In order to classify the minimal hepatic encephalopathy （MHE） patients from healthy controls, the independent component analysis （ICA） is used to generate the default mode network （DMN） from resting-state functi...In order to classify the minimal hepatic encephalopathy （MHE） patients from healthy controls, the independent component analysis （ICA） is used to generate the default mode network （DMN） from resting-state functional magnetic resonance imaging （fMRI）. Then a Bayesian voxel- wised method, graphical-model-based multivariate analysis （GAMMA）, is used to explore the associations between abnormal functional integration within DMN and clinical variable. Without any prior knowledge, five machine learning methods, namely, support vector machines （SVMs）, classification and regression trees （ CART ）, logistic regression, the Bayesian network, and C4.5, are applied to the classification. The functional integration patterns were alternative within DMN, which have the power to predict MHE with an accuracy of 98%. The GAMMA method generating functional integration patterns within DMN can become a simple, objective, and common imaging biomarker for detecting MIIE and can serve as a supplement to the existing diagnostic methods.展开更多
1 Introduction Hypertension and cerebrovascular disease incidence and prevalence rise dramatically with age, owing to longer exposure time to age-associated alterations in vascular function and structure and cardiova...1 Introduction Hypertension and cerebrovascular disease incidence and prevalence rise dramatically with age, owing to longer exposure time to age-associated alterations in vascular function and structure and cardiovascular risk factors. This chapter is aimed at connecting age-related alterations in vascular function and structure to the resultant target organ damage, and to raise awareness of unique presentations and treatment strategies for hypertension and stroke in older adults.展开更多
In this paper, we review the current state- of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate co...In this paper, we review the current state- of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering： neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity （via a neuroimaging modality） through a neural interface （invasive or noninvasive） and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering--to develop neurotechniques for enhancing the understanding of whole- brain function and dysfunction, and the management of neurological and mental disorders.展开更多
Objective: Neurological evaluation is commonly applied to identify ischemia in focal cerebral ischemia model though it might not be sensitive. In present study, we hired sleeping time to assess ischemia occurrence. Me...Objective: Neurological evaluation is commonly applied to identify ischemia in focal cerebral ischemia model though it might not be sensitive. In present study, we hired sleeping time to assess ischemia occurrence. Methods: Permanent middle cerebral artery occlusion was induced in Sprague-Dawley rats under pentobarbital and ketamine anesthesia respectively. Sleeping time was recorded. Neurological evaluation was conducted by modified Bederson’s scoring system at 4 h and histopathological evaluation was performed at 3 d after middle cerebral artery occlusion. Results: Slices of brain stained by TTC, H&E and hoechst 33258 revealed extensive lesion in the two ischemic groups. The sensitivity to identify ischemia by neurological evaluation was 62.5%, but it was 81.3% and 80% respectively when evaluating by sleeping time (pentobarbital: ≥90.7 min, ketamine: ≥36.1 min). The sensitivity to identify ischemia by sleeping time was significantly higher than that by neurological evaluation (P<0.05). Conclusion: Our results suggested that to identify ischemia by sleeping time is a simple and sensitive method in the setting of focal cerebral ischemia in rat.展开更多
AIM: The role of motor dysfunction in early diagnosis of low-grade hepatic encephalopathy remains uncertain. We performed a pilot study to comparatively investigate the kinematic characteristics of small and large rap...AIM: The role of motor dysfunction in early diagnosis of low-grade hepatic encephalopathy remains uncertain. We performed a pilot study to comparatively investigate the kinematic characteristics of small and large rapid alternating movements in patients with liver cirrhosis and low-grade hepatic encephalopathy.METHODS: A kinematic analysis of alternating handwriting (7.5 mm) and large drawing movements (DM, 175 mm) was performed in 30 patients with liver cirrhosis (no hepatic encephalopathy: n = 10; minimal hepatic encephalopathy: n = 9; grade I hepatic encephalopathy: n = 11; healthy controls: n = 12). The correlation between kinematic parameters, clinical neuro-psychiatric symptoms of cerebral dysfunction and the grade of encephalopathy was investigated.RESULTS: Both movement types, handwriting and drawing, were significantly slower in cirrhotic patients. In contrast to large DM, the deterioration of handwriting movements significantly correlated with the increase of symptoms of motor dysfunction and differentiated significantly within the group of cirrhosis patients corresponding to the degree of hepatic encephalopathy. CONCLUSION: The deterioration of fine motor control is an important symptom of low-grade hepatic encephalopathy. The kinematic analysis of handwriting allows the quantitative analysis of alterations of motor function and is a possible tool for diagnostics and monitoring of motor dysfunction in patients with low-grade hepatic encephalopathy.展开更多
基金The National Natural Science Foundation of China(No.8123003481271739+2 种基金81501453)the Special Program of Medical Science of Jiangsu Province(No.BL2013029)the Natural Science Foundation of Jiangsu Province(No.BK20141342)
文摘In order to classify the minimal hepatic encephalopathy （MHE） patients from healthy controls, the independent component analysis （ICA） is used to generate the default mode network （DMN） from resting-state functional magnetic resonance imaging （fMRI）. Then a Bayesian voxel- wised method, graphical-model-based multivariate analysis （GAMMA）, is used to explore the associations between abnormal functional integration within DMN and clinical variable. Without any prior knowledge, five machine learning methods, namely, support vector machines （SVMs）, classification and regression trees （ CART ）, logistic regression, the Bayesian network, and C4.5, are applied to the classification. The functional integration patterns were alternative within DMN, which have the power to predict MHE with an accuracy of 98%. The GAMMA method generating functional integration patterns within DMN can become a simple, objective, and common imaging biomarker for detecting MIIE and can serve as a supplement to the existing diagnostic methods.
