Up and down oscillations of membrane potentials are viewed as one kind of significant spontaneous... more Up and down oscillations of membrane potentials are viewed as one kind of significant spontaneous periodic activities. This kind of oscillation always shows that membrane potentials make spontaneous transitions between two preferred states called up and down states, which characterized by some features as follows in level of membrane potentials: bistability, directivity, spontaneity, synchronicity and spontaneous spikings. Here, we focus on the spontaneous spiking and its energy feature. We studied the influence of the intrinsic characteristics and synaptic transmission of spontaneous spiking during up and down activities. The simulated results showed that persistent sodium current was critical to spontaneous fluctuation without any stimulus, while the fast sodium current had the dominant position in generation of spontaneous neural firing. Considering the noise, we found the role of persistent sodium current was partially replaced by oscillation of noise. And energy consumption of neurons in spontaneous activities also shows bistable feature and bimodal distribution as same as the membrane potential, which indicated that the energy consumption can encode up and down states in this kind of activities.
This paper focuses on the neurodynamical research of a small neural network that consists of 25 n... more This paper focuses on the neurodynamical research of a small neural network that consists of 25 neurons. We study the periodic spontaneous activity and transitions between up and down states without synaptic input. The results demonstrate that these transitions are bidirectional or unidirectional with the parameters changing, which not only reveals the function of the cortex, but also cohere with the experiment results.
Spatial cognitive function is crucial for the animal's survival. However, the formation of place ... more Spatial cognitive function is crucial for the animal's survival. However, the formation of place codes in different dimensional spaces cannot be uniformly explained. In this paper, a constrained optimization model based on information theory is constructed to explain the formation of place cell activity in different dimensional spaces across species. The question is proposed as, using limited amount of neural energy, how to design the place field to obtain the most efficient spatial information representation? Variational techniques are applied and the results suggest that the place field will comply with a certain centralized distribution (normally is Gaussian form) automatically to convey the largest amount spatial information per spike, under the constraint of limited neural energy. The animal's natural habitat property and locomotion experience statistics also affected the spatial codes. These findings not only answer whether the spatial codes of place cell are isotropic in different dimensional spaces, but also provide an insight about the maximum information principle of the place cell activity.
The visual system is under heated investigation in the field of neuroscience and computer vision ... more The visual system is under heated investigation in the field of neuroscience and computer vision (CV). In alignment with the implementation of some large brain projects across the world such as those in China, Europe, the USA and Japan, the intersection of visual system in these two fields has been promoted. Therefore, as the most important source of human perception towards the objective world, research on mechanisms of the visual information processing bears great significance for exploring biological vision and developing CV. However, there is a scarcity of soundly established and widely accepted theory that can be used to explain the mechanisms. Specifically, what remains unknown is the degradation mechanism of visual information data during the topological mapping between retina and V1. Hence, in view of the characteristics of convolutional neural network (CNN), this paper draws on the concept of convolution algorithm to propose an edge detection model based on retina to V1 (EDMRV1), which is built on the pathway of photoreceptors-ganglion cells-LGN-V1 in the functional channel of image features detection. The results not only match the neurobiological experimental data but also show that the image edge features of visual information are detected by the convolution algorithm according to the function of synaptic plasticity, when visual signals are hierarchically processed from low-level to high-level in visual cortex. Findings are expected to lay a solid foundation for revealing the mechanisms of the visual information processing in future research. In CV, applying the model to the scenes with different brightness has a better performance on the edge features detection than that in the traditional algorithms, providing an intelligent basis for breakthroughs. This research also opens up opportunities for the integration of CV and neuroscience.
