Computational Model of Neurogenesis
Inventors: James B. Aimone, Janet Wiles, and Fred H. Gage
Potential Uses: CNS, Software
Role of Neurogenesis in Pattern Separation Neural Networks
Neural Network Model: (A) Simplified block diagram of network architecture. (B) Sketch of newborn granule cell maturation
Adult neurogenesis in the hippocampus leads to the incorporation of thousands of new granule cells into the dentate gyrus (DG) every month, but its function remains unclear. Using a computational model we demonstrated that adult neurogenesis may make three separate but related contributions to memory formation.
This approach to modeling adult neurogenesis differs considerably from that of previous models of adult neurogenesis, including (1) the inclusion of details about the maturation process; (2) simulation over long time scales, allowing successive generations of new neurons to populate the DG; and (3) assaying DG function by measuring pattern separation while using biologically derived inputs.
The methods used in this model can be used for profiling or predicting a variety of events in a diverse number of fields, including: in the field of biotechnology, for example, for genomics analysis and for profiling brain networks and brain network modeling; information processing; predicting or profiling events in various finance systems, i.e., in stock markets, commodities etc.; and predicting or profiling information in profiling systems, such as applications in homeland security.
Patent Status: U.S. Patent Application Filed January 2009
Publications: James B. Aimone, Janet Wiles, and Fred H. Gage. 2009. Computational Influence of Adult Neurogenesis on Memory Encoding. Neuron 61:187-202 Supplement.
Press Release: Newborn brain cells "time-stamp" memories
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