Analysis of correlation between white matter changes and functional responses in thalamic stroke: a DTI & EEG study

Neuroimaging of motor recovery after ischemic stroke - functional reorganization of motor network

The long-term motor outcome of acute stroke patients may be correlated to the reorganization of brain motor network. Abundant neuroimaging studies contribute to understand the pathological changes and recovery of motor networks after stroke. In this review, we summarized how current neuroimaging studies have increased understanding of reorganization and plasticity in post stroke motor recovery. Firstly, we discussed the changes in the motor network over time during the motor-activation and resting states, as well as the overall functional integration trend of the motor network. These studies indicate that the motor network undergoes dynamic bilateral hemispheric functional reorganization, as well as a trend towards network randomization. In the second part, we summarized the current study progress in the application of neuroimaging technology to early predict the post-stroke motor outcome. In the third part, we discuss the neuroimaging techniques commonly used in the post-stroke recovery. These methods provide direct or indirect visualization patterns to understand the neural mechanisms of post-stroke motor recovery, opening up new avenues for studying spontaneous and treatment-induced recovery and plasticity after stroke.

Exploring resting-state EEG oscillations in patients with Neuromyelitis Optica Spectrum Disorder

BACKGROUND AND OBJECTIVE

Quantitative resting-state electroencephalography (rs-EEG) is a convenient method for characterizing the functional impairments and adaptations of the brain that has been shown to be valuable for assessing many neurological and psychiatric disorders, especially in monitoring disease status and assisting neuromodulation treatment. However, it has not yet been explored in patients with neuromyelitis optica spectrum disorder (NMOSD). This study aimed to investigate the rs-EEG features of NMOSD patients and explore the rs-EEG features related to disease characteristics and complications (such as anxiety, depression, and fatigue).

METHODS

A total of 32 NMOSD patients and 20 healthy controls (HCs) were recruited; their demographic and disease information were collected, and their anxiety, depression, and fatigue symptoms were evaluated. The rs-EEG power spectra of all the participants were obtained. After excluding the participants with low-quality rs-EEG data during processing, statistical analysis was conducted based on the clinical information and rs-EEG data of 29 patients and 19 HCs. The rs-EEG power (the mean spectral energy (MSE) of absolute power and relative power in all frequency bands, as well as the specific power for all electrode sites) of NMOSD patients and HCs was compared. Furthermore, correlation analyses were performed between rs-EEG power and other variables for NMOSD patients (including the disease characteristics and complications).

RESULTS

The distribution of the rs-EEG power spectra in NMOSD patients was similar to that in HCs. The dominant alpha-peaks shifted significantly towards a lower frequency for patients when compared to HCs. The delta and theta power was significantly increased in the NMOSD group compared to that in the HC group. The alpha oscillation power was found to be significantly negatively associated with the degree of anxiety (reflected by the anxiety subscore of hospital anxiety and depression scale (HADS)) and the degree of depression (reflected by the depression subscore of HADS). The gamma oscillation power was revealed to be significantly positively correlated with the fatigue severity scale (FSS) score, while further analysis indicated that the electrode sites of almost the whole brain region showing correlations with fatigue. Regarding the disease variables, no statistically significant rs-EEG features were related to the main disease features in NMOSD patients.

CONCLUSION

The results of this study suggest that the rs-EEG power spectra of NMOSD patients show increased slow oscillations and are potential biomarkers of widespread white matter microstructural damage in NMOSD. Moreover, this study revealed the rs-EEG features associated with anxiety, depression, and fatigue in NMOSD patients, which might help in the evaluation of these complications and the development of neuromodulation treatment. Quantitative rs-EEG analysis may play an important role in the management of NMOSD patients, and future studies are warranted to more comprehensively understand its application value.

