Integration of cognitive tasks into artificial general intelligence test for large models.

During the evolution of large models, performance evaluation is necessary for assessing their capabilities. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united framework for assessing the multidimensional intelligence of large models. In this perspective, we advocate for a comprehensive framework of cognitive science-inspired artificial general intelligence (AGI) tests, including crystallized, fluid, social, and embodied intelligence. The AGI tests consist of well-designed cognitive tests adopted from human intelligence tests, and then naturally encapsulates into an immersive virtual community. We propose increasing the complexity of AGI testing tasks commensurate with advancements in large models and emphasizing the necessity for the interpretation of test results to avoid false negatives and false positives. We believe that cognitive science-inspired AGI tests will effectively guide the targeted improvement of large models in specific dimensions of intelligence and accelerate the integration of large models into human society.

Explainable fMRI-based brain decoding via spatial temporal-pyramid graph convolutional network.

Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and neural engineering. However, existing machine learning methods for fMRI-based brain decoding either suffer from low classification performance or poor explainability. Here, we address this issue by proposing a biologically inspired architecture, Spatial Temporal-pyramid Graph Convolutional Network (STpGCN), to capture the spatial-temporal graph representation of functional brain activities. By designing multi-scale spatial-temporal pathways and bottom-up pathways that mimic the information process and temporal integration in the brain, STpGCN is capable of explicitly utilizing the multi-scale temporal dependency of brain activities via graph, thereby achieving high brain decoding performance. Additionally, we propose a sensitivity analysis method called BrainNetX to better explain the decoding results by automatically annotating task-related brain regions from the brain-network standpoint. We conduct extensive experiments on fMRI data under 23 cognitive tasks from Human Connectome Project (HCP) S1200. The results show that STpGCN significantly improves brain-decoding performance compared to competing baseline models; BrainNetX successfully annotates task-relevant brain regions. Post hoc analysis based on these regions further validates that the hierarchical structure in STpGCN significantly contributes to the explainability, robustness and generalization of the model. Our methods not only provide insights into information representation in the brain under multiple cognitive tasks but also indicate a bright future for fMRI-based brain decoding.

Kuramoto Model-Based Analysis Reveals Oxytocin Effects on Brain Network Dynamics.

The oxytocin effects on large-scale brain networks such as Default Mode Network (DMN) and Frontoparietal Network (FPN) have been largely studied using fMRI data. However, these studies are mainly based on the statistical correlation or Bayesian causality inference, lacking interpretability at the physical and neuroscience level. Here, we propose a physics-based framework of the Kuramoto model to investigate oxytocin effects on the phase dynamic neural coupling in DMN and FPN. Testing on fMRI data of 59 participants administrated with either oxytocin or placebo, we demonstrate that oxytocin changes the topology of brain communities in DMN and FPN, leading to higher synchronization in the FPN and lower synchronization in the DMN, as well as a higher variance of the coupling strength within the DMN and more flexible coupling patterns at group level. These results together indicate that oxytocin may increase the ability to overcome the corresponding internal oscillation dispersion and support the flexibility in neural synchrony in various social contexts, providing new evidence for explaining the oxytocin modulated social behaviors. Our proposed Kuramoto model-based framework can be a potential tool in network neuroscience and offers physical and neural insights into phase dynamics of the brain.

Role of prophylactic filter placement in the endovascular treatment of symptomatic thrombosis in the central veins.

OBJECTIVES: To evaluate the role of filter implantation in reducing the incidence of fatal pulmonary embolism during the endovascular treatment of thrombosis in the major tributary of the superior vena cava (SVC). METHODS: From October 2004 to October 2008, we conducted a cohort study of 40 patients with thrombosis of the central veins who were preparing for endovascular interventions and received or did not receive filter. The symptom scores were measured, the incidence of pulmonary embolism (PE) was observed, and patient follow-up studies were conducted for three years. RESULTS: One week after therapy, the symptom score improved in both groups compared with before therapy (P <0.001), but no significant difference was found between the scores of the two groups (P >0.05). Four patients in the control group died from PEs after therapy, but no patients in the filter group presented evidence of PE. The survival rates at 1, 2, and 3 years (72.9%, 50%, and 27.1%, respectively) for the filter group were higher than those for the control group (47.6%, 19.0% and 14.3%, respectively; P =0.015). The survival time of patients in the filter group with bronchogenic carcinoma (18 ± 2 months) was longer than that of the patients in the control group (12 ± 2 months) after the endovascular treatment (P <0.001). CONCLUSIONS: Prophylactic filter placement could be a safe and effective method for preventing PE in pre- or post-endovascular-treated patients with thrombi in their central veins.

