Dynamic changes of resting state functional network following acute ischemic stroke

Alterations of static and dynamic changes in intrinsic brain activity and its relation to behavioral outcomes in subcortical ischemic stroke after one-month intervention

Ischemic stroke is a prominent contributor to cognitive dysfunction and disability. Gaining a comprehensive understanding of the neuronal activity and longitudinal changes underlying stroke is crucial for designing effective rehabilitative strategies. However, the neural mechanisms responsible for the longitudinal reorganization of neuronal activity following stroke remain unclear. The objective of this study was to comprehensively investigate potential abnormalities in brain activity among stroke patients before and after one month of intervention (antiplatelet therapy, as well as intravenous citicoline). To achieve this goal, we combined static and dynamic functional imaging indicators for the comprehensive analysis. Twenty ischemic stroke patients at the subacute stage and seventeen age-matched healthy controls were included in the final analysis of this study from one center. Additionally, resting-state functional magnetic imaging scans were conducted on all patients twice with a one-month interval between scans. Four static intrinsic brain activity indicators (static amplitude of low-frequency fluctuation (sALFF), static fractional amplitude of low-frequency fluctuation (sfALFF), static regional homogeneity (sReHo), and static degree centrality (sDC)), along with their corresponding dynamic indicators, were calculated to detect longitudinal alterations in brain activity following stroke onset. Correlation analyses were also performed between these indicators within areas exhibiting group differences as well as clinical scale scores and disease duration. Significant variations in these static and dynamic image indicators were observed among patients with ischemic stroke. There was substantial overlap among the abnormal brain regions detected, primarily including decreased sALFF/sfALFF/dALFF in the bilateral central precuneus, increased sfALFF/sReHo/sDC/dReHo in the left superior precuneus, increased sALFF/sReHo/dfALFF in the left inferior temporal gyrus, decreased sReHo/sDC in the anterior cingulate cortex, increased sReHo/dfALFF in the right inferior parietal lobe, increased sfALFF/sDC in the right fusiform gyrus, as well as decreased sALFF/dALFF and increased sReHo/sDC in the right angular gyrus. Furthermore, these disrupted image indicators in some regions exhibited only partial recovery at the second time point. The percentage changes of these image indicators (sfALFF in the bilateral central precuneus, sDC in the left fusiform and dALFF in the right central precuneus) between the two time points were positively correlated with the percentage changes of clinical scores (FMA and MBI). In combination, this study demonstrates that a comprehensive understanding of abnormal activity and its longitudinal changes in ischemic stroke can be achieved by integrating static and dynamic imaging methods. Regions showing significant overlap among different brain activity indicators and exhibiting consistent image-behavior relationships may have some potential values for predicting clinical outcomes.

Frequency-Dependent Changes in Wavelet-ALFF in Patients With Acute Basal Ganglia Ischemic Stroke: A Resting-State fMRI Study

