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Compensating for synaptic loss in Alzheimer’s disease

Abuhassan, Kamal, Coyle, Damien, Belatreche, Ammar and Maguire, LP (2014) Compensating for synaptic loss in Alzheimer’s disease. Journal of Computational Neuroscience, 36 (1). pp. 19-37. [Journal article]

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URL: http://dx.doi.org/10.1007/s10827-013-0462-8

DOI: 10.1007/s10827-013-0462-8

Abstract

Confirming that synaptic loss is directly related to cognitive deficit in Alzheimer’s disease (AD) has been the focus of many studies. Compensation mechanisms counteract synaptic loss and prevent the catastrophic amnesia induced by synaptic loss via maintaining the activity levels of neural circuits. Here we investigate the interplay between various synaptic degeneration and compensation mechanisms, and abnormal cortical oscillations based on a large-scale network model consisting of 100,000 neurons exhibiting several cortical firing patterns, 8.5 million synapses, short-term plasticity, axonal delays and receptor kinetics. The structure of the model is inspired by the anatomy of the cerebral cortex. The resultsof the modelling study suggest that cortical oscillations respond differently to compensation mechanisms. Local compensation preserves the baseline activity of theta (5–7 Hz) and alpha (8–12 Hz) oscillations whereas delta (1–4Hz) and beta (13–30 Hz) oscillations are maintained via global compensation. Applying compensation mechanisms independently shows greater effects than combining both compensation mechanisms in one model and applying them in parallel. Consequently, it can be speculated that enhancing local compensation might recover the neural processes and cognitive functions that are associated with theta and alpha oscillations whereas inducing global compensation might contribute to the repair of neural (cognitive) processes which are associated with delta and beta band activity. Compensation mechanisms may vary across cortical regions and the activation of inappropriate compensation mechanism in a particular region may fail to recover network dynamics and/or induce secondary pathological changes in the network.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:26437
Deposited By: Prof Damien Coyle
Deposited On:21 Aug 2013 14:38
Last Modified:10 Mar 2014 15:20

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