Modeling the Molecular Networks that Underlie the Formation and Consolidation of Memory

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Molecular processes that underlie the induction and consolidation of long-term memory (LTM) are the subjects of intensive research, and studies are providing a wealth of empirical data that relate aspects of memory to specific intracellular signaling pathways. For example, empirical studies are elucidating the roles played by extracellular factors (e.g. growth factors), kinase activity, and transcriptional regulation in induction and consolidation of memory. Due in part to the complexity and nonlinear features of these molecular pathways, it is difficult to develop an intuitive understanding of the ways in which these pathways respond to stimulus protocols or pharmacological manipulations or are affected by single-site molecular lesions. To provide a better understanding of the processes underlying LTM, the present proposal will develop quantitative models of the molecular pathways that underlie two well-characterized models of LTM: i) long-term synaptic facilitation (LTF) and ii) long-term synaptic potentiation (LTP). Parameters will be constrained by empirical data. Parameter sensitivity analysis and a novel cluster analysis will assess model robustness. Aim 1 will extend our model for LTF, which describes the regulation of transcription by PKA and ERK via phosphorylation of the transcription factors CREB1 and CREB2. The extended model will include components of additional intra- and extracellular feedback loops (e.g., TGFβ, and ApNT), an additional transcription factor (C/EBP), ribosomal s6 kinase (RSK) and p38 MAP kinase. In Aim 2, this model will be used to predict stimulus protocols, as well as pharmacological treatments, that enhance LTF and that rescue impaired LTF. Aim 3 will extend our current model of LTP, which describes roles of several kinase pathways (e.g., MAPK, PKA, PKC, and CAMKII) and histone acetylation. The model will incorporate a recently delineated BDNF positive-feedback loop, which leads to activation of ERK, phosphorylation of CREB1, and induction of transcription necessary for the consolidation of LTP. We will simulate stimulus protocols and drug effects to predict treatments that could rescue impaired memory mechanisms in Rett syndrome, which is caused by mutations that alter the activity of the transcription factor MeCP2, and that can rescue impaired mechanisms in Rubinstein-Taybi syndrome, which is caused by mutations in CREB binding protein. This proposed approach of using models to predict novel learning paradigms and/or drug treatments that restore normal plasticity, is an innovative methodology that could ultimately lead to the development of new strategies for the treatment of cognitive disorders.