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Figure 3 | BMC Neuroscience

Figure 3

From: Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy

Figure 3

Synaptic Connectivity and Plasticity. A) Example matrix of potential synaptic interconnections between the 100 excitatory neurons in a network with 50% connectivity. Gray squares show possible (silent) synapses, and white squares indicate the absence of anatomical synapses, as a function of postsynaptic (x axis) and presynaptic (y axis) neuron identity. B) Synaptic plasticity was implemented with the parameter, gMaxAMPA specifying the strength of a fully potentiated synapse resulting from co-activation of a presynaptic and postsynaptic neuron during storage of a stimulus pattern. The parameter γLTD determined the strength of depression resulting from asynchronous activation of a presynaptic and postsynaptic neuron during different stimulus patterns within a set of stored memories. The resulting profile of plasticity for different numbers of asynchronous activations per synchronous activation is show for γLTD values logarithmically spaced between 0.1 (top series) and 10 (bottom series). C) The synaptic strength matrix of the example network with 50% connectivity is shown after 5 patterns have been stored, using an intermediate value of γLTD. Un-strengthened (silent) synapses are white, and the strengths of synapses ranging from fully potentiated to strongly depressed are illustrated with the color scale from red to blue. D) The synaptic strength matrix of the example network is shown after 30 patterns have been stored. Note that while more synaptic connections have been potentiated, accumulation of overlap between the patterns has resulted in stronger average depression in the network compared to the storage of 5 patterns.

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