Electronic systems are vulnerable in electromagnetic interference environment. Although many solutions are adopted to solve this problem, for example shielding, filtering and grounding, noise is still introduced into ...Electronic systems are vulnerable in electromagnetic interference environment. Although many solutions are adopted to solve this problem, for example shielding, filtering and grounding, noise is still introduced into the circuit inevitably. What impresses us is the biological nervous system with a vital property of robustness in noisy environment. Some mechanisms, such as neuron population coding, degeneracy and parallel distributed processing, are believed to partly explain how the nervous system counters the noise and component failure. This paper proposes a novel concept of bio-inspired electromagnetic protec- tion making reference to the characteristic of neural information processing. A bionic model is presented here to mimic neuron populations to transform the input signal into neural pulse signal. In the proposed model, neuron provides a dynamic feedback to the adjacent one according to the concept of synaptic plasticity. A simple neural circuitry is designed to verify the rationality of the bio-inspired model for electromagnetic protection. The experiment results display that bio-inspired electromagnetic pro- tection model has more power to counter the interference and component failure.展开更多
Mathematical frameworks of quantum theory have recently been adopted in cognitive and behavioral sciences, to explain the violations of normative decision theory and anomalies in cognition. However, to date, no study ...Mathematical frameworks of quantum theory have recently been adopted in cognitive and behavioral sciences, to explain the violations of normative decision theory and anomalies in cognition. However, to date, no study has attempted to explore neural implementations of such “quantum-like” information processing in the brain. This study demonstrates that neural population coding of information with nonlinear neural response functions can account for such “quantum” information processing in decision-making and cognition. It is also shown that quantum decision theory is a special case of more general population vector cording theory. Future applications of the present theory in the rapidly evolving field of “psychophysical neuroeconomics” are also discussed.展开更多
Background: This work aims at investigating the histology of hippocampus formation as structural model of information processing. The study addressed the question whether the pattern of cellular type distribution with...Background: This work aims at investigating the histology of hippocampus formation as structural model of information processing. The study addressed the question whether the pattern of cellular type distribution within hippocampal fields could be used as support of information processing in the hippocampus. Method: Pyramidal-shaped neurons presenting both cytoplasm and nucleus outlined clearly were measured systematically on brain slides, using a light microscope connected to a microcomputer equipped with a scanner software for measuring particles. Morphological types of cells were identified following class sizes and their distribution determined through hippocampal fields. Results: A battery of statistical tests: Sturges’ classification, class sizes distribution around overall mean, Bartlett’s sphericity test, principal components analysis (PCA) followed by correlations matrix analysis and ANOVA allowed two cellular groups to be identified in the hippocampus: large and small pyramidal-shaped cells. Conclusion: The results show that sensory information processing in the hippocampus could be built on two classes of pyramidal neurons that differed anatomically with probably different physiological functions. The study suggests combination ensembles clustering large and small pyramidal cells at different rates, as fundamental signaling units of the hippocampus.展开更多
基金This research was supported by the National Natural Science Foundation of China
文摘Electronic systems are vulnerable in electromagnetic interference environment. Although many solutions are adopted to solve this problem, for example shielding, filtering and grounding, noise is still introduced into the circuit inevitably. What impresses us is the biological nervous system with a vital property of robustness in noisy environment. Some mechanisms, such as neuron population coding, degeneracy and parallel distributed processing, are believed to partly explain how the nervous system counters the noise and component failure. This paper proposes a novel concept of bio-inspired electromagnetic protec- tion making reference to the characteristic of neural information processing. A bionic model is presented here to mimic neuron populations to transform the input signal into neural pulse signal. In the proposed model, neuron provides a dynamic feedback to the adjacent one according to the concept of synaptic plasticity. A simple neural circuitry is designed to verify the rationality of the bio-inspired model for electromagnetic protection. The experiment results display that bio-inspired electromagnetic pro- tection model has more power to counter the interference and component failure.
文摘Mathematical frameworks of quantum theory have recently been adopted in cognitive and behavioral sciences, to explain the violations of normative decision theory and anomalies in cognition. However, to date, no study has attempted to explore neural implementations of such “quantum-like” information processing in the brain. This study demonstrates that neural population coding of information with nonlinear neural response functions can account for such “quantum” information processing in decision-making and cognition. It is also shown that quantum decision theory is a special case of more general population vector cording theory. Future applications of the present theory in the rapidly evolving field of “psychophysical neuroeconomics” are also discussed.
文摘Background: This work aims at investigating the histology of hippocampus formation as structural model of information processing. The study addressed the question whether the pattern of cellular type distribution within hippocampal fields could be used as support of information processing in the hippocampus. Method: Pyramidal-shaped neurons presenting both cytoplasm and nucleus outlined clearly were measured systematically on brain slides, using a light microscope connected to a microcomputer equipped with a scanner software for measuring particles. Morphological types of cells were identified following class sizes and their distribution determined through hippocampal fields. Results: A battery of statistical tests: Sturges’ classification, class sizes distribution around overall mean, Bartlett’s sphericity test, principal components analysis (PCA) followed by correlations matrix analysis and ANOVA allowed two cellular groups to be identified in the hippocampus: large and small pyramidal-shaped cells. Conclusion: The results show that sensory information processing in the hippocampus could be built on two classes of pyramidal neurons that differed anatomically with probably different physiological functions. The study suggests combination ensembles clustering large and small pyramidal cells at different rates, as fundamental signaling units of the hippocampus.