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 corticospinal tract remodeling based on diffusion tensor imaging in the treatment of motor dysfunction after ischemic stroke by acupuncture: A meta-analysis

BACKGROUND

To investigate the efficacy of acupuncture in improving motor dysfunction after ischemic stroke (IS) and to investigate the effect of acupuncture on corticospinal tract (CST) remodeling using diffusion tensor imaging.

METHODS

Published literature on the effect of acupuncture on CST remodeling after IS using diffusion tensor imaging in the form of randomized controlled trials (RCTs) were systematically retrieved and screened from Cochrane Library, Web of Science, PubMed, Embase, CNKI, CBM, VIP, and Wanfang databases from inception to December 2022. The methodological quality of the included studies was critically and independently evaluated by 2 reviewers using the Cochrane Risk of Bias Assessment Tool for RCTs. The correlated data were extracted using the pre-designed form, and all analyses were performed using Reviewer Manager version 5.4.

RESULTS

Eleven eligible RCTs involving 459 patients were eventually included. The combined evidence results showed that the acupuncture group significantly improved patients' National Institute of Health stroke scale, Fugl-Meyer Assessment Scale, and Barthel index compared with conventional medical treatment. The acupuncture group significantly promoted remodeling of the CST, as reflected by an increase in fractional anisotropy (FA) throughout the CST [MD = 0.04, 95% CI (0.02, 0.07), P = .001], and in addition, subgroup analysis showed that the acupuncture group significantly improved FA in the infarct area compared with conventional medical treatment at around 4 weeks [MD = 0.04, 95% CI (0.02, 0.06), P = .0002] and FA of the affected cerebral peduncle [MD = 0.03, 95% CI (0.00, 0.07), P = .02]. Also, compared with conventional medical treatment, the acupuncture group significantly increased average diffusion coefficient of the affected cerebral peduncle [MD = -0.21, 95% CI (-0.28, -0.13), P < .00001].

CONCLUSION

The results of the meta-analysis suggest that acupuncture therapy can improve the clinical manifestations of motor dysfunction in patients after IS and advance a possibly beneficial effect on CST remodeling. However, due to the number and quality of eligible studies, these findings need to be further validated in more standardized, rigorous, high-quality clinical trials.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

Brain Structural and Functional Connectivity: A Review of Combined Works of Diffusion Magnetic Resonance Imaging and Electro-Encephalography

Implications of structural connections within and between brain regions for their functional counterpart are timely points of discussion. White matter microstructural organization and functional activity can be assessed in unison. At first glance, however, the corresponding findings appear variable, both in the healthy brain and in numerous neuro-pathologies. To identify consistent associations between structural and functional connectivity and possible impacts for the clinic, we reviewed the literature of combined recordings of electro-encephalography (EEG) and diffusion-based magnetic resonance imaging (MRI). It appears that the strength of event-related EEG activity increases with increased integrity of structural connectivity, while latency drops. This agrees with a simple mechanistic perspective: the nature of microstructural white matter influences the transfer of activity. The EEG, however, is often assessed for its spectral content. Spectral power shows associations with structural connectivity that can be negative or positive often dependent on the frequencies under study. Functional connectivity shows even more variations, which are difficult to rank. This might be caused by the diversity of paradigms being investigated, from sleep and resting state to cognitive and motor tasks, from healthy participants to patients. More challenging, though, is the potential dependency of findings on the kind of analysis applied. While this does not diminish the principal capacity of EEG and diffusion-based MRI co-registration, it highlights the urgency to standardize especially EEG analysis.

QEEG as a Useful Tool for the Evaluation of Early Cognitive Changes in Dementia and Traumatic Brain Injury

Quantitative electroencephalography (QEEG)-electrical neuroimaging has been underutilized in general neurology practice. Recent advances in computer technology have made this electrophysiological testing relatively inexpensive as well as precise in identifying brain areas with electrical dysfunction related to either traumatic injury or neurodegenerative process. In this article, the author presents 2 cases that can be frequently encountered in every general neurological practice: case of early dementia and traumatic brain injury. The clinical usefulness of QEEG is demonstrated by showing evidence of electrical abnormalities and networks dysfunctions (including an elevation of frontal/temporal delta and theta powers as well as abnormalities in functional connectivity). In addition, the correlation of QEEG and findings from structural imaging technique-magnetic resonance imaging diffusion tensor imaging and another functional imaging-positron emission tomography is presented.

Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG)

An electroencephalogram (EEG) is a significant source of diagnosing brain issues. It is also a mediator between the external world and the brain, especially in the case of any mental illness; however, it has been widely used to monitor the dynamics of the brain in healthy subjects. This paper discusses the resting state of the brain with eyes open (EO) and eyes closed (EC) by using sixteen channels by the use of conventional frequency bands and entropy of the EEG signal. The Fast Fourier Transform (FFT) and sample entropy (SE) of each sensor are computed as methods of feature extraction. Six classifiers, including logistic regression (LR), K-Nearest Neighbors (KNN), linear discriminant (LD), decision tree (DT), support vector machine (SVM), and Gaussian Naive Bayes (GNB) are used to discriminate the resting states of the brain based on the extracted features. EEG data were epoched with one-second-length windows, and they were used to compute the features to classify EO and EC conditions. Results showed that the LR and SVM classifiers had the highest average classification accuracy (97%). Accuracies of LD, KNN, and DT were 95%, 93%, and 92%, respectively. GNB gained the least accuracy (86%) when conventional frequency bands were used. On the other hand, when SE was used, the average accuracies of SVM, LD, LR, GNB, KNN, and DT algorithms were 92% 90%, 89%, 89%, 86%, and 86%, respectively.

Clinical Features of Thalamic Stroke

OPINION STATEMENT

The thalamus plays an important role in different brain functions including memory, emotions, sleep-wake cycle, executive functions, mediating general cortical alerting responses, processing of sensory (including taste, somatosensory, visual, and auditory) information and relaying it to the cortex, and sensorimotor control. Thalamic stroke, both in isolation and in combination with infarcts involving other structures, are not rare. The functional complexity of the thalami nuclei and the not uncommon normal variations of arteries supply the thalamus induce wide variations in presentation of thalami infarcts. In patients with an unusual collection of deficits difficult to explain by a single lesion, in particular where there is impaired vigilance, thalamic disease should be considered which may mimic several different neurological conditions. By researching the literature, we found that the characteristic stroke syndrome of paramedian thalamic infarction is probably underdiagnosed. In addition to thalamic infarct, thalamic lesions can be caused by deep cerebral venous thrombosis with neuropsychological and radiological features that should be considered in the differential diagnosis of intracranial artery occlusion or bleeding, especially in young patients.

White matter injury in ischemic stroke

Stroke is one of the major causes of disability and mortality worldwide. It is well known that ischemic stroke can cause gray matter injury. However, stroke also elicits profound white matter injury, a risk factor for higher stroke incidence and poor neurological outcomes. The majority of damage caused by stroke is located in subcortical regions and, remarkably, white matter occupies nearly half of the average infarct volume. Indeed, white matter is exquisitely vulnerable to ischemia and is often injured more severely than gray matter. Clinical symptoms related to white matter injury include cognitive dysfunction, emotional disorders, sensorimotor impairments, as well as urinary incontinence and pain, all of which are closely associated with destruction and remodeling of white matter connectivity. White matter injury can be noninvasively detected by MRI, which provides a three-dimensional assessment of its morphology, metabolism, and function. There is an urgent need for novel white matter therapies, as currently available strategies are limited to preclinical animal studies. Optimal protection against ischemic stroke will need to encompass the fortification of both gray and white matter. In this review, we discuss white matter injury after ischemic stroke, focusing on clinical features and tools, such as imaging, manifestation, and potential treatments. We also briefly discuss the pathophysiology of WMI and future research directions.