4.4 Article

Spatial movement with distributed memory

Journal

JOURNAL OF MATHEMATICAL BIOLOGY
Volume 82, Issue 4, Pages -

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s00285-021-01588-0

Keywords

Spatial memory; Reaction– diffusion equation; Distributed delayed diffusion; Pattern formation; Spatially non-homogeneous time periodic solution; Hopf bifurcation; Turing bifurcation

Funding

  1. China Scholarship Council
  2. NSFC [12001240]
  3. Natural Science Foundation of Jiangsu Province [BK20200589]
  4. US-NSF [DMS-1715651]
  5. NSERC Discovery Grant [RGPIN-2020-03911]
  6. NSERC Accelerator Grant [RGPAS-2020-00090]

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The paragraph discusses the modeling of animal movement using diffusion and the importance of spatial memory and cognition in characterizing animal behavior. It is found that modeling spatial memory can lead to rich spatiotemporal dynamics.
Diffusion has been widely applied to model animal movement that follows Brownian motion. However, animals typically move in non-Brownian ways due to their perceptual judgment. Spatial memory and cognition recently have received much attention in characterizing complicated animal movement behaviours. Explicit spatial memory is modeled via a distributed delayed diffusion term in this paper. The distributed time represents the memory growth and decay over time, and the spatial nonlocality reflects the dependence of spatial memory on location. When the temporal delay kernel is weak under the assumption that animals can immediately acquire knowledge and memory decays over time, the equation is equivalent to a Keller-Segel chemotaxis model. For the strong kernel with learning and memory decay stages, rich spatiotemporal dynamics, such as Turing and checker-board patterns, appear via spatially non-homogeneous steady-state and Hopf bifurcations.

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