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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Generating functionals for autonomous latching dynamics in attractor relict networks.

Mathias Linkerhand1, Claudius Gros

  • 1Institute for Theoretical Physics, Goethe University Frankfurt, Germany.

Scientific Reports
|June 21, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces attractor relict networks with autonomous latching dynamics. Conflicting optimization targets, or stress, can induce intermittent bursting dynamics in these neural networks.

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Area of Science:

  • Computational neuroscience
  • Theoretical neuroscience
  • Complex systems

Background:

  • Attractor networks are fundamental models in neuroscience for understanding neural computation and memory.
  • Destabilizing attractors can lead to novel network dynamics, such as latching transitions.
  • Understanding the impact of conflicting objectives on neural network dynamics is crucial.

Purpose of the Study:

  • To propose a novel method for constructing attractor relict networks exhibiting autonomous latching dynamics.
  • To investigate the influence of objective function stress, arising from conflicting optimization targets, on network dynamics.
  • To characterize the resulting dynamics under different stress conditions.

Main Methods:

  • Utilizing two generating functionals: a Hopfield energy functional and an information-theoretical functional.
  • Constructing attractor relict networks by coupling local, slowly adapting variables to an attractor network.
  • Analyzing the impact of objective function stress by varying target activity levels between the two functionals.

Main Results:

  • The proposed method successfully generates attractor relict networks with ongoing autonomous latching dynamics.
  • Absence of objective function stress (identical target activity levels) results in regular latching dynamics.
  • Presence of objective function stress (differing target activity levels) induces intermittent bursting latching dynamics.

Conclusions:

  • Attractor relict networks offer a framework for studying complex neural dynamics beyond stable attractors.
  • Objective function stress is a critical factor modulating the nature of latching dynamics in these networks.
  • The findings provide insights into how conflicting internal goals might shape neural activity patterns.