Background and Purpose: Motor impairment is a common occurrence in patients with acute basal ganglia (BG) ischemic stroke (ABGIS). However, the underlying mechanisms of poststroke motor dysfunction remain incompletely elucidated. In this study, we employed multifrequency band wavelet transform-based amplitude of low-frequency fluctuations (Wavelet-ALFFs) to investigate the alterations of spontaneous regional neural activity in patients with ABGIS. Methods: A total of 39 ABGIS patients with motor dysfunction and 45 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Wavelet-ALFF values were calculated in the conventional frequency band (0.01-0.08 Hz), slow-5 frequency band (0.01-0.027 Hz), and slow-4 frequency band (0.027-0.073 Hz). A two-sample t-test was performed to compare the Wavelet-ALFF values between the two groups with sex as a covariate and Gaussian random field (GRF) theory (voxel p < 0.001, cluster p < 0.05, two-tailed) was used for the multiple corrections. Furthermore, spearman correlation analysis was performed to assess the relationship between alterations in regional neural activity between Fugl-Meyer Assessment (FMA) and National Institutes of Health Stroke Scale (NIHSS) scores. Results: In comparison to HCs, patients with ABGIS showed significantly increased Wavelet-ALFF in the left middle temporal gyrus (MTG) and decreased Wavelet-ALFF in the right inferior frontal operculum (IFO) across all three frequency bands (conventional, slow-4, and slow-5). In the left superior occipital gyrus (SOG), Wavelet-ALFF was decreased in the conventional frequency band but increased in the slow-4 frequency band. Additionally, patients with ABGIS demonstrated reduced Wavelet-ALFF in the right superior temporal gyrus (STG) in the conventional and slow-4 frequency bands. In the slow-5 frequency band, increased Wavelet-ALFF was observed in the left calcarine cortex (CC), left middle frontal gyrus (MFG), left supramarginal gyrus (SMG), and left postcentral gyrus (PCG), while decreased Wavelet-ALFF was noted in the right precuneus (PCu). Correlation analysis revealed that increased Wavelet-ALFF in the left CC in the slow-5 frequency band was positively correlated with the FMA score. No other correlations were detected in the conventional and slow-4 frequency bands. Conclusions: The altered spontaneous neural activity was frequency-specific in patients with ABGIS, and the slow-5 frequency band exhibited better results. Furthermore, the relationship between spontaneous brain activity and clinical characteristics highlighted patterns of neural alterations associated with motor dysfunction. These findings may provide novel insights into the neural mechanisms underlying motor dysfunction in ABGIS.

Altered Static and Dynamic Functional Network Connectivity and Combined Machine Learning in Stroke

Stroke is a condition characterized by damage to the cerebral vasculature from various causes, resulting in focal or widespread brain tissue damage. Prior neuroimaging research has demonstrated that individuals with stroke present structural and functional brain abnormalities, evident through disruptions in motor, cognitive, and other vital functions. Nevertheless, there is a lack of studies on alterations in static and dynamic functional network connectivity in the brains of stroke patients. Fifty stroke patients and 50 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Initially, the independent component analysis (ICA) method was utilized to extract the resting-state network (RSN). Subsequently, the disparities in static functional network connectivity both within and between networks among the two groups were computed and juxtaposed. Following this, five consistent and robust dynamic functional network connectivity (dFNC) states were derived by integrating the sliding time window method with k-means cluster analysis, and the distinctions in dFNC between the groups across different states, along with the intergroup variations in three dynamic temporal metrics, were assessed. Finally, a support vector machine (SVM) approach was employed to discriminate stroke patients from HCs using FC and FNC as classification features. Comparing the stroke group to the healthy control (HC) group, the stroke group exhibited reduced intra-network functional connectivity (FC) in the right superior temporal gyrus of the ventral attention network (VAN), the left calcarine of the visual network (VN), and the left precuneus of the default mode network (DMN). Regarding static functional network connectivity (FNC), we identified increased connectivity between the executive control network (ECN) and dorsal attention network (DAN), salience network (SN) and DMN, SN-ECN, and VN-ECN, along with decreased connectivity between DAN-DAN, ECN-SN, SN-SN, and DAN-VN between the two groups. Noteworthy differences in dynamic FNC (dFNC) were observed between the groups in states 3 to 5. Moreover, stroke patients demonstrated a significantly higher proportion of time and longer mean dwell time in state 4, alongside a decreased proportion of time in state 5 compared to HC. Finally, utilizing FC and FNC as features, stroke patients could be distinguished from HC with an accuracy exceeding 70% and an area under the curve ranging from 0.8284 to 0.9364. In conclusion, our study reveals static and dynamic changes in large-scale brain networks in stroke patients, potentially linked to abnormalities in visual, cognitive, and motor functions. This investigation offers valuable insights into the neural mechanisms underpinning the functional deficits observed in stroke, thereby aiding in the diagnosis and development of targeted therapeutic interventions for affected individuals.