The information processing mechanisms of the visual nervous system remain to be unsolved scientif... more The information processing mechanisms of the visual nervous system remain to be unsolved scientific issues in neuroscience field, owing to a lack of unified and widely accepted theory for explanation. It has been well documented that approximately 80% of the rich and complicated perceptual information from the real world is transmitted to the visual cortex, and only a small fraction of visual information reaches the primary visual cortex (V1). This, nevertheless, does not affect our visual perception. Furthermore, how neurons in the secondary visual cortex (V2) encode such a small amount of visual information has yet to be addressed. To this end, the current paper established a visual network model for retina-lateral geniculate nucleus (LGN)-V1-V2 and quantitatively accounted for that response to the scarcity of visual information and encoding rules, based on the principle of neural mapping from V1 to V2. The results demonstrated that the visual information has a small degree of dynamic degradation when it is mapped from V1 to V2, during which there is a convolution calculation occurring. Therefore, visual information dynamic degradation mainly manifests itself along the pathway of the retina to V1, rather than V1 to V2. The slight changes in the visual information are attributable to the fact that the receptive fields (RFs) of V2 cannot further extract the image features. Meanwhile, despite the scarcity of visual information mapped from the retina, the RFs of V2 can still accurately respond to and encode ''corner'' information, due to the effects of synaptic plasticity, but the similar function does not exist in V1. This is a new discovery that has never been noticed before. To sum up, the coding of the ''contour'' feature (edge and corner) is achieved in the pathway of retina-LGN-V1-V2.
Computer Methods and Programs in Biomedicine, Jun 1, 2017
Background and objective: In human-machine (HM) hybrid control systems, human operator and machin... more Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the presence of both discrete task-load (control) variable and continuous operator performance variable. Methods: Petri net is an effective tool for modeling discrete event systems, whereas for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components in a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the modelbased OFS prediction. Furthermore, for the purpose of validation of the framework suggested, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) variables via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for individual experimental participant were optimized by using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Results: Experiment data from six participants are processed and simulated, the results show that the proposed method(FIPN with adaptive task allocation) yields better performance with lower breakdown rate(from 14.8% to 3.27%) and higher human performance(from 90.30% to 91.99%). Conclusions: The simulation results of FIPN-based adaptive HM (AHM) system on six experimental participants demonstrated that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of
About 50-80% of total energy is consumed by signaling in neural networks. A neural network consum... more About 50-80% of total energy is consumed by signaling in neural networks. A neural network consumes much energy if there are many active neurons in the network. If there are few active neurons in a neural network, the network consumes very little energy. The ratio of active neurons to all neurons of a neural network, that is, the sparseness, affects the energy consumption of a neural network. Laughlin's studies show that the sparseness of an energy-efficient code depends on the balance between signaling and fixed costs. Laughlin did not give an exact ratio of signaling to fixed costs, nor did they give the ratio of active neurons to all neurons in most energy-efficient neural networks. In this paper, we calculated the ratio of signaling costs to fixed costs by the data from physiology experiments. The ratio of signaling costs to fixed costs is between 1.3 and 2.1. We calculated the ratio of active neurons to all neurons in most energy-efficient neural networks. The ratio of active neurons to all neurons in neural networks is between 0.3 and 0.4. Our results are consistent with the data from many relevant physiological experiments, indicating that the model used in this paper may meet neural coding under real conditions. The calculation results of this paper may be helpful to the study of neural coding.
The human operator's ability to perform their tasks can fluctuate over time. Because the cognitiv... more The human operator's ability to perform their tasks can fluctuate over time. Because the cognitive demands of the task can also vary it is possible that the capabilities of the operator are not sufficient to satisfy the job demands. This can lead to serious errors when the operator is overwhelmed by the task demands. Psychophysiological measures, such as heart rate and brain activity, can be used to monitor operator cognitive workload. In this paper, the most influential psychophysiological measures are extracted to characterize Operator Functional State (OFS) in automated tasks under a complex form of human-automation interaction. The fuzzy c-mean (FCM) algorithm is used and tested for its OFS classification performance. The results obtained have shown the feasibility and effectiveness of the FCM algorithm as well as the utility of the selected input features for OFS classification. Besides being able to cope with nonlinearity and fuzzy uncertainty in the psychophysiological data it can provide information about the relative importance of the input features as well as the confidence estimate of the classification results. The OFS pattern classification method developed can be incorporated into an adaptive aiding system in order to enhance the overall performance of a large class of safetycritical human-machine cooperative systems.
