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Optogenetic Entrainment of Hippocampal Theta Oscillations in Behaving Mice
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Oscillatorylike behavior in feedforward neuronal networks.

Alexandre Payeur1, Leonard Maler2, André Longtin3

  • 1Department of Physics, University of Ottawa, 150 Louis-Pasteur, Ottawa, Canada K1N 6N5.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|August 15, 2015
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Summary
This summary is machine-generated.

Neural networks can generate rhythmic activity using feedforward circuits, explaining temporal decorrelation in gamma-band oscillations. This finding challenges the traditional view of recurrent networks being solely responsible for such rhythmic neural dynamics.

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Area of Science:

  • Computational Neuroscience
  • Systems Neuroscience
  • Neural Oscillations

Background:

  • Recurrent neural networks are traditionally associated with generating rhythmic activity.
  • Gamma-band oscillations are crucial for various cognitive functions.
  • Temporal decorrelation of neural activity is a key aspect of information processing.

Purpose of the Study:

  • To demonstrate rhythmic activity generation in feedforward neural networks.
  • To provide a mechanism for temporal decorrelation of gamma-band oscillations.
  • To compare spiking activity and spike-train statistics between feedforward and recurrent networks.

Main Methods:

  • Comparison of spiking activity between delayed recurrent and feedforward inhibitory neural networks.
  • Analysis of spike-train statistics under correlated input.
  • Application of Taylor expansion to network susceptibility (frequency-dependent gain function).
  • Investigation using linear response theory.

Main Results:

  • Feedforward networks can generate rhythmic activity, similar to recurrent networks.
  • High neuronal noise and short axonal delays lead to similar spike-train statistics in both network types.
  • Indirect spike correlations in feedforward networks can mimic direct correlations in recurrent networks under specific conditions.
  • Distributed delays further enhance the similarity between network outputs.

Conclusions:

  • Rhythmic neural activity and temporal decorrelation of gamma-band oscillations can emerge from feedforward circuitry.
  • Network connectivity (feedforward vs. recurrent) is not the sole determinant of oscillatory dynamics.
  • Neuronal noise and axonal delays play critical roles in shaping network output and inter-neuronal correlations.