Rowan, Mark Stephen (2013)
Ph.D. thesis, University of Birmingham.
Homeostatic synaptic scaling mechanisms, which normally balance potentiation during learning, may direct the progression of the disease throughout the brain as cells scale up their sensitivity to compensate for lost activation. Such a mechanism would be likely to target those cells with the lowest contribution of information to the network in early stages of the disease, resulting in delayed onset of cognitive symptoms and making timely intervention and treatment of the disease more difficult.
These predictions were investigated in a Hopfield-type neural network. Lesioning according to the scaling-driven progression hypothesis of AD showed that the pathology is capable of targeting neurons with lowest information contribution to the network at early stages of the disease. Additional experiments revealed a positive-feedback loop by which noisy compensatory synaptic scaling mechanisms caused the accelerated degradation of recent memories, which were themselves preferentially used as drivers of the compensatory mechanism.
The hypothesis was then tested in a biologically-realistic spiking model of neocortex. Cell death, modelled as an abstract excitotoxicity mechanism based on scaling factor values, confirmed the earlier results and showed that low-information neurons (and neurons from cortical layers with the lowest information contribution) were again the first to die in scaling-driven AD pathology.
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