Noise promotes independent control of gamma oscillations and grid firing within recurrent attractor networks
Abstract
Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation. With moderate noise, variation in excitatory or inhibitory synaptic strength tunes the amplitude and frequency of gamma activity without disrupting grid firing. This beneficial role for noise results from disruption of epileptic-like network states. Thus, moderate noise promotes independent control of multiplexed firing rate- and gamma-based computational mechanisms. Our results have implications for tuning of normal circuit function and for disorders associated with changes in gamma oscillations and synaptic strength.
Article and author information
Author details
Reviewing Editor
- Frances K Skinner, University Health Network, Canada
Version history
- Received: January 11, 2015
- Accepted: July 4, 2015
- Accepted Manuscript published: July 6, 2015 (version 1)
- Version of Record published: July 21, 2015 (version 2)
Copyright
© 2015, Solanka et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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