Neural activity alters with the changes in cerebral blood flow (CBF) and blood oxygen saturation.... more Neural activity alters with the changes in cerebral blood flow (CBF) and blood oxygen saturation. Despite that these changes can be detected with functional magnetic resonance imaging (fMRI), the underlying physiological mechanism remains obscure. Upon activation of the specific brain region, CBF increases substantially, albeit with 6-8 s delay. Neuroscience has no scientific explanation for this experimental discovery yet. This study proposed a physiological mechanism for generating hemodynamic phenomena from the perspective of energy metabolism. The ratio of reduction (NADH) and oxidation states (NAD ?) of nicotinamide adenine dinucleotide in cell was considered as the variable for CBF regulation. After the specific brain region was activated, brain glycogen was rapidly consumed as reserve energy, resulting in no significant change in the ratio of NADH and NAD ? concentrations. However, when the stored energy in the cell is exhausted, the dynamic equilibrium state of the transition between NADH and NAD ? is changed, and the ratio of NADH and NAD ? concentrations is significantly increased, which regulates the blood flow to be greatly increased. Based on this physiological mechanism, this paper builds a large-scale visual nervous system network based on the Wang-Zhang neuron model, and quantitatively reproduced the hemodynamics observed in fMRI by computer numerical simulation. The results demonstrated that the negative energy mechanism, which was previously reported by our group using Wang-Zhang neuronal model, played a vital role in governing brain hemodynamics. Also, it precisely predicted the neural coupling mechanism between the energy metabolism and blood flow changes in the brain under stimulation. In nature, this mechanism is determined by imbalance and mismatch between the positive and negative energy during the spike of neuronal action potentials. A quantitative analysis was adopted to elucidate the physiological mechanism underlying this phenomenon, which would provide an insight into the principle of brain operation and the neural model of the overall brain function. Keywords fMRI Á Negative energy Á Energetics coding Á Hemodynamics Á Neural network Á Brain glycogen
The papers invited by DBF are published as the second section of this volume. We also would like ... more The papers invited by DBF are published as the second section of this volume. We also would like to express our gratitude to Profs. Francois-Benoit Vialatte, Justin Dauwels, and Jianting Cao for organizing a mini-symposium on Neural dynamics of brain disorders; Profs.
The spatial motion of rodent hippocampi is considered as a cognitive map to represent a spatial e... more The spatial motion of rodent hippocampi is considered as a cognitive map to represent a spatial environment.In this cognitive map,different spatial regions are assigned to different cell populations in a framework of rate coding,they are also widely used in the associative memory.Here,the formation and function of the two kinds of cognitive maps were presented through building the neural computational model and cognitive map.The first one was the spatial vector map,it could perform self localization.At the same time,it could update the new detail information of the map.The other one was the goal-oriented vector map,it played an important role in path finding.As an intermediate between the two types,their combination formed an effective and efficient way of path finding.Here,applying this kind of cognitive map-based path-finding method to a mental exploration model was focused on.Relying on the driving force of adaptation,the basic knowledge of the relationship between the locations ...
Hand is one of the fundamental characteristics of fabric. Over the last century,significant resul... more Hand is one of the fundamental characteristics of fabric. Over the last century,significant results on the characterization and evaluation of fabric hand have been achieved following the development in science and technology. Due to the lack of knowledge of the human cognitive performances,however,neurocognitive theory of fabric hand is under exploration. As results,the understanding of fabric hand and its physiological mechanism remains rather superficial. From the physiological point of view,this paper reviews the progress of researches on fabric hand and its evaluation techniques. Attempts have been made to clear up some misunderstanding on the evaluation of fabric hand,the fact that the previous suggestion of tactile texture space of fabric,namely primary hand,is contradictory to the conclusions of cognitive psychology and cognitive neurology. It is suggested that the future study on fabric hand and its evaluation technique can only make material progress once the current resear...
In rock mass hydraulics research,an important issue is the coupled analysis of the rock mass seep... more In rock mass hydraulics research,an important issue is the coupled analysis of the rock mass seepage field and temperature field.By paying attention to the domestic and international relevant research,the trend of the studies under consideration is prospected.The current state of the research of temperature and seepage in fractured rock mass is systematically introduced and studied.The features and application scopes for three kinds of models in fractured rock mass are discussed,and the main research achievements on non-continuum media of fractured network are elaborated.The research of coupled seepage and temperature analysis in fractured rock mass is pointed out,and their application in engineering is introduced.Further more,in this paper,the representative testing methods and techniques in recent years in the studies of coupled seepage field and temperature field analysis on non-continuum media of fractured network are proposed,and the problems requesting further research are als...