Network Abnormalities in Ischemic Stroke: A Meta-analysis of Resting-State Functional Connectivity

Aberrant large-scale resting-state functional connectivity (rsFC) has been frequently documented in ischemic stroke. However, it remains unclear about the altered patterns of within- and across-network connectivity. The purpose of this meta-analysis was to identify the altered rsFC in patients with ischemic stroke relative to healthy controls, as well as to reveal longitudinal changes of network dysfunctions across acute, subacute, and chronic phases. A total of 24 studies were identified as eligible for inclusion in the present meta-analysis. These studies included 269 foci observed in 58 contrasts (558 patients with ischemic stroke; 526 healthy controls; 38.84% female). The results showed: (1) within-network hypoconnectivity in the sensorimotor network (SMN), default mode network (DMN), frontoparietal network (FPN), and salience network (SN), respectively; (2) across-network hypoconnectivity between the SMN and both of the SN and visual network, and between the FPN and both of the SN and DMN; and (3) across-network hyperconnectivity between the SMN and both of the DMN and FPN, and between the SN and both of the DMN and FPN. Meta-regression showed that hypoconnectivity between the DMN and the FPN became less pronounced as the ischemic stroke phase progressed from the acute to the subacute and chronic phases. This study provides the first meta-analytic evidence of large-scale rsFC dysfunction in ischemic stroke. These dysfunctional biomarkers could help identify patients with ischemic stroke at risk for cognitive, sensory, motor, and emotional impairments and further provide potential insight into developing diagnostic models and therapeutic interventions for rehabilitation and recovery.

Resting-state functional abnormalities in ischemic stroke: a meta-analysis of fMRI studies

Ischemic stroke is a leading neurological cause of severe disabilities and death in the world and has a major negative impact on patients' quality of life. However, the neural mechanism of spontaneous fluctuating neuronal activity remains unclear. This meta-analysis explored brain activity during resting state in patients with ischemic stroke including 22 studies of regional homogeneity, amplitude of low-frequency fluctuation, and fractional amplitude of low-frequency fluctuation (692 patients with ischemic stroke, 620 healthy controls, age range 35-80 years, 41% female, 175 foci). Results showed decreased regional activity in the bilateral caudate and thalamus and increased regional activity in the left superior occipital gyrus and left default mode network (precuneus/posterior cingulate cortex). Meta-analysis of the amplitude of low-frequency fluctuation studies showed that increased activity in the left inferior frontal gyrus was reduced across the progression from acute to chronic phases. These findings may indicate that disruption of the subcortical areas and default mode network could be one of the core functional abnormalities in ischemic stroke. Altered brain activity in the inferior frontal gyrus could be the imaging indicator of brain recovery/plasticity after stroke damage, which offers potential insight into developing prediction models and therapeutic strategies for ischemic stroke rehabilitation and recovery.

Altered Intrinsic Brain Activity in Ischemic Stroke Patients Assessed Using the Percent Amplitude of a Fluctuation Method

Ischemic stroke is a vascular disease that may cause cognitive and behavioral abnormalities. This study aims to assess abnormal brain function in ischemic stroke patients using the percent amplitude of fluctuation (PerAF) method and further explore the feasibility of PerAF as an imaging biomarker for investigating ischemic stroke pathophysiology mechanisms. Sixteen ischemic stroke patients and 22 healthy controls (HCs) underwent resting state functional magnetic resonance imaging (rs-fMRI) scanning, and the resulting data were analyzed using PerAF. Then a correlation analysis was conducted between PerAF values and Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Finally, the abnormal PerAF values were extracted and defined as features for support vector machine (SVM) analysis. Compared with HCs, ischemic stroke patients showed decreased PerAF in the bilateral cuneus, left middle frontal gyrus, precuneus and right inferior temporal gyrus, and increased PerAF in the bilateral orbital part of middle frontal gyrus and right orbital part of superior frontal gyrus. Correlation analyses revealed that PerAF values in the left orbital part of middle frontal gyrus was negatively correlated with the MoCA scores. The SVM classification of the PerAF values achieved an area under the curve (AUC) of 0.98 and an accuracy of 94.74%. Abnormal brain function has been found among ischemic stroke patients, which may be correlated with visual impairment, attention deficits, and dysregulation of negative emotions following a stroke. Our findings may support the potential of PerAF as a sensitive biomarker for investigating the underlying mechanisms of ischemic stroke.

