The artificial neural network has the ability of the information processing and storage, good adaptability, strong learning function, association function and fault tolerance function. The research on the artificial neural network is mostly focused on the dynamic properties due to fact that the applications of artificial neural networks are related to its dynamic properties. At present, the researches on the neural network are based on the hierarchical network which can not simulate the real neural network. As a high level of abstraction of real complex systems, the small world network has the properties of biological neural networks. In the study, the small world network was constructed and the optimal parameter of the small word network was chosen based on the complex network theory firstly. And then based on the regulation mechanism of the synaptic plasticity and the topology of the small world network, the small world neural network was constructed and dynamic properties of the neural network were analyzed from the three aspects of the firing properties, dynamic properties of synaptic weights and complex network properties. The experimental results showed that with the increase of the time, the firing patterns of excitatory and inhibitory neurons in the small world neural network didn’t change and the firing time of the neurons tended to synchronize; the synaptic weights between the neurons decreased sharply and eventually tended to be steady; the connections in the neural network were weakened and the efficiency of the information transmission was reduced, but the small world attribute was stable. The dynamic properties of the small world neural network vary with time, and the dynamic properties can also interact with each other: the firing synchronization of the neural network can affect the distribution of synaptic weights to the minimum, and then the dynamic changes of the synaptic weights can affect the complex network properties of the small world neural network.
Biological neural networks have dual properties of small-world attributes and scale-free attributes. Most of the current researches on neural networks are based on small-world networks or scale-free networks with lower clustering coefficient, however, the real brain network is a scale-free network with small-world attributes. In this paper, a scale-free spiking neural network with high clustering coefficient and small-world attribute was constructed. The dynamic evolution process was analyzed from three aspects: synaptic regulation process, firing characteristics and complex network characteristics. The experimental results show that, as time goes by, the synaptic strength gradually decreases and tends to be stable. As a result, the connection strength of the network decreases and tends to be stable; the firing rate of neurons gradually decreases and tends to be stable, and the synchronization becomes worse; the local information transmission efficiency is stable, the global information transmission efficiency is reduced and tends to be stable, and the small-world attributes are relatively stable. The dynamic characteristics vary with time and interact with each other. The regulation of synapses is based on the firing time of neurons, and the regulation of synapses will affect the firing of neurons and complex characteristics of networks. In this paper, a scale-free spiking neural network was constructed, which has biological authenticity. It lays a foundation for the research of artificial neural network and its engineering application.
Under the current situation of the rapid development of brain-like artificial intelligence and the increasingly complex electromagnetic environment, the most bionic and anti-interference spiking neural network has shown great potential in computing speed, real-time information processing, and spatiotemporal data processing. Spiking neural network is the core part of brain-like artificial intelligence, which realizes brain-like computing by simulating the structure of biological neural network and the way of information transmission. This article first summarizes the advantages and disadvantages of the five models, and analyzes the characteristics of several network topologies. Then, it summarizes the spiking neural network algorithms. The unsupervised learning based on spike timing dependent plasticity (STDP) rules and four types of supervised learning algorithms are analyzed. Finally, the research on brain-like neuromorphic chips at home and abroad are reviewed. This paper aims to provide learning ideas and research directions for new colleagues in the field of spiking neural network.
【Abstract】 Objective To investigate the effect of retinoic acid (RA) on cell apoptosis and gene regulation of IGF-2in chondrocyte. Methods One 1-month-old Chinese rabbit weighted 500 g was used in this experiment. The chondrocyte from rabbit knee were cultured by enzyme digestion. Twenty-five μL all-trans-retinoic acid (ATRA) (1×10-6 mol/L) were added in the media of cultured chondrocyte for 24 hours as experimental group, while 25 μL DMEM were added as control group. The secretion of collagen Ⅱ was observed by immunohistochemistry method, cell apoptosis was detected by flow cytometry, IGF-2 mRNA and protein expression in chondrocyte were detected by RT-PCR and Western blot analysis. Results The expression of collagen Ⅱ was down-regulated by ATRA in the experimental group. The cell apoptosis in chondrocyte exposed to ATRA at 1 ×10-6 mol/L was 21% ± 2%, which increased 5 times compared with the control group（5% ± 1%）. The IGF-2 mRNA and protein level in the experimental group were decreased 75% and 57%, respectively, compared to the control group. There weresignificant difference between the experimental group and control group in each index (P lt; 0.05). Conclusion RA may down-regulate the secretion and cell prol iferation, but up-regulate the cell apoptosis in chondrocyte. The apoptotic effect may carry out through inhibiting the IGF-2 expression of chondrocyte.