No‐clean fluxes and solder pastes are rapidly finding an important position in soldering producti... more No‐clean fluxes and solder pastes are rapidly finding an important position in soldering production technology. Their growth has been strongly influenced by the increasingly large usage of surface mount components, and accelerated by the need for an alternative to cleaning procedures which incorporate CFCs. The ‘no‐clean’ concept is not new, but the very low residue levels now attainable have added an important new dimension in formulation and inspection technologies.
The 27th Chinese Control and Decision Conference (2015 CCDC), 2015
For an interval type-2 fuzzy logic system (IT2FLS), its structure and parameters are learned simu... more For an interval type-2 fuzzy logic system (IT2FLS), its structure and parameters are learned simultaneously by using evolutionary strategy in this paper. Then gradient descent (GD) and recursive least-squares with forgetting factor (FFRLS) algorithms are employed to optimize the parameters of the IT2FLS. Furthermore, a more efficient type-reduction method, called enhanced iterative algorithm with stop condition (EIASC), is utilized. Finally, an evolutionary interval type-2 TSK fuzzy logic system (EIT2FLS) is developed. The results of applying EIT2FLS to nonlinear systems identification problems demonstrated the superiority of the developed EIT2FLS to existing methods.
The paper simulates membrane potential of Lamprey neural circuit based on WLC model. The influenc... more The paper simulates membrane potential of Lamprey neural circuit based on WLC model. The influences parameter of RS and SR neuron stimulation are numerically analyzed. The results show that left or right motoneuron will appear alternately spike in circumstance of ...
... charac-teristics of the activity of the neuron, the method that simulating the neuron as a X.... more ... charac-teristics of the activity of the neuron, the method that simulating the neuron as a X. Zhang (B) Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai 200237, China e-mail: jimy. zhang@ 163. com 227 R. Wang, F. Gu (eds ...
Up and down oscillations of membrane potentials are viewed as one kind of significant spontaneous... more Up and down oscillations of membrane potentials are viewed as one kind of significant spontaneous periodic activities. This kind of oscillation always shows that membrane potentials make spontaneous transitions between two preferred states called up and down states, which characterized by some features as follows in level of membrane potentials: bistability, directivity, spontaneity, synchronicity and spontaneous spikings. Here, we focus on the spontaneous spiking and its energy feature. We studied the influence of the intrinsic characteristics and synaptic transmission of spontaneous spiking during up and down activities. The simulated results showed that persistent sodium current was critical to spontaneous fluctuation without any stimulus, while the fast sodium current had the dominant position in generation of spontaneous neural firing. Considering the noise, we found the role of persistent sodium current was partially replaced by oscillation of noise. And energy consumption of neurons in spontaneous activities also shows bistable feature and bimodal distribution as same as the membrane potential, which indicated that the energy consumption can encode up and down states in this kind of activities.
This paper focuses on the neurodynamical research of a small neural network that consists of 25 n... more This paper focuses on the neurodynamical research of a small neural network that consists of 25 neurons. We study the periodic spontaneous activity and transitions between up and down states without synaptic input. The results demonstrate that these transitions are bidirectional or unidirectional with the parameters changing, which not only reveals the function of the cortex, but also cohere with the experiment results.
Spatial cognitive function is crucial for the animal's survival. However, the formation of place ... more Spatial cognitive function is crucial for the animal's survival. However, the formation of place codes in different dimensional spaces cannot be uniformly explained. In this paper, a constrained optimization model based on information theory is constructed to explain the formation of place cell activity in different dimensional spaces across species. The question is proposed as, using limited amount of neural energy, how to design the place field to obtain the most efficient spatial information representation? Variational techniques are applied and the results suggest that the place field will comply with a certain centralized distribution (normally is Gaussian form) automatically to convey the largest amount spatial information per spike, under the constraint of limited neural energy. The animal's natural habitat property and locomotion experience statistics also affected the spatial codes. These findings not only answer whether the spatial codes of place cell are isotropic in different dimensional spaces, but also provide an insight about the maximum information principle of the place cell activity.
