The Sync/deSync model: how a synchronized hippocampus and a desynchronized neocortex code memories

Parish, G., Hanslmayr, S. and Bowman, H. (2018) The Sync/deSync model: how a synchronized hippocampus and a desynchronized neocortex code memories. Journal of Neuroscience, 38(14), pp. 3428-3440. (doi: 10.1523/JNEUROSCI.2561-17.2018) (PMID:29487122) (PMCID:PMC6596040)

Abstract

Neural oscillations are important for memory formation in the brain. The desynchronization of alpha (10 Hz) oscillations in the neocortex has been shown to predict successful memory encoding and retrieval. However, when engaging in learning, it has been found that the hippocampus synchronizes in theta (4 Hz) oscillations, and that learning is dependent on the phase of theta. This inconsistency as to whether synchronization is “good” for memory formation leads to confusion over which oscillations we should expect to see and where during learning paradigm experiments. This paper seeks to respond to this inconsistency by presenting a neural network model of how a well functioning learning system could exhibit both of these phenomena, i.e., desynchronization of alpha and synchronization of theta during successful memory encoding. We present a spiking neural network (the Sync/deSync model) of the neocortical and hippocampal system. The simulated hippocampus learns through an adapted spike-time dependent plasticity rule, in which weight change is modulated by the phase of an extrinsically generated theta oscillation. Additionally, a global passive weight decay is incorporated, which is also modulated by theta phase. In this way, the Sync/deSync model exhibits theta phase-dependent long-term potentiation and long-term depression. We simulated a learning paradigm experiment and compared the oscillatory dynamics of our model with those observed in single-cell and scalp-EEG studies of the medial temporal lobe. Our Sync/deSync model suggests that both the desynchronization of neocortical alpha and the synchronization of hippocampal theta are necessary for successful memory encoding and retrieval.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Hanslmayr, Professor Simon
• Authors: Parish, G., Hanslmayr, S., and Bowman, H.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
• Journal Name: Journal of Neuroscience
• Publisher: The Society for Neuroscience
• ISSN: 0270-6474
• ISSN (Online): 1529-2401
• Published Online: 27 February 2018