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The Sync/deSync model: How a synchronized hippocampus and a de-synchronized neocortex code memories

Parish, George, Hanslmayr, Simon, Bowman, Howard (2018) The Sync/deSync model: How a synchronized hippocampus and a de-synchronized neocortex code memories. The Journal of Neuroscience, 38 (14). pp. 3428-3440. ISSN 0270-6474. (doi:10.1523/JNEUROSCI.2561-17.2018) (KAR id:66377)

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Neural oscillations are important for memory formation in the brain. The de-synchronisation of Alpha (10Hz) oscillations in the neo-cortex has been shown to predict successful memory encoding and retrieval. However, when engaging in learning, it has been found that the hippocampus synchronises in Theta (4Hz) oscillations, and that learning is dependent on the phase of Theta. This inconsistency as to whether synchronisation 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 synchronisation of Theta during successful memory encoding.

We present a spiking neural network (the Sync/deSync model) of the neo-cortical 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 de-synchronisation of neo-cortical Alpha and the synchronisation of hippocampal Theta are necessary for successful memory encoding and retrieval.

Item Type: Article
DOI/Identification number: 10.1523/JNEUROSCI.2561-17.2018
Uncontrolled keywords: oscillations; computational modeling; episodic memory; theta; alpha; EEG
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
R Medicine > RC Internal medicine > RC321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Howard Bowman
Date Deposited: 14 Mar 2018 10:35 UTC
Last Modified: 16 Feb 2021 13:53 UTC
Resource URI: (The current URI for this page, for reference purposes)
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