The visual system is under heated investigation in the field of neuroscience and computer vision ... more The visual system is under heated investigation in the field of neuroscience and computer vision (CV). In alignment with the implementation of some large brain projects across the world such as those in China, Europe, the USA and Japan, the intersection of visual system in these two fields has been promoted. Therefore, as the most important source of human perception towards the objective world, research on mechanisms of the visual information processing bears great significance for exploring biological vision and developing CV. However, there is a scarcity of soundly established and widely accepted theory that can be used to explain the mechanisms. Specifically, what remains unknown is the degradation mechanism of visual information data during the topological mapping between retina and V1. Hence, in view of the characteristics of convolutional neural network (CNN), this paper draws on the concept of convolution algorithm to propose an edge detection model based on retina to V1 (EDMRV1), which is built on the pathway of photoreceptors-ganglion cells-LGN-V1 in the functional channel of image features detection. The results not only match the neurobiological experimental data but also show that the image edge features of visual information are detected by the convolution algorithm according to the function of synaptic plasticity, when visual signals are hierarchically processed from low-level to high-level in visual cortex. Findings are expected to lay a solid foundation for revealing the mechanisms of the visual information processing in future research. In CV, applying the model to the scenes with different brightness has a better performance on the edge features detection than that in the traditional algorithms, providing an intelligent basis for breakthroughs. This research also opens up opportunities for the integration of CV and neuroscience.
The information processing mechanisms of the visual nervous system remain to be unsolved scientif... more The information processing mechanisms of the visual nervous system remain to be unsolved scientific issues in neuroscience field, owing to a lack of unified and widely accepted theory for explanation. It has been well documented that approximately 80% of the rich and complicated perceptual information from the real world is transmitted to the visual cortex, and only a small fraction of visual information reaches the primary visual cortex (V1). This, nevertheless, does not affect our visual perception. Furthermore, how neurons in the secondary visual cortex (V2) encode such a small amount of visual information has yet to be addressed. To this end, the current paper established a visual network model for retina-lateral geniculate nucleus (LGN)-V1-V2 and quantitatively accounted for that response to the scarcity of visual information and encoding rules, based on the principle of neural mapping from V1 to V2. The results demonstrated that the visual information has a small degree of dynamic degradation when it is mapped from V1 to V2, during which there is a convolution calculation occurring. Therefore, visual information dynamic degradation mainly manifests itself along the pathway of the retina to V1, rather than V1 to V2. The slight changes in the visual information are attributable to the fact that the receptive fields (RFs) of V2 cannot further extract the image features. Meanwhile, despite the scarcity of visual information mapped from the retina, the RFs of V2 can still accurately respond to and encode ''corner'' information, due to the effects of synaptic plasticity, but the similar function does not exist in V1. This is a new discovery that has never been noticed before. To sum up, the coding of the ''contour'' feature (edge and corner) is achieved in the pathway of retina-LGN-V1-V2.
Computer Methods and Programs in Biomedicine, Jun 1, 2017
Background and objective: In human-machine (HM) hybrid control systems, human operator and machin... more Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the presence of both discrete task-load (control) variable and continuous operator performance variable. Methods: Petri net is an effective tool for modeling discrete event systems, whereas for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components in a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the modelbased OFS prediction. Furthermore, for the purpose of validation of the framework suggested, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) variables via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for individual experimental participant were optimized by using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Results: Experiment data from six participants are processed and simulated, the results show that the proposed method(FIPN with adaptive task allocation) yields better performance with lower breakdown rate(from 14.8% to 3.27%) and higher human performance(from 90.30% to 91.99%). Conclusions: The simulation results of FIPN-based adaptive HM (AHM) system on six experimental participants demonstrated that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of
About 50-80% of total energy is consumed by signaling in neural networks. A neural network consum... more About 50-80% of total energy is consumed by signaling in neural networks. A neural network consumes much energy if there are many active neurons in the network. If there are few active neurons in a neural network, the network consumes very little energy. The ratio of active neurons to all neurons of a neural network, that is, the sparseness, affects the energy consumption of a neural network. Laughlin's studies show that the sparseness of an energy-efficient code depends on the balance between signaling and fixed costs. Laughlin did not give an exact ratio of signaling to fixed costs, nor did they give the ratio of active neurons to all neurons in most energy-efficient neural networks. In this paper, we calculated the ratio of signaling costs to fixed costs by the data from physiology experiments. The ratio of signaling costs to fixed costs is between 1.3 and 2.1. We calculated the ratio of active neurons to all neurons in most energy-efficient neural networks. The ratio of active neurons to all neurons in neural networks is between 0.3 and 0.4. Our results are consistent with the data from many relevant physiological experiments, indicating that the model used in this paper may meet neural coding under real conditions. The calculation results of this paper may be helpful to the study of neural coding.
