Computational design of enhanced learning protocols

Nat Neurosci. 2011 Dec 25;15(2):294-7. doi: 10.1038/nn.2990.

Abstract

Learning and memory are influenced by the temporal pattern of training stimuli. However, the mechanisms that determine the effectiveness of a particular training protocol are not well understood. We tested the hypothesis that the efficacy of a protocol is determined in part by interactions among biochemical cascades that underlie learning and memory. Previous findings suggest that the protein kinase A (PKA) and extracellular signal-regulated kinase (ERK) cascades are necessary to induce long-term synaptic facilitation (LTF) in Aplysia, a neuronal correlate of memory. We developed a computational model of the PKA and ERK cascades and used it to identify a training protocol that maximized PKA and ERK interactions. In vitro studies confirmed that the protocol enhanced LTF. Moreover, the protocol enhanced the levels of phosphorylation of the transcription factor CREB1. Behavioral training confirmed that long-term memory also was enhanced by the protocol. These results illustrate the feasibility of using computational models to design training protocols that improve memory.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Analysis of Variance
  • Animals
  • Aplysia
  • CREB-Binding Protein / metabolism
  • Cells, Cultured
  • Coculture Techniques
  • Computer Simulation*
  • Cyclic AMP-Dependent Protein Kinases / metabolism
  • Electric Stimulation
  • Extracellular Signal-Regulated MAP Kinases / metabolism
  • Functional Laterality
  • Ganglia, Invertebrate / cytology
  • Humans
  • Learning / drug effects
  • Learning / physiology*
  • Long-Term Potentiation / physiology
  • Models, Biological*
  • Motor Neurons / physiology
  • Sensory Receptor Cells / physiology
  • Serotonin / pharmacology
  • Signal Transduction

Substances

  • Serotonin
  • CREB-Binding Protein
  • Cyclic AMP-Dependent Protein Kinases
  • Extracellular Signal-Regulated MAP Kinases