Gypenoside attenuates white matter lesions induced by chronic cerebral hypoperfusion in rats.

Cerebral white matter lesions (WMLs) are frequently observed in vascular dementia and Alzheimer's disease and are believed to be responsible for cognitive dysfunction. The cerebral WMLs are most likely caused by chronic cerebral hypoperfusion and can be experimentally induced by permanent bilateral common carotid artery occlusion (BCCAO) in rats. Previous studies found the involvement of oxidative stress and astrocytic activation in the cerebral WMLs of BCCAO rats. Gypenoside (GP), a pure component extracted from the Gyrostemma pentaphyllum Makino, a widely reputed medicinal plants in China, has been reported to have some neuroprotective effects via anti-oxidative stress and anti-inflammatory mechanisms. In the present study, we investigated the protective effect of GP against cerebral WMLs and the underlying mechanisms for its inhibition of cognitive decline in BCCAO rats. Adult male Sprague-Dawley rats were orally administered daily doses of 200 and 400mg/kg GP for 33 days after BCCAO, and spatial learning and memory were assessed using the Morris water maze. Following behavioral testing, oxygen free radical levels and antioxidative capability were measured biochemically. The levels of lipid peroxidation and oxidative DNA damage were also assessed by immunohistochemical staining for 4-hydroxynonenal and 8-hydroxy-2'-deoxyguanosine, respectively. Activated astrocytes were also assessed by immunohistochemical staining and Western blotting with GFAP antibodies. The morphological changes were stained with Klüver-Barrera. Rats receiving 400mg/kg GP per day performed significantly better in tests for spatial learning and memory than saline-treated rats. GP 400mg/kg per day were found to markedly scavenge oxygen free radicals, enhance antioxidant abilities, decrease lipid peroxide production and oxidative DNA damage, and inhibit the astrocytic activation in corpus callosum and optic tract in BCCAO rats. However, GP 200mg/kg per day had no significant effects. GP may have therapeutic potential for treating dementia induced by chronic cerebral hypoperfusion and further evaluation is warranted.

Intraarterial thrombolysis and stent placement for acute basilar artery occlusion.

PURPOSE: To study retrospectively the prognostic factors for acute basilar artery occlusion treated with intraarterial thrombolysis and stent placement. MATERIALS AND METHODS: Within 3-48 hours of disease onset, 52 patients with basilar artery occlusion were treated with emergency intraarterial thrombolysis with recombinant tissue plasminogen activator (rtPA) or urokinase (UK) or intraarterial thrombolysis combined with stent placement. Sixteen patients simultaneously received stent placement for the partial recanalization of basilar artery occlusion after intraarterial thrombolysis. The National Institutes of Health Stroke Scale (NIHSS) scores and the modified Rankin Scale (mRS) scores of the patients were estimated. RESULTS: A favorable clinical outcome occurred in 22 patients (42.3%), and 20 patients (38.5%) died. The survival rate was 61.5% (32 patients). Successful recanalization of basilar artery occlusion was achieved in 24 patients (46.2%), and partial recanalization was achieved in 16 patients (30.7%). The rate of recanalization was 76.9%. NIHSS scores less than 14, treatment time window less than 24 hours, and a good recanalization were markedly correlated with good clinical prognosis. NIHSS scores less than 14 and treatment time window less than 24 hours were significantly correlated with recanalization. NIHSS scores less than 14 and good recanalization could act as independent predictors for clinical prognosis. CONCLUSIONS: NIHSS scores less than 14 on admission and successful recanalization can predict favorable outcome for patients with basilar artery occlusion. This study shows that intraarterial thrombolysis and stent placement may be a useful treatment for acute basilar artery occlusion.