Clinical correlates of social cognition after an ischemic stroke: preliminary findings

Behavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression

BACKGROUND

Emotion processing deficits are known to accompany depressive symptoms and are often seen in stroke patients. Little is known about the influence of post-stroke depressive (PSD) symptoms and specific brain lesions on altered emotion processing abilities and how these phenomena develop over time. This potential relationship may impact post-stroke rehabilitation of neurological and psychosocial function. To address this scientific gap, we investigated the relationship between PSD symptoms and emotion processing abilities in a longitudinal study design from the first days post-stroke into the early chronic phase.

METHODS

Twenty-six ischemic stroke patients performed an emotion processing task on videos with emotional faces ('happy,' 'sad,' 'anger,' 'fear,' and 'neutral') at different intensity levels (20%, 40%, 60%, 80%, 100%). Recognition accuracies and response times were measured, as well as scores of depressive symptoms (Montgomery-Åsberg Depression Rating Scale). Twenty-eight healthy participants matched in age and sex were included as a control group. Whole-brain support-vector regression lesion-symptom mapping (SVR-LSM) analyses were performed to investigate whether specific lesion locations were associated with the recognition accuracy of specific emotion categories.

RESULTS

Stroke patients performed worse in overall recognition accuracy compared to controls, specifically in the recognition of happy, sad, and fearful faces. Notably, more depressed stroke patients showed an increased processing towards specific negative emotions, as they responded significantly faster to angry faces and recognized sad faces of low intensities significantly more accurately. These effects obtained for the first days after stroke partly persisted to follow-up assessment several months later. SVR-LSM analyses revealed that inferior and middle frontal regions (IFG/MFG) and insula and putamen were associated with emotion-recognition deficits in stroke. Specifically, recognizing happy facial expressions was influenced by lesions affecting the anterior insula, putamen, IFG, MFG, orbitofrontal cortex, and rolandic operculum. Lesions in the posterior insula, rolandic operculum, and MFG were also related to reduced recognition accuracy of fearful facial expressions, whereas recognition deficits of sad faces were associated with frontal pole, IFG, and MFG damage.

CONCLUSION

PSD symptoms facilitate processing negative emotional stimuli, specifically angry and sad facial expressions. The recognition accuracy of different emotional categories was linked to brain lesions in emotion-related processing circuits, including insula, basal ganglia, IFG, and MFG. In summary, our study provides support for psychosocial and neural factors underlying emotional processing after stroke, contributing to the pathophysiology of PSD.

Predicting ischemic stroke risk from atrial fibrillation based on multi-spectral fundus images using deep learning

Background

Ischemic stroke (IS) is one of the most common serious secondary diseases of atrial fibrillation (AF) within 1 year after its occurrence, both of which have manifestations of ischemia and hypoxia of the small vessels in the early phase of the condition. The fundus is a collection of capillaries, while the retina responds differently to light of different wavelengths. Predicting the risk of IS occurring secondary to AF, based on subtle differences in fundus images of different wavelengths, is yet to be explored. This study was conducted to predict the risk of IS occurring secondary to AF based on multi-spectrum fundus images using deep learning.

Methods

A total of 150 AF participants without suffering from IS within 1 year after discharge and 100 IS participants with persistent arrhythmia symptoms or a history of AF diagnosis in the last year (defined as patients who would develop IS within 1 year after AF, based on fundus pathological manifestations generally prior to symptoms of the brain) were recruited. Fundus images at 548, 605, and 810 nm wavelengths were collected. Three classical deep neural network (DNN) models (Inception V3, ResNet50, SE50) were trained. Sociodemographic and selected routine clinical data were obtained.

Results

The accuracy of all DNNs with the single-spectral or multi-spectral combination images at the three wavelengths as input reached above 78%. The IS detection performance of DNNs with 605 nm spectral images as input was relatively more stable than with the other wavelengths. The multi-spectral combination models acquired a higher area under the curve (AUC) scores than the single-spectral models.

Conclusions

The probability of IS secondary to AF could be predicted based on multi-spectrum fundus images using deep learning, and combinations of multi-spectrum images improved the performance of DNNs. Acquiring different spectral fundus images is advantageous for the early prevention of cardiovascular and cerebrovascular diseases. The method in this study is a beneficial preliminary and initiative exploration for diseases that are difficult to predict the onset time such as IS.

A comparative study of the neuroprotective effects of dl-3-n-butylphthalide and edaravone dexborneol on cerebral ischemic stroke rats

INTRODUCTION

DL-3-n-butylphthalide (NBP) and edaravone dexborneol (Eda-Dex) are two promising reagents for stroke treatment. However, the impacts of NBP and Eda-Dex on poststroke mental deficits are still poorly understood. In this study, we aimed to investigate and compare the influences of NBP and Eda-Dex on neurological function and cognitive behavior in rats with ischemic stroke.

METHODS

An ischemic stroke model was established by middle cerebral artery occlusion (MCAO). After peritoneal administration of the drugs, the rats were subjected to neurological deficit evaluation, cerebral blood flow (CBF) assays, cerebral infarct area evaluations or behavioral tests. Brain tissues were collected and further analyzed by enzyme-linked immunosorbent assay (ELISA), western blotting or immunohistochemistry.

RESULTS

NBP and Eda-Dex significantly decreased the neurological score, reduced the cerebral infarct area and improved CBF. Behavioral changes as assessed in the sucrose preference test, novel object recognition test, and social interaction test were significantly alleviated by NBP and Eda-Dex in rats with ischemic stroke. Moreover, NBP and Eda-Dex significantly suppressed inflammation by targeting the nuclear factor kappa-B/inducible nitric oxide synthase (NF-κB/iNOS) pathway and significantly inhibited oxidative stress by targeting the kelch-1ike ECH-associated protein l/nuclear factor erythroid 2-related factor 2 (Keap1/Nrf2) pathway. In addition, NBP and Eda-Dex distinctly suppressed the activation of microglia and astrocytes and improved neuronal viability in the ischemic brain.

CONCLUSIONS

NBP and Eda-Dex improved neurological function and alleviated cognitive disorders in rats with ischemic stroke by synergistically inhibiting inflammation and oxidative stress.