Neural Network Model for Apparent Deterministic Chaos in Spontaneously Bursting Hippocampal Slices

B. Biswal and C. Dasgupta
Phys. Rev. Lett. 88, 088102 – Published 7 February 2002
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Abstract

A neural network model that exhibits stochastic population bursting is studied by simulation. First return maps of interburst intervals exhibit recurrent unstable-periodic-orbit(UPO)-like trajectories similar to those found in experiments on hippocampal slices. Applications of various control methods and surrogate analysis for UPO detection also yield results similar to those of experiments. Our results question the interpretation of the experimental data as evidence for deterministic chaos and suggest caution in the use of UPO-based methods for detecting determinism in time-series data.

  • Received 7 June 2001

DOI:https://doi.org/10.1103/PhysRevLett.88.088102

©2002 American Physical Society

Authors & Affiliations

B. Biswal1,2 and C. Dasgupta3,4

  • 1ICA1, University of Stuttgart, Pfaffenwaldring 27, D-70569 Stuttgart, Germany
  • 2Department of Physics, Sri Venkateswara College, University of Delhi, New Delhi, India
  • 3Department of Physics, Indian Institute of Science, Bangalore-560 012, India
  • 4Condensed Matter Theory Unit, JNCASR, Bangalore-560 064, India

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Vol. 88, Iss. 8 — 25 February 2002

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