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Complex Systems: Chaos and Beyond is co-authored by scientist Kunihiko Kaneko and mathematician Ichiro Tsuda. It is a book about " the study of complex systems, based on, but beyond, chaos " (p. v). The authors develop notions about types and features of chaos and applications to biological systems are highlighted. Because " complex systems are such that we(More)
We investigate the dynamic character of a network of electrotonically coupled cells consisting of class I point neurons, in terms of a finite dimensional dynamical system. We classify a subclass of class I point neurons, called class I* point neurons. Based on this classification, we use a reduced Hindmarsh-Rose (H-R) model, which consists of two dynamical(More)
To adapt to changeable or unfamiliar environments, it is important that animals develop strategies for goal-directed behaviors that meet the new challenges. We used a sequential paired-association task with asymmetric reward schedule to investigate how prefrontal neurons integrate multiple already-acquired associations to predict reward. Two types of(More)
The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum(More)
The transitory activity of neuron assemblies has been observed in various areas of animal and human brains. We here highlight some typical transitory dynamics observed in laboratory experiments and provide a dynamical systems interpretation of such behaviors. Using the information theory of chaos, it is shown that a certain type of chaos is capable of(More)