文摘1 Introduction Hypertension and cerebrovascular disease incidence and prevalence rise dramatically with age, owing to longer exposure time to age-associated alterations in vascular function and structure and cardiovascular risk factors. This chapter is aimed at connecting age-related alterations in vascular function and structure to the resultant target organ damage, and to raise awareness of unique presentations and treatment strategies for hypertension and stroke in older adults.
基金supported in part by the US National Institutes of Health (NIH) (EB006433, EY023101, EB008389,and HL117664)the US National Science Foundation (NSF) (CBET1450956, CBET-1264782, and DGE-1069104),to Bin He
文摘In this paper, we review the current state- of-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governs our everyday lives involves an intricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by specific anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering： neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity （via a neuroimaging modality） through a neural interface （invasive or noninvasive） and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering--to develop neurotechniques for enhancing the understanding of whole- brain function and dysfunction, and the management of neurological and mental disorders.
文摘Objective: Neurological evaluation is commonly applied to identify ischemia in focal cerebral ischemia model though it might not be sensitive. In present study, we hired sleeping time to assess ischemia occurrence. Methods: Permanent middle cerebral artery occlusion was induced in Sprague-Dawley rats under pentobarbital and ketamine anesthesia respectively. Sleeping time was recorded. Neurological evaluation was conducted by modified Bederson’s scoring system at 4 h and histopathological evaluation was performed at 3 d after middle cerebral artery occlusion. Results: Slices of brain stained by TTC, H&E and hoechst 33258 revealed extensive lesion in the two ischemic groups. The sensitivity to identify ischemia by neurological evaluation was 62.5%, but it was 81.3% and 80% respectively when evaluating by sleeping time (pentobarbital: ≥90.7 min, ketamine: ≥36.1 min). The sensitivity to identify ischemia by sleeping time was significantly higher than that by neurological evaluation (P<0.05). Conclusion: Our results suggested that to identify ischemia by sleeping time is a simple and sensitive method in the setting of focal cerebral ischemia in rat.
文摘AIM: The role of motor dysfunction in early diagnosis of low-grade hepatic encephalopathy remains uncertain. We performed a pilot study to comparatively investigate the kinematic characteristics of small and large rapid alternating movements in patients with liver cirrhosis and low-grade hepatic encephalopathy.METHODS: A kinematic analysis of alternating handwriting (7.5 mm) and large drawing movements (DM, 175 mm) was performed in 30 patients with liver cirrhosis (no hepatic encephalopathy: n = 10; minimal hepatic encephalopathy: n = 9; grade I hepatic encephalopathy: n = 11; healthy controls: n = 12). The correlation between kinematic parameters, clinical neuro-psychiatric symptoms of cerebral dysfunction and the grade of encephalopathy was investigated.RESULTS: Both movement types, handwriting and drawing, were significantly slower in cirrhotic patients. In contrast to large DM, the deterioration of handwriting movements significantly correlated with the increase of symptoms of motor dysfunction and differentiated significantly within the group of cirrhosis patients corresponding to the degree of hepatic encephalopathy. CONCLUSION: The deterioration of fine motor control is an important symptom of low-grade hepatic encephalopathy. The kinematic analysis of handwriting allows the quantitative analysis of alterations of motor function and is a possible tool for diagnostics and monitoring of motor dysfunction in patients with low-grade hepatic encephalopathy.
