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Limited capacity of working memory in unihemispheric random walks implies conceivable slow dispersal

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Abstract

Phenomenologically inspired by dolphins’ unihemispheric sleep, we introduce a minimal model for random walks with physiological memory. The physiological memory consists of long-term memory which includes unconscious implicit memory and conscious explicit memory, and working memory which serves as a multi-component system for integrating, manipulating and managing short-term storage. The model assumes that the sleeping state allows retrievals of episodic objects merely from the episodic buffer where these memory objects are invoked corresponding to the ambient objects and are thus object-oriented, together with intermittent but increasing use of implicit memory in which decisions are unconsciously picked up from historical time series. The process of memory decay and forgetting is constructed in the episodic buffer. The walker’s risk attitude, as a product of physiological heuristics according to the performance of objected-oriented decisions, is imposed on implicit memory. The analytical results of unihemispheric random walks with the mixture of object-oriented and time-oriented memory, as well as the long-time behavior which tends to the use of implicit memory, are provided, indicating the common sense that a conservative risk attitude is inclinable to slow movement.

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Acknowledgements

We would like to thank the anonymous reviewers for improving this manuscript. We also thank Dr. Tingzhu Huang of UESTC for providing supporting conditions for lasting the research. The work of KW was supported by the Fundamental Research Funds for the Central Universities (Grant No. ZYGX2013J104) and the Natural Science Foundation of China (Grant No. 11601066). The work of SZ was supported by the Natural Science Foundation of China (Grant No. 11501386).

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Correspondence to Kun Wei or Suchuan Zhong.

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Wei, K., Zhong, S. Limited capacity of working memory in unihemispheric random walks implies conceivable slow dispersal. Biol Cybern 111, 279–286 (2017). https://doi.org/10.1007/s00422-017-0723-0

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  • DOI: https://doi.org/10.1007/s00422-017-0723-0

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