The human operator's ability to perform their tasks can fluctuate over time. Because the cognitiv... more The human operator's ability to perform their tasks can fluctuate over time. Because the cognitive demands of the task can also vary it is possible that the capabilities of the operator are not sufficient to satisfy the job demands. This can lead to serious errors when the operator is overwhelmed by the task demands. Psychophysiological measures, such as heart rate and brain activity, can be used to monitor operator cognitive workload. In this paper, the most influential psychophysiological measures are extracted to characterize Operator Functional State (OFS) in automated tasks under a complex form of human-automation interaction. The fuzzy c-mean (FCM) algorithm is used and tested for its OFS classification performance. The results obtained have shown the feasibility and effectiveness of the FCM algorithm as well as the utility of the selected input features for OFS classification. Besides being able to cope with nonlinearity and fuzzy uncertainty in the psychophysiological data it can provide information about the relative importance of the input features as well as the confidence estimate of the classification results. The OFS pattern classification method developed can be incorporated into an adaptive aiding system in order to enhance the overall performance of a large class of safetycritical human-machine cooperative systems.
Neural activity alters with the changes in cerebral blood flow (CBF) and blood oxygen saturation.... more Neural activity alters with the changes in cerebral blood flow (CBF) and blood oxygen saturation. Despite that these changes can be detected with functional magnetic resonance imaging (fMRI), the underlying physiological mechanism remains obscure. Upon activation of the specific brain region, CBF increases substantially, albeit with 6-8 s delay. Neuroscience has no scientific explanation for this experimental discovery yet. This study proposed a physiological mechanism for generating hemodynamic phenomena from the perspective of energy metabolism. The ratio of reduction (NADH) and oxidation states (NAD ?) of nicotinamide adenine dinucleotide in cell was considered as the variable for CBF regulation. After the specific brain region was activated, brain glycogen was rapidly consumed as reserve energy, resulting in no significant change in the ratio of NADH and NAD ? concentrations. However, when the stored energy in the cell is exhausted, the dynamic equilibrium state of the transition between NADH and NAD ? is changed, and the ratio of NADH and NAD ? concentrations is significantly increased, which regulates the blood flow to be greatly increased. Based on this physiological mechanism, this paper builds a large-scale visual nervous system network based on the Wang-Zhang neuron model, and quantitatively reproduced the hemodynamics observed in fMRI by computer numerical simulation. The results demonstrated that the negative energy mechanism, which was previously reported by our group using Wang-Zhang neuronal model, played a vital role in governing brain hemodynamics. Also, it precisely predicted the neural coupling mechanism between the energy metabolism and blood flow changes in the brain under stimulation. In nature, this mechanism is determined by imbalance and mismatch between the positive and negative energy during the spike of neuronal action potentials. A quantitative analysis was adopted to elucidate the physiological mechanism underlying this phenomenon, which would provide an insight into the principle of brain operation and the neural model of the overall brain function. Keywords fMRI Á Negative energy Á Energetics coding Á Hemodynamics Á Neural network Á Brain glycogen
The papers invited by DBF are published as the second section of this volume. We also would like ... more The papers invited by DBF are published as the second section of this volume. We also would like to express our gratitude to Profs. Francois-Benoit Vialatte, Justin Dauwels, and Jianting Cao for organizing a mini-symposium on Neural dynamics of brain disorders; Profs.
