Example of Personalized Therapeutics in Groups with Heterogeneous Pathologies. The personalized therapeutics approach is illustrated using the example of a group of patients with pathological decreases in LTP, LTD, Inhibition, and Connectivity, as have been reported in various models related to Schizophrenia, for example (Table 1). To provide analogy with the heterogeneous genetic and environmental factors seen in human patients, the 100 optimal neural networks were each perturbed with randomly varying degrees of decreases in each synaptic property, such that an average pattern completion bias was seen in the population, consistent with average rescue of memory impairment by increased inhibition in populations of Schizophrenia patients (see Discussion). A) The maximal error in each of the pathologically perturbed networks is illustrated. For direct comparison with the wild-type networks in Figure 5, values of LTP, LTD, and inhibition are illustrated, while connectivity rates are not shown. B) The pattern completion and separation error rates with 30 patterns stored are illustrated for each of the individual pathological networks. Completion or separation error rates exceeding average tolerable limits of wild-type networks are illustrated with dark red or dark blue, respectively. Red arrowheads indicate assayed pattern separation biases, where GABAAR antagonists would be prescribed, while blue error heads indicate pattern completion biases, where GABAAR positive modulators would be prescribed (majority of individuals). C) The maximal error rates in each network following therapeutic correction as indicated in panel B, is shown. D) The pattern completion and separation error rates following therapeutic improvement with drugs targeting inhibition are shown for the individual networks.