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Quantitative properties of a feedback circuit predict frequency-dependent pattern separation.

Oliver Braganza1, Daniel Mueller-Komorowska1,2, Tony Kelly1

  • 1Institute for Experimental Epileptology and Cognition Research, University of Bonn, Bonn, Germany.

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|February 21, 2020
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Summary
This summary is machine-generated.

Feedback inhibition in the mouse dentate gyrus aids pattern separation. This circuit

Keywords:
dentate gyrusfeedback inhibitiongamma oscillationsmicrocircuit motifmouseneurosciencepattern separation

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Area of Science:

  • Neuroscience
  • Computational Neuroscience

Background:

  • Feedback inhibitory motifs are crucial for pattern separation across species.
  • The precise mechanisms by which feedback circuits achieve pattern separation of temporally structured input in mammals remain unclear.

Purpose of the Study:

  • To quantitatively determine the properties of net feedback inhibition in the mouse dentate gyrus.
  • To investigate the role of feedback inhibition in pattern separation of theta-modulated inputs.

Main Methods:

  • Quantitative analysis of net feedback inhibition in the mouse dentate gyrus.
  • Computational modeling of feedback inhibition and pattern separation.

Main Results:

  • Net feedback inhibition is steeply recruited with a low dynamic range (0-4% of active GCs) and a non-uniform spatial profile.
  • Frequency-dependent facilitation of net feedback inhibition was observed, driven by mossy fiber inputs.
  • Feedback circuits significantly contribute to pattern separation of theta-modulated inputs within theta cycles.
  • Pattern separation was selectively enhanced at gamma frequencies, particularly for similar inputs.

Conclusions:

  • Frequency-dependent pattern separation is a key feature of the dentate gyrus feedback inhibitory microcircuit.
  • The feedback circuit robustly boosts pattern separation, especially at gamma frequencies for similar inputs.