Transcranial direct current stimulation (tDCS) is a brain stimulation intervention technique, which has the problem of different criteria for the selection of stimulation parameters. In this study, a four-layer real head model was constructed. Based on this model, the changes of the electric field distribution in the brain with the current intensity, electrode shape, electrode area and electrode spacing were analyzed by using finite element simulation technology, and then the optimal scheme of electrical stimulation parameters was discussed. The results showed that the effective stimulation region decreased and the focusing ability increased with the increase of current intensity. The normal current density of the quadrilateral electrode was obviously larger than that of the circular electrode, which indicated that the quadrilateral electrode was more conducive to current stimulation of neurons. Moreover, the effective stimulation region of the quadrilateral electrode was more concentrated and the focusing ability was stronger. The focusing ability decreased with the increase of electrode area. Specifically, the focusing tended to increase first and then decrease with the increase of electrode spacing and the optimal electrode spacing was 64.0–67.2 mm. These results could provide some basis for the selection of electrical stimulation parameters.
As an emerging non-invasive brain stimulation technique, transcranial direct current stimulation (tDCS) has received increasing attention in the field of stroke disease rehabilitation. However, its efficacy needs to be further studied. The tDCS has three stimulation modes: bipolar-stimulation mode, anode-stimulation mode and cathode-stimulation mode. Nineteen stroke patients were included in this research (10 with left-hemisphere lesion and 9 with right). Resting electroencephalogram (EEG) signals were collected from subjects before and after bipolar-stimulation, anodal-stimulation, cathodal-stimulation, and pseudo-stimulation, with pseudo-stimulation serving as the control group. The changes of multi-scale intrinsic fuzzy entropy (MIFE) of EEG signals before and after stimulation were compared. The results revealed that MIFE was significantly greater in the frontal and central regions after bipolar-stimulation (P < 0.05), in the left central region after anodal-stimulation (P < 0.05), and in the frontal and right central regions after cathodal-stimulation (P < 0.05) in patients with left-hemisphere lesions. MIFE was significantly greater in the frontal, central and parieto-occipital joint regions after bipolar-stimulation (P < 0.05), in the left frontal and right central regions after anodal- stimulation (P < 0.05), and in the central and right occipital regions after cathodal-stimulation (P < 0.05) in patients with right-hemisphere lesions. However, the difference before and after pseudo-stimulation was not statistically significant (P > 0.05). The results of this paper showed that the bipolar stimulation pattern affected the largest range of brain areas, and it might provide a reference for the clinical study of rehabilitation after stroke.
Transcranial direct current stimulation (tDCS) is an emerging non-invasive brain stimulation technique. However, the rehabilitation effect of tDCS on stroke disease is unclear. In this paper, based on electroencephalogram (EEG) and complex network analysis methods, the effect of tDCS on brain function network of stroke patients during rehabilitation was investigated. The resting state EEG signals of 31 stroke rehabilitation patients were collected and divided into stimulation group (16 cases) and control group (15 cases). The Pearson correlation coefficients were calculated between the channels, brain functional network of two groups were constructed before and after stimulation, and five characteristic parameters were analyzed and compared such as node degree, clustering coefficient, characteristic path length, global efficiency, and small world attribute. The results showed that node degree, clustering coefficient, global efficiency, and small world attributes of brain functional network in the tDCS group were significantly increased, characteristic path length was significantly reduced, and the difference was statistically significant (P < 0.05). It indicates that tDCS can improve the brain function network of stroke patients in rehabilitation period, and may provide theory and experimental basis for the application of tDCS in stroke rehabilitation treatment.
