assess the severity of stroke. A Chinese version of the Mini Mental State Examination (MMSE) was used for the assessment of cognitive function.

Results

After three months of follow-up, 87 (23.7%) patients were diagnosed with PSCI. The NLR was significantly higher in PSCI patients than in non-PSCI patients (P &lt; 0.001). Patient age, sex, body mass index, NIHSS scores, and high-density lipoprotein levels also differed in the univariate analysis. In the logistic regression analysis, the NLR was an independent risk factor associated with the patients with PSCI after adjustment for potential confounders (OR = 1.67, 95%CI: 1.21–2.29, P = 0.002). The nomogram based on patient sex, age, NIHSS score, and NLR had good predictive power with an AUC of 0.807. In the validation group, the AUC was 0.816.

Conclusion

An increased NLR at admission is associated with PSCI, and the model built with NLR as one of the predictors can increase prognostic information for the early detection of PSCI.

Evaluation of White Matter Microstructural Alterations in Patients with Post-Stroke Cognitive Impairment at the Sub-Acute Stage

PURPOSE

To investigate white matter alterations in post-stroke cognitive impairment (PSCI) patients at the subacute stage employing diffusion kurtosis and tensor imaging.

METHODS

Thirty PSCI patients at the subacute phase and 30 healthy controls (HC) underwent diffusion kurtosis imaging (DKI) scans and neuropsychological assessments. Based on the tract-based spatial statistics and atlas-based ROI analysis, fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), kurtosis fractional anisotropy (KFA), axial kurtosis (AK), and radial kurtosis (RK) were compared in specific white matter fiber bundles between the groups (with family-wise error correction). Adjusting for age and gender, a partial correlation was conducted between neurocognitive assessments and DKI metrics in the PSCI group.

RESULTS

In comparison with the HC, PSCI patients significantly showed decreased MK, RK, and FA and increased MD values in the genu of corpus callosum, anterior limb internal capsule, and left superior corona radiata. In addition, DKI detected more white matter region changes in MK (31/48), KFA (40/48), and RK (25/48) than DTI with FA (28/48) and MD (21/48), which primarily consisted of the right cingulum, right superior longitudinal fasciculus, and left posterior limb of internal capsule. In the left anterior limb of internal capsule, MK and RK values were significantly negatively correlated with TMT-B (r = -0.435 and -0.414, P < 0.05), and KFA values (r = -0.385, P < 0.05) of corpus callosum negatively associated with TMT-B.

CONCLUSION

Combing DTI, DKI, and neuropsychological tests, we found extensive damaged white matter microstructure and poor execution performance in subacute PSCI patients. DKI could detect more subtle white matter changes than DTI metrics. Our findings provide added information for exploring the mechanisms of PSCI and conducting cognitive rehabilitation in the subacute stage.