期刊
HIPPOCAMPUS
卷 27, 期 1, 页码 89-110出版社
WILEY
DOI: 10.1002/hipo.22675
关键词
computational model; hippocampus; network model; memory
资金
- European Research Council (ERC) [ERC-2012-StG-311435]
The hippocampus plays a key role in pattern separation, the process of transforming similar incoming information to highly dissimilar, nonverlapping representations. Sparse firing granule cells (GCs) in the dentate gyrus (DG) have been proposed to undertake this computation, but little is known about which of their properties influence pattern separation. Dendritic atrophy has been reported in diseases associated with pattern separation deficits, suggesting a possible role for dendrites in this phenomenon. To investigate whether and how the dendrites of GCs contribute to pattern separation, we build a simplified, biologically relevant, computational model of the DG. Our model suggests that the presence of GC dendrites is associated with high pattern separation efficiency while their atrophy leads to increased excitability and performance impairments. These impairments can be rescued by restoring GC sparsity to control levels through various manipulations. We predict that dendrites contribute to pattern separation as a mechanism for controlling sparsity. (C) 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.
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