Transcranial direct current stimulation (tDCS) has become a new method of post-stroke rehabilitation treatment and is gradually accepted by people. However, the neurophysiological mechanism of tDCS in the treatment of stroke still needs further study. In this study, we recruited 30 stroke patients with damage to the left side of the brain and randomly divided them into a real tDCS group (15 cases) and a sham tDCS group (15 cases). The resting EEG signals of the two groups of subjects before and after stimulation were collected, then the difference of power spectral density was analyzed and compared in the band of delta, theta, alpha and beta, and the delta/alpha power ratio (DAR) was calculated. The results showed that after real tDCS, delta band energy decreased significantly in the left temporal lobes, and the difference was statistically significant (P < 0.05); alpha band energy enhanced significantly in the occipital lobes, and the difference was statistically significant (P < 0.05); the difference of theta and beta band energy was not statistically significant in the whole brain region (P > 0.05). Furthermore, the difference of delta, theta, alpha and beta band energy was not statistically significant after sham tDCS (P > 0.05). On the other hand, the DAR value of stroke patients decreased significantly after real tDCS, and the difference was statistically significant (P < 0.05), and there was no significant difference in sham tDCS (P > 0.05). This study reveals to a certain extent the neurophysiological mechanism of tDCS in the treatment of stroke.
Posterior-stabilized total knee prostheses have been widely used in orthopedic clinical treatment of knee osteoarthritis, but the patients and surgeons are still troubled by the complications, for example severe wear and fracture of the post, as well as prosthetic loosening. Understanding the in vivo biomechanics of knee prostheses will aid in the decrease of postoperative prosthetic revision and patient dissatisfaction. Therefore, six different designs of posterior-stabilized total knee prostheses were used to establish the musculoskeletal multibody dynamics models of total knee arthroplasty respectively, and the biomechanical differences of six posterior-stabilized total knee prostheses were investigated under three simulated physiological activities: walking, right turn and squatting. The results showed that the post contact forces of PFC Sigma and Scorpio NGR prostheses were larger during walking, turning right, and squatting, which may increase the risk of the fracture and wear as well as the early loosening. The post design of Gemini SL prosthesis was more conductive to the knee internal-external rotation and avoided the edge contact and wear. The lower conformity design in sagittal plane and the later post-cam engagement resulted in the larger anterior-posterior translation. This study provides a theoretical support for guiding surgeon selection, improving posterior-stabilized prosthetic design and reducing the prosthetic failure.
The use of a filling block can improve the initial stability of the fixation plate in the open wedge high tibial osteotomy (OWHTO), and promote bone healing. However, the biomechanical effects of filling block structures and materials on OWHTO remain unclear. OWHTO anatomical filling block model was designed and built. The finite element analysis method was adopted to study the influence of six filling block structure designs and four different materials on the stress of the fixed plate, tibia, screw, and filling block, and the micro-displacement at the wedge gap of the OWHTO fixation system. After the filling block was introduced in the OWHTO, the maximum von Mises stress of the fixation plate was reduced by more than 30%, the maximum von Mises stress of the tibia decreased by more than 15%, and the lateral hinge decreased by 81%. When the filling block was designed to be filled in the posterior position of the wedge gap, the maximum von Mises stress of the fixation system was 97.8 MPa, which was smaller than other filling methods. The minimum micro-displacement of osteotomy space was –2.9 μm, which was larger than that of other filling methods. Compared with titanium alloy and tantalum metal materials, porous hydroxyapatite material could obtain larger micro-displacement in the osteotomy cavity, which is conducive to stimulating bone healing. The results demonstrate that OWHTO with a filling block can better balance the stress distribution of the fixation system, and a better fixation effect can be obtained by using a filling block filled in the posterior position. Porous HA used as the material of the filling block can obtain a better bone healing effect.