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
This paper proposes a method in order to detect the importance of the input variables in multivariate analysis problems. When there is correlation among predictor variables, the importance of each input variable, when...This paper proposes a method in order to detect the importance of the input variables in multivariate analysis problems. When there is correlation among predictor variables, the importance of each input variable, when adding variables in the model, can be detected from the knowledge stored in Artificial Neural Network （NN） and it must be taken into account. Neural networks models have been used with the analysis of sensibility, these models predict more accurately the relationship between variables, and it is the way to find a set of forecasting variables in order to be included in the new prediction model. The obtained results have been applied in a system to forecast the volume of wood for a tree, and to detect relationships between input and output variables.展开更多
Objective： To observe the distribution of the nerve fibers in the bone tissue and the entry points of these fibers into the bone. Methods： The adult tibia was used for the ground sections which were afterwards made...Objective： To observe the distribution of the nerve fibers in the bone tissue and the entry points of these fibers into the bone. Methods： The adult tibia was used for the ground sections which were afterwards made into the slice sections by decalcification in ethylenediamine tetraacetic acid （EDTA）. The ground sections were stained in silver and the slice sections were stained in silver and haematoxylin and eosin （HE） respectively. Then, the samples of the transmission electron microscope and the atomic force microscope were made and observed. Results ： In the human long bone tissue, many nerve fibers were distributed in the membrane, cortical bone, cancellous bone and marrow. The nerve fibers entered the bone from the nutrient foramen, and passed through the nutrient canal, Haversian＇ s canal and Volkmann＇ s canal, and finally into the bone marrow. In the nutrient canal, the nerve fibers, mainly the medullary nerve fibers, followed the blood vessel into the bone. In the cortical bone, the nerve fibers also followed the blood vessels and were mainly distributed along Haversian＇ s canal and Volkmann＇ s canal. In the bone trabecular and bone marrow, there were many nerve fiber endings arranged around the blood vessels, mainly around the tunica media of medium-size arteries in the marrow and around capillary blood vessels, and a few scattered in the bone marrow. There were sporadic nerve endings in epiphyseal plate and no nerve fibers permeated epiphysis to diaphysis. No distribution of nerve fibers could be found in cartilaginous part. Conclusions： There are many nerve fibers in bone and the nerve passageway is nutrient foramen, Volkman＇ s canal, Haversian＇ s canal and bone marrow.展开更多
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This paper proposes a method in order to detect the importance of the input variables in multivariate analysis problems. When there is correlation among predictor variables, the importance of each input variable, when adding variables in the model, can be detected from the knowledge stored in Artificial Neural Network （NN） and it must be taken into account. Neural networks models have been used with the analysis of sensibility, these models predict more accurately the relationship between variables, and it is the way to find a set of forecasting variables in order to be included in the new prediction model. The obtained results have been applied in a system to forecast the volume of wood for a tree, and to detect relationships between input and output variables.
文摘Objective： To observe the distribution of the nerve fibers in the bone tissue and the entry points of these fibers into the bone. Methods： The adult tibia was used for the ground sections which were afterwards made into the slice sections by decalcification in ethylenediamine tetraacetic acid （EDTA）. The ground sections were stained in silver and the slice sections were stained in silver and haematoxylin and eosin （HE） respectively. Then, the samples of the transmission electron microscope and the atomic force microscope were made and observed. Results ： In the human long bone tissue, many nerve fibers were distributed in the membrane, cortical bone, cancellous bone and marrow. The nerve fibers entered the bone from the nutrient foramen, and passed through the nutrient canal, Haversian＇ s canal and Volkmann＇ s canal, and finally into the bone marrow. In the nutrient canal, the nerve fibers, mainly the medullary nerve fibers, followed the blood vessel into the bone. In the cortical bone, the nerve fibers also followed the blood vessels and were mainly distributed along Haversian＇ s canal and Volkmann＇ s canal. In the bone trabecular and bone marrow, there were many nerve fiber endings arranged around the blood vessels, mainly around the tunica media of medium-size arteries in the marrow and around capillary blood vessels, and a few scattered in the bone marrow. There were sporadic nerve endings in epiphyseal plate and no nerve fibers permeated epiphysis to diaphysis. No distribution of nerve fibers could be found in cartilaginous part. Conclusions： There are many nerve fibers in bone and the nerve passageway is nutrient foramen, Volkman＇ s canal, Haversian＇ s canal and bone marrow.
