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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.
Elife
|February 21, 2020
Summary
Feedback inhibition in the mouse dentate gyrus aids pattern separation. This circuit
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.
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