The spatial motion of rodent hippocampi is considered as a cognitive map to represent a spatial e... more The spatial motion of rodent hippocampi is considered as a cognitive map to represent a spatial environment.In this cognitive map,different spatial regions are assigned to different cell populations in a framework of rate coding,they are also widely used in the associative memory.Here,the formation and function of the two kinds of cognitive maps were presented through building the neural computational model and cognitive map.The first one was the spatial vector map,it could perform self localization.At the same time,it could update the new detail information of the map.The other one was the goal-oriented vector map,it played an important role in path finding.As an intermediate between the two types,their combination formed an effective and efficient way of path finding.Here,applying this kind of cognitive map-based path-finding method to a mental exploration model was focused on.Relying on the driving force of adaptation,the basic knowledge of the relationship between the locations ...
Hand is one of the fundamental characteristics of fabric. Over the last century,significant resul... more Hand is one of the fundamental characteristics of fabric. Over the last century,significant results on the characterization and evaluation of fabric hand have been achieved following the development in science and technology. Due to the lack of knowledge of the human cognitive performances,however,neurocognitive theory of fabric hand is under exploration. As results,the understanding of fabric hand and its physiological mechanism remains rather superficial. From the physiological point of view,this paper reviews the progress of researches on fabric hand and its evaluation techniques. Attempts have been made to clear up some misunderstanding on the evaluation of fabric hand,the fact that the previous suggestion of tactile texture space of fabric,namely primary hand,is contradictory to the conclusions of cognitive psychology and cognitive neurology. It is suggested that the future study on fabric hand and its evaluation technique can only make material progress once the current resear...
In rock mass hydraulics research,an important issue is the coupled analysis of the rock mass seep... more In rock mass hydraulics research,an important issue is the coupled analysis of the rock mass seepage field and temperature field.By paying attention to the domestic and international relevant research,the trend of the studies under consideration is prospected.The current state of the research of temperature and seepage in fractured rock mass is systematically introduced and studied.The features and application scopes for three kinds of models in fractured rock mass are discussed,and the main research achievements on non-continuum media of fractured network are elaborated.The research of coupled seepage and temperature analysis in fractured rock mass is pointed out,and their application in engineering is introduced.Further more,in this paper,the representative testing methods and techniques in recent years in the studies of coupled seepage field and temperature field analysis on non-continuum media of fractured network are proposed,and the problems requesting further research are als...
No‐clean fluxes and solder pastes are rapidly finding an important position in soldering producti... more No‐clean fluxes and solder pastes are rapidly finding an important position in soldering production technology. Their growth has been strongly influenced by the increasingly large usage of surface mount components, and accelerated by the need for an alternative to cleaning procedures which incorporate CFCs. The ‘no‐clean’ concept is not new, but the very low residue levels now attainable have added an important new dimension in formulation and inspection technologies.
The 27th Chinese Control and Decision Conference (2015 CCDC), 2015
For an interval type-2 fuzzy logic system (IT2FLS), its structure and parameters are learned simu... more For an interval type-2 fuzzy logic system (IT2FLS), its structure and parameters are learned simultaneously by using evolutionary strategy in this paper. Then gradient descent (GD) and recursive least-squares with forgetting factor (FFRLS) algorithms are employed to optimize the parameters of the IT2FLS. Furthermore, a more efficient type-reduction method, called enhanced iterative algorithm with stop condition (EIASC), is utilized. Finally, an evolutionary interval type-2 TSK fuzzy logic system (EIT2FLS) is developed. The results of applying EIT2FLS to nonlinear systems identification problems demonstrated the superiority of the developed EIT2FLS to existing methods.
The paper simulates membrane potential of Lamprey neural circuit based on WLC model. The influenc... more The paper simulates membrane potential of Lamprey neural circuit based on WLC model. The influences parameter of RS and SR neuron stimulation are numerically analyzed. The results show that left or right motoneuron will appear alternately spike in circumstance of ...
... charac-teristics of the activity of the neuron, the method that simulating the neuron as a X.... more ... charac-teristics of the activity of the neuron, the method that simulating the neuron as a X. Zhang (B) Institute for Cognitive Neurodynamics, East China University of Science and Technology, Shanghai 200237, China e-mail: jimy. zhang@ 163. com 227 R. Wang, F. Gu (eds ...
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