Abstract / Description of output
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.
Original language | English |
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Number of pages | 75 |
Journal | eLIFE |
Volume | 4 |
DOIs | |
Publication status | Published - 6 Jul 2015 |
Keywords / Materials (for Non-textual outputs)
- attractor networks
- cognition
- entorhinal cortex
- inhibition
- oscillation
- synapse
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Matthew Nolan
- Deanery of Biomedical Sciences - Personal Chair of Neural Circuits and Computation
- Centre for Discovery Brain Sciences
- Edinburgh Neuroscience
Person: Academic: Research Active