Fabio Schittler Neves

Publications (3)14.74 Total impact

• Article: Computation by switching in complex networks of States.

  Fabio Schittler Neves, Marc Timme
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  ABSTRACT: Complex networks of dynamically connected saddle states persistently emerge in a broad range of high-dimensional systems and may reliably encode inputs as specific switching trajectories. Their computational capabilities, however, are far from being understood. Here, we analyze how symmetry-breaking inhomogeneities naturally induce predictable persistent switching dynamics across such networks. We show that such systems are capable of computing arbitrary logic operations by entering into switching sequences in a controlled way. This dynamics thus offers a highly flexible new kind of computation based on switching along complex networks of states.
  Physical Review Letters 07/2012; 109(1):018701. · 7.37 Impact Factor
• Source

  Available from: Marc Timme

  Article: Computation by Switching in Complex Networks of States

  Fabio Schittler Neves, Marc Timme
  [show abstract] [hide abstract]
  ABSTRACT: Complex networks of dynamically connected saddle states persistently emerge in a broad range of high-dimensional systems and may reliably encode inputs as specific switching trajectories. Their computational capabilities, however, are far from being understood. Here, we analyze how symmetry-breaking inhomogeneities naturally induce predictable persistent switching dynamics across such networks. We show that such systems are capable of computing arbitrary logic operations by entering into switching sequences in a controlled way. This dynamics thus offers a highly flexible new kind of computation based on switching along complex networks of states.
  Physical Review Letters 07/2012; 109:018701. · 7.37 Impact Factor
• Article: Controlled perturbation-induced switching in pulse-coupled oscillator networks

  Fabio Schittler Neves, Marc Timme
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  ABSTRACT: Pulse-coupled systems such as spiking neural networks exhibit nontrivial invariant sets in the form of attracting yet unstable saddle periodic orbits where units are synchronized into groups. Heteroclinic connections between such orbits may in principle support switching processes in these networks and enable novel kinds of neural computations. For small networks of coupled oscillators, we here investigate under which conditions and how system symmetry enforces or forbids certain switching transitions that may be induced by perturbations. For networks of five oscillators, we derive explicit transition rules that for two cluster symmetries deviate from those known from oscillators coupled continuously in time. A third symmetry yields heteroclinic networks that consist of sets of all unstable attractors with that symmetry and the connections between them. Our results indicate that pulse-coupled systems can reliably generate well-defined sets of complex spatiotemporal patterns that conform to specific transition rules. We briefly discuss possible implications for computation with spiking neural systems.
  Journal of Physics A, v.42 (2009).