Efficacy of Cerebellar Transcranial Magnetic Stimulation for Post-stroke Balance and Limb Motor Function Impairments: Meta-analyses of Random Controlled Trials and Resting-State fMRI Studies

This study aimed to investigate the potential therapeutic effects of cerebellar transcranial magnetic stimulation (TMS) on balance and limb motor impairments in stroke patients. A meta-analysis of randomized controlled trials was conducted to assess the effects of cerebellar TMS on balance and motor impairments in stroke patients. Additionally, an activation likelihood estimation (ALE) meta-analysis was performed on resting-state functional magnetic resonance imaging (fMRI) studies to compare spontaneous neural activity differences between stroke patients and healthy controls using measures including the amplitude of low frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo). The analysis included 10 cerebellar TMS studies and 18 fMRI studies. Cerebellar TMS treatment demonstrated significant improvements in the Berg Balance Scale score (p < 0.0001) and the Fugl-Meyer Assessment lower extremity score (p < 0.0001) compared to the control group in stroke patients. Additionally, spontaneous neural activity alterations were identified in motor-related regions after stroke, including the precentral gyrus, putamen, thalamus, and paracentral lobule. Cerebellar TMS shows promise as a therapeutic intervention to enhance balance and lower limb motor function in stroke patients. It is easy for clinical application and addresses the limitations of insufficient direct stimulation depth on the leg area of the cortex. However, further research combining neuroimaging outcomes with clinical measurements is necessary to validate these findings.

Immediate and long-term brain activation of acupuncture on ischemic stroke patients: an ALE meta-analysis of fMRI studies

Background

Acupuncture, as an alternative and complementary therapy recommended by the World Health Organization for stroke treatment, holds potential in ameliorating neurofunctional deficits induced by ischemic stroke (IS). Understanding the immediate and long-term effects of acupuncture and their interrelation would contribute to a better comprehension of the mechanisms underlying acupuncture efficacy.

Methods

Activation likelihood estimation (ALE) meta-analysis was used to analyze the brain activation patterns reported in 21 relevant functional neuroimaging studies. Among these studies, 12 focused on the immediate brain activation and 9 on the long-term activation. Single dataset analysis were employed to identify both immediate and long-term brain activation of acupuncture treatment in IS patients, while contrast and conjunction analysis were utilized to explore distinctions and connections between the two.

Results

According to the ALE analysis, immediately after acupuncture treatment, IS patients exhibited an enhanced cluster centered around the right precuneus (PCUN) and a reduced cluster centered on the left middle frontal gyrus (MFG). After long-term acupuncture treatment, IS patients showed an enhanced cluster in the left PCUN, along with two reduced clusters in the right insula (INS) and hippocampus (HIP), respectively. Additionally, in comparison to long-term acupuncture treatment, the right angular gyrus (ANG) demonstrated higher ALE scores immediately after acupuncture, whereas long-term acupuncture resulted in higher scores in the left superior parietal gyrus (SPG). The intersecting cluster activated by both of them was located in the left cuneus (CUN).

Conclusion

The findings provide initial insights into both the immediate and long-term brain activation patterns of acupuncture treatment for IS, as well as the intricate interplay between them. Both immediate and long-term acupuncture treatments showed distinct patterns of brain activation, with the left CUN emerging as a crucial regulatory region in their association.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, CRD42023480834.