Multi-timescale cascade models of synaptic plasticity

DESCRIPTION (provided by applicant): Changes in the efficacy of synaptic transmission in neural circuits are thought to underlie memory and learning. The traditional analogy is that of the synapse acting as a switch to retain a memory trace of the activity evoked by a particular experience. However, experience and neuronal activity are ongoing, and memory storage is a continuous process throughout life. Both experimental and theoretical work has shown that this ongoing activity and the plasticity it induces are highly destructive to memory traces maintained in synaptic efficacies. How can a synaptic memory trace be retained for a long time in the face of ongoing plasticity? Surprisingly, this question has received little theoretical attention. The solution proposed in this application is that synaptic plasticity does not act as a static, on-off switching mechanism, but rather as a complex, dynamic biochemical cascade. Preliminary models of such cascades indicate that they dramatically extend the amount of time over which memories can be retained. Cascade models provide a framework for understanding and accounting for the enormous complexity of the biochemical processes that underlie synaptic plasticity. The cascade approach to plasticity will be applied in network models to the problem of recognition memory and the response suppression that is its neural correlate. The proposed research will combine theoretical studies with both existing and new data to explore the implications of plasticity cascades for memory retention. Because these models account for the full range of dynamics exhibited by synaptic plasticity, they permit, for the first time, a detailed study of the dynamic aspects of memory, learning, and forgetting and their relationship to synaptic plasticity. The proposed research has important implications for the physiological basis of memory and its pathologies, and for our understanding of biochemical cascades and their role in shaping the dynamics of biological processes.