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Quantum-like behavior without quantum physics II. A quantum-like model of neural network dynamics

机译:没有量子物理II的量子样行为II。 一种Quantum样模型的神经网络动态

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In earlier work, we laid out the foundation for explaining the quantum-like behavior of neural systems in the basic kinematic case of clusters of neuron-like units. Here we extend this approach to networks and begin developing a dynamical theory for them. Our approach provides a novel mathematical foundation for neural dynamics and computation which abstracts away from lower-level biophysical details in favor of information-processing features of neural activity. The theory makes predictions concerning such pathologies as schizophrenia, dementias, and epilepsy, for which some evidence has accrued. It also suggests a model of memory retrieval mechanisms. As further proof of principle, we analyze certain energy-like eigenstates of the 13 three-neuron motif classes according to our theory and argue that their quantum-like superpositional nature has a bearing on their observed structural integrity.
机译:在早期的工作中,我们奠定了解释神经系统中神经系统的量子样行为在神经元的基本运动情况下的基础。 在这里,我们将这种方法扩展到网络并开始为它们开发动态理论。 我们的方法为神经动力学和计算提供了一种新的数学基础,以及摘要远离较低级别的生物物理细节,有利于神经活动的信息处理特征。 该理论使得预测有关精神分裂症,痴呆和癫痫的这种病症,有些证据已经累积。 它还表明了内存检索机制的模型。 作为原则的进一步证明,我们根据我们的理论分析了13个三神经元主题课程的某些能量状特征,并争辩说它们的量子超词性质对其观察到的结构完